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Ethylene removal efficiency and bacterial community diversity of a natural zeolite biofilter
Bioresource Technology 102 (2011) 576–584
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Ethylene removal efficiency and bacterial community diversity of a natural zeolite biofilter Yuming Fu, Lingzhi Shao, Ling Tong, Hong Liu * Laboratory of Environmental Biology and Life Support Technology, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
a r t i c l e
i n f o
Article history: Received 30 May 2010 Received in revised form 29 July 2010 Accepted 29 July 2010 Available online 4 August 2010 Keywords: Ethylene Natural zeolite PCR-DGGE Biofilter Bacterial diversity
a b s t r a c t To establish an economical and environmentally friendly technology for ethylene removal from horticultural facilities and industrial point sources, a bench-scale natural zeolite biofiltration system was developed in this study. The system was evaluated for its performance in removing ethylene from an artificially contaminated air stream and characterized for its bacterial diversity under varied ethylene concentrations, and in different spatial stages of the filter. The biofilter enabled to approximately 100% remove ethylene at loading rates of 0.26–3.76 g m3 h1 when operated with inoculum containing enriched ethylene-degrading bacteria. The bacterial diversity and abundance varied with the height of the biofilter. Moreover, the occurrence and predominance of specific bacterial species varied with the concentrations of ethylene introduced into the biofilter, as observed by PCR-DGGE methods. Phylogenetic analysis indicated that the biofilter system supported a diverse community of ethylene-degrading bacteria, with high similarity to species in the classes Betaproteobacteria, Gammaproteobacteria, Bacilli, and Actinobacteria. Ó 2010 Elsevier Ltd. All rights reserved.
1. Introduction Ethylene (C2H4), one of the hazardous volatile organic compounds (VOCs), causes serious air pollution problems, for example, it produces carbon monoxide and ozone, and prevents the removal of chlorine in stratosphere. As an air pollutant, it was shown to originate from a variety of natural and anthropogenic sources such as the biosynthesis of plants and microorganisms in soils (Sawada and Totsuka, 1986), waste gas and leaks in petrochemical complexes, automobile exhaust, and burning of organic materials (Temple et al., 1998). Unlike other air pollutants, ethylene is a plant hormone that controls plant physiological processes such as growth, flowering and senescence. Accumulation of atmospheric ethylene is able to reduce vegetative growth, flower and fruit development and accelerate normal ageing of plant tissues (Manning and Feder, 1980). Growing plants in enclosed or semienclosed environments, such as greenhouse, easily result in an elevated concentration of ethylene. Also, significant accumulation of ethylene may occur in horticultural storage facilities due to endogenous production by the fruit and vegetable (Hoyer, 1995). Thus, it is essential to take removal of such pollutant into consideration when dealing with the gaseous waste products and maintaining plant normal growth and postharvest quality.
* Corresponding author. Tel./fax: +86 10 82339837. E-mail address: [email protected] (H. Liu). 0960-8524/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.biortech.2010.07.119
Despite the effectiveness of physical/chemical methods in destroying ethylene, the disadvantages of requiring replenishing the ethylene-destroying agent and high costs for operation have motivated a desire for more easily and economically beneficial technologies (Kim, 2006; Schnelle and Brown, 2002). One potential alternative is the biological catalysis using biofilter that has been known as a reliable and cost-effective biofiltration technology. In the design and operation of the biofiltration process, the selection of a suitable media is critical to enable the required removal efficiency to be achieved (He et al., 2007). Various types of biofilters removing ethylene, based on different filter media such as peat-soil and activated carbon have been studied (Elsgaard, 1998, 2000). Natural zeolite is also a well-known, traditional packing material for biofilters. It not only provides several advantages similar to other typical packing materials such as high porosity for easy air flow, extensive surface area for biofilm attachment, but also has high moisture holding capacity, diverse nutrient content, very slow degradation rate as well as more economic advantages (Stoeckinger, 2004). However, there is little information available in literature about the removal ethylene by the biofilter packed with natural zeolite. Moreover, since there is also a lack of information on microbial communities in biofilter, there is a need for a database of microbial communities that include the ethylene-degrading bacteria in biofilter materials. In this study, ethylene removal by a natural zeolite as a filter material for a bench-scale biofilter was evaluated at different ethylene loading rates. Analysis of the abundance, diversity, and
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spatial distribution of bacteria in the packing media was conducted using culture-dependent and denaturing gradient gel electrophoresis (DGGE) methods. The dominant ethylene-degrading bacteria in the biofilter were also identified by sequencing. The results show promise for the development of zeolite biofilter systems as an effective option for ethylene control for the plant cultivating chambers, horticultural storage facilities, and petrochemical industries. 2. Methods 2.1. Microorganisms and natural zeolite Potential biofilter inoculum was obtained from activated sludge in the Gaobeidian Wastewater Treatment Plant in the City of Beijing, China. Ten milliliters of the activated sludge was homogenized with 90 mL sterile phosphate-buffered saline (PBS; 137 mM NaCl, 2.7 mM KCl, 4.3 mM Na2HPO4, 1.4 mM KH2PO4, [pH 7.3]) on a rotary shaker at 25 °C and 250 rpm for 1 h. One hundred milliliters of the homogenized mixture was incubated in a 3 L vessels containing 1.5 L of mineral salts medium without added carbon sources, and ethylene was added to a headspace concentration of ca. 1% as recommended by the prior report (Tambwekar, 2002). The culture was incubated with shaking (180 rpm) at 25 °C, and the ethylene was replenished to ca. 1% when its concentration dropped below 0.5% (assayed by gas chromatographic analysis) under the aerobic condition for 20 days. The mineral salts medium had the following components according to the previous report (Daigger, 1979),on a mg L1 basis: K2HPO4, 4350; KH2P04, 3400; NH4C1, 1010; MgSO47H2O, 15; HCl, 3.93; CaCl22H20, 2; FeCl36H20, 1.5; MnS04H20, 0.45; CoCl26H20, 0.15; ZnCl2, 0.15; CuCl22H20, 0.05; Na2Mo042H20, 0.05; H3BO3, 0.015. All chemicals used were obtained from Sigma–Aldrich (Beijing, China) and were of analytical grade or higher. The natural zeolite used as a filter media in this study was a commercial sample, supplied from Kaibiyuan Company, Beijng, China. Its characteristics were shown in Table 1. After washed with tap water and dried at a room temperature, the natural zeolite was transferred into the biofilter. To investigate the ability of this material to adsorb ethylene without bacteria, batch studies were performed on 10 g of the packing samples. The packing samples were first sterilized by autoclaving, and their moisture contents were adjusted to 50%. The samples were added to a 50 mL vial inletting 100, 500, or 1000 ppm of ethylene. The weight change of the natural zeolite was measured at 24, 48, 72 h and on the 7th day using an Ohaus dv/80–210 balance (Ohaus, USA), respectively. No change among 48, 72 h, and day 7 was observed, suggesting the equilibrium of the system. Equilibrium concentrations in the gas phase (Ce) and absorbed ethylene concentrations in the packing materials (qe) were used to estimate the Freundlich model coefficients (KF and N) with a best fit method, according to the Freundlich model equation (qe ¼ K F C Ne ). The KF and N estimated for zeolite were shown in Table S1. The results indicated the low ethylene adsorptive capacity of the zeolite. The Freundlich model equation yielded the abiotic ethylene adsorption capacities for zeolite of 4.68 mg/kg, at the equilibrium gas-phase concentration of 50 ppm. Using the abiotic adsorption capacities and a simple mass balance, the adsorptive capacity of zeolite was Table 1 Characteristics of the natural zeolite. Size range (mm) Density (kg m3) Bulk density (kg m3) Specific surface area (m2 g1) Porosity (%) Silicon/aluminum ratio
3–5 2315 1014 6.84 43.83 4.1–5.7
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predicted to be exhausted during 18 h and that ethylene removal after that time point would likely be attributed to the bacterial activity in the biofilter. 2.2. Biofilter and operation To assess the feasibility of the proposed biofiltration system, a lab-scale biofilter was built, consisting of a transparent rigid plexiglass column with 8 cm diameter, 70 cm length and 45 cm filter bed height (Fig. 1). The filter bed was composed of three identical stages, each equipped with gas and medium sampling ports. The biofilter was inoculated with the culture enriched in the mineral salts medium described above and the initial volatile suspended solid concentration of inoculated solution was 50 mg L 1. The nutrient solution (mineral salts medium) was introduced at the top of the biofilter through a water distributor using a Cole-Parmer metering pump (USA) at a rate of 800 mL day1. The solution was provided for the maintenance of 43–51% moisture content of zeolite in the biofilter. A mixture of atmospheric air and ethylene in nitrogen (N2) (Haipu, Beijing, China) was supplied to the biofilter via two mass flow controllers. Before reaching the inlet, the gas was humidified by being bubbled through a flask containing distilled water. The ethylene concentration of the gas flow was kept constant by adjusting the flow rate of the air stream and ethylene. Biofilter operation was characterized in room temperature by four consecutive sets of operating conditions, described here and summarized in Table 2. 2.3. Sampling and gas analysis Gaseous samples were periodically collected at the inlet and outlet of each stage of the bioreactors by 1.6 L Tedlar gas sampling bags (Cole-Parmer, USA). Sampling was conducted over a 7 min period. Before every sampling, the bags were filled with air and cleaned out by an air pump for three times. Packing samples were collected from each stage of the biofilter on days 0 (original inoculum), 15, 45, 75, and 105 for subsequent analysis. A sterile metal corer was used to take samples of ca. 10 g (wet weight) of zeolite from the biofilter via sampling ports, when biofilter was taken down. Each packing sample was divided into two parts for determination of bacterial amounts and DNA extraction. The parts for determination of bacterial amounts and DNA extraction were stored at 4 and 20 °C, respectively. Ethylene and carbon dioxide (CO2) were analyzed with a gas chromatography (GC) 7890 (Tianmei, Shanghai, China) using a glass column packed with GDX-401. The ethylene detection limit was 105 ppm. The GC was coupled to a flame ionization detector (FID) and N2 served as the carrier gas at a flow rate of 40 mL min1. Temperatures for column, injector, and detector were 60, 130, and 380 °C, respectively. The samples from the gas sampling bags were directly injected into the injector port of GC using a 1 mL gas syringe (Agilent, USA) with a push-button valve. Twice sample injections and a standard curve (R2 = 0.99) were used for all data analyses. In order to display the results of this study, three quantitative parameters including the inlet loading, the removal efficiency and the elimination capacity (EC) have been used and were presented in Table 3. 2.4. Viable bacterial plate counts and DNA extraction Routinely, 5 g (wet weight) of packing sample for determination of bacterial amounts was placed in 50 mL of sterile water and vortexed for 10 s every 2–3 min for 15 min. A tenfold dilution series of these samples was made by using sterile water. The dilutions were plated in triplicate on tryptic soy agar (TSA; Oxoid Ltd., United Kingdom). All plates were incubated at 20 °C for 7 days, and plates
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Fig. 1. Schematic of the biofilter system. (1) cylinder, (2) air blower, (3) gas flow meter, (4) mixing tank, (5) humidifier, (6) gas sampling port, (7)inlet gas port, (8) drainage, (9) filtering material sampling ports, (10) outlet gas port, (11) metering pump, and (12) water & nutrients.
Table 2 Summary of biofilter operating conditions. Phase
Days
Ethylene concentration (ppm)
Gas retention time (min)
Ethylene loading rate (g m3 h1)
I II III IV
1–20 21–50 51–90 91–109
50 200–300 600–700 1000
13 13 13 13
0.27 1.07–1.61 3.21–3.75 5.35
Table 3 Quantitative parameters. Definitions Inlet loading (IL) (g m3 h1)
in IL ¼ Q C V
Removal efficiency (RE) %
out 100% RE ¼ C in CC in
Elimination capacity (EC) (g m3 h1)
EC ¼ ðC in CVout ÞQ ¼ IL RE 3
where: Cin: the inlet ethylene concentration in g m Cout: outlet ethylene concentration in g m3. Q: the air flow rate in m3 h1. V: the biofilter bed volume in m3.
.
with between 30 and 200 colonies were counted (Calvo-Bado et al., 2003). For DNA extraction assay, packing samples of 5 g were mixed with 15 mL of extraction buffer (100 mM Tris–HCl [pH 8.0], 100 mM sodium EDTA [pH 8.0], 100 mM sodium phosphate [pH 8.0], 1.5 M NaCl, 1% CTAB) in 50 mL centrifuge tubes by horizontal shaking at 225 rpm for 30 min at 37 °C (Yin and Xu, 2009). Total DNA was extracted directly from the samples mixed buffer using a FastPrep DNA isolation kit according to the manufacturer’s instruction (QBIOGENE, USA). DNA extracts were stored at 70 °C before use. 2.5. PCR amplification and DGGE analysis Bacterial primers F968 with attached GC clamp (F968-GC) and R1378 were used for amplification of 16S rRNA of the total
bacterial community (Warmink and van Elsas, 2008). The PCR reactions were performed in 50 ll solution containing ca. 100 ng of the template DNA, 0.2 lM of each primer, 200 lM of each dNTP, 3.75 mM MgCl2, 6 PCR buffer and 5 U/ll Taq DNA polymerase (TakaRa, Japan). The thermal cycling was as follows: denaturation at 94 °C for 5 min, two cycles of: 1 min at 94 °C, 1 min at 60 °C, and 2 min 72 °C, followed by 10 of the same cycles with every cycle at 0.5 °C lower annealing temperature (until 55 °C), 20 cycles of 94 °C (1 min), 55 °C (1 min) and 72 °C (2 min), followed by final extension at 72 °C (10 min) (Garbeva et al., 2007). PCR products of high quality were purified and analyzed by denaturing gradient gel electrophoresis (DGGE). DGGE analysis was performed in the Bio-Rad D-GENE System (Bio-Rad, USA) using 35–70% gradients of denaturants. The separated amplicon bands in the gel were visualized on a UV-illuminator after staining with GelRed (Biotium, USA). To evaluate the bacterial community in the bioreactor of different stages, the positions and signal intensities of detected bands in the gel track were determined with a gel documentation system, Gel Doc 2000, Quantity-one 4.5.2 (Bio-Rad, USA). As a parameter for the structural diversity of the microbial community, the Shannon index of general diversity, H’ (Möhlenhoff et al., 2001), was calculated according to methods of Konstantinov et al. (2003). Based on the presence or absence of individual bands (Clegg et al., 2003), principal component analysis (PCA) was performed using SPSS 13.0 (SPSS Inc., USA). 2.6. Sequencing and phylogenetic analysis To further characterize the bacteria community present during biofilter operation and in the original inoculums, selected DGGE bands were excised from the gel with a sterile blade. The gel fragments were eluted, and DNA templates were prepared according to previously described method (Babbitt et al., 2009). These templates were reamplified using the same methods as described above and checked on original samples. Sequencing was carried out by Sangon Bioengineering Ltd (Beijing, China). Analysis of DNA sequences and homology searches were completed with the BLAST server of the National Centre for Biotechnology Information
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using the BLAST algorithm for the comparison of a nucleotide query sequence against a nucleotide sequence database (blastn). Phylogenetic tree was then generated by the neighbor-joining algorithm and Kimura-2 parameter model of base substitution within the MEGA4.1 package (Tamura et al., 2007), which was confirmed by 1000-fold bootstrapping.
3. Results and discussion 3.1. Ethylene removal tests Biofiltration of ethylene was carried out for more than consecutive three months at various concentrations of inlet ethylene ranging from 50 to 1000 ppm. In each phase, effect of inlet concentration on total performance of the biofilter was investigated. The results of ethylene removal by the biofilter were shown in Fig. 2A. Removal efficiencies in each phase gradually increased, reached stable, and rapidly decreased after a sudden increase in influent concentration. The system was started with flow rate of 174 mL min1 resulting in a gas retention time of 13 min with an inlet ethylene concentration of 50 ppm (loading rate 0.27 g m3 h1). After one day of operation in phase I, removal efficiency in biofilter was 49.8% and by day 5, it was more than 80.2%. The removal efficiency was up to 96% after 13 days. Steady-state conditions were observed after day 15 of the operation, with the removal efficiency of almost 100%. The results are consistent with the previous report that microorganisms exposed to new environment may require adaptation time before they start vigorous biodegradation (He et al., 2007). Inoculation of biofilter media with adapted microbial aggregates greatly reduces adaptation time of biofilter to as low as about 10 days (Arnold et al., 1997; Mathur and Majumder, 2008). On day 21, the start of phase II, loading rate was increased by nearly five times from 0.27 g m3 h1 to a range of 1.071.61 g m3 h1. Due to sudden change in loading rate to the biofilter, removal efficiency declined to 81.5%. The removal efficiency in the reactor reached to an average of more than 97% by day 25. The reason may be that ethylene is an extremely volatile and slowly adsorbed compound, sufficient time for microorganisms to adapt the increased ethylene might be required (Kim, 2006). During the 40-day phase III influent ethylene concentration was further increased and ranged from 600 to 700 ppm, with loading rate 3.213.75 g m3 h1. Same response, similar to phase II, was observed once again. There was initial high sudden decrease in removal efficiency from 100% to 80.1%, and then recovery up to100%. To achieve loading rate of 5.35 g m3 h1 nearer to the same as in phase IV, inlet ethylene concentration was increased up to 1000 ppm. In this phase, removal efficiency of ethylene <83% was achieved. This could be due to restriction of microbial activity or capability limitation of ethylene-degrading bacteria in the reactor at high concentration of ethylene. The biofilter performance was also evaluated in terms of ethylene EC for various loading rates (Fig. 2B). As a whole, ECs of ethylene increased with the increase in influent concentration. ECs of ethylene also increased with the increase of removal efficiency and then reached to a maximum level at a constant loading rate. These results are related to the dynamics of changing of EC with days (Fig. 2B). Significant variation of EC in various phases was observed due to change in influent concentration. When influent ethylene loadings were <5.35 g m3 h1, 100% removal could be achieved. Maximum EC of biofilter was 4.44 g m3 h1 at inlet ethylene load of 5.34 g m3 h1 in phase IV. In a comparable study, Kim reported the maximum EC of ethylene removal by a biofilter using Pseudomonas packed with activated carbon was 1.42 g m3 h1 at a loading rate of 1.42 g m3 h1 (Kim, 2006). Elsgaard (1998) employed a peat-soil biofilter inoculated with
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ethylene-degrading bacterial strain RD-4 to remove ethylene and obtained maximum EC of 0.86 g m3 h1 at loading rate 0.88 g m3 h1, resulting in 99.9% removal. Heyder et al. (1994) studied the removal of ethylene by a packed granular activated carbon biobed inoculated with Mycobacterium strain E3 and observed maximum EC of 4.67 g m3 h1 with constant wetting, which corresponded to a removal efficiency of 84.9%. These findings implied that the different filter media and microorganisms have shown different performance of ethylene removal. The appropriate filter media and microorganisms are important operation factors for the biofiltration process of ethylene removal (Kim, 2006). Our results suggested that natural zeolite biofilter appeared to be a promising tool for ethylene removal because it combined a high removal efficiency and a good EC. In order to understand the dynamics of ethylene removal in the biofilter, the ethylene concentration profiles in different phases were obtained as a function of the biofilter height. The ratio between the outlet (C) and inlet (Co) ethylene concentration is presented in Fig. 2C. We found that the removal was more efficient in the lower part of the biofilter than that in the upper part of the biofilter. Nearly 70%, 20% and 10% of the ethylene was removed in the three stages from low to high of the biofilter in day 17 with an inlet ethylene concentration of 200 ppm, respectively. With the increase of inlet ethylene concentration, the removal proportions of ethylene of the upper two stages gradually increased. However, the ethylene removal was mainly attributed to the bottom stage in all tested operating phases. This may be due to a higher concentration of microbial population in the lower section of the filter bed. Similar dynamics were reported in the benzene removal using activated carbon as a filter medium (Kim, 2006). 3.2. Carbon dioxide production by ethylene degradation In the biofiltration process, the organic pollutants are aerobically degraded to carbon dioxide and water used as the essential carbon source for the microbial growth. Hence, the carbon dioxide concentration profile in the gas phase at the inlet and the outlet of the biofilter provides useful information on the biofilter performance. A positive gradient of carbon dioxide concentration in the gas phase through the biofilter indicates that there is carbon dioxide production due to the biodegradation of the organic pollutants. Fig. 3A shows the inlet and outlet carbon dioxide concentration versus the ethylene inlet concentration. In all operation duration, the outlet carbon dioxide concentration is always higher than the inlet carbon dioxide concentration, indicating biodegradation of ethylene in the biofilter. The production of carbon dioxide as a function of EC for the various tested operating phases is presented in Fig. 3B. In this figure, the mean experimental data lie reasonably around the line y = 2.82x. This indicates that the ratio between production carbon dioxide and EC, i.e. the mass of carbon dioxide produced per mass of ethylene removed, is on average equal to 2.82 for all tested conditions with a R2 value of 0.96. Theoretically, this ratio should be 3.14 in the case of complete oxidation of ethylene to water and carbon dioxide according to the following stoichiometry:
C2 H4 þ 3O2 ! 2CO2 þ 2H2 O: In case of biodegradation of organic pollutants, a fraction of consumed organic carbon is used for the microbial growth. Ethylene degradation might have resulted in the growth of biofilm and a mineralization of ethylene in the biofilter (Elsgaard, 1998). This explains the observed deficit in carbon dioxide production in comparison with the case of complete chemical oxidation of ethylene, meanwhile, they may also partly explain the fluctuations of the experimental ratio. In addition, the small difference between the experimental ratio and the theoretical one of complete
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Fig. 2. (A) Removal efficiency of biofilter as a function of inlet ethylene concentration with time. (B) Elimination capacity (EC) of biofilter as a function of inlet load of contaminated gas stream. Square symbols represent experimental data of ethylene and the dotted line indicates 100% removal. The small figure shows the dynamics of changing of elimination capacity with days. (C) Ethylene concentration profiles according to biofilter height.
oxidation is evidence of the removal of ethylene exclusively by aerobic degradation, excluding other factors like leakage or incomplete oxidation of ethylene in explaining the decrease of ethylene concentration through the biofilter. Carbon dioxide generation profiles along the height of the biofilter were presented for days 17, 28, 59 and 105 (Fig. 3C). Carbon dioxide formulation was by consistency in ethylene disappearance. With a higher influent concentration, both loading and EC of ethylene were higher, leading to the production of even more carbon dioxide. Carbon dioxide generation profiles along the height of the biofilter were similar to that previously reported for alpha-pine degrading biofilter (Bagherpour et al., 2005). 3.3. Dynamics of the microbial population and community structure The natural zeolite samples withdrawn from different stages of the packing were collected during the assessment of different phase for microbial population dynamics. The results of population dynamics of the packing medium in the biofilter are presented in Fig. 4A. The initial cell numbers of inoculums just before transient loading were approximately 106 CFU/g of dry packing material in each stage. Irrespective of the operation conditions, the cell numbers of microorganisms ranged from 103 to 107 CFU/g of dry packing material for the three stages of the filter bed during the transient loading period, however, were statistically different
(p < 0.05), except for that for middle stage and top stage in the phase I. With different loading rates of ethylene, the change of bacteria count in the bottom stage was the most obvious among the three stages. Moreover, microbial population in the bottom stage was always significantly higher two orders of magnitude than those in the other stages. These behaviors are probably due to that the inlet ethylene load gradually decreased from bottom to top. Microbial population in each stage exhibited a similar trend in which there was a decrease in the phase I followed by an increase. We think this was attributed to bacterial adaptation and lower ethylene loading rate in the phase I. Our view is supported by the reports from other three-stage biofiltration process (Ding et al., 2008). PCR-DGGE was performed to compare the 16S rRNA gene fragment profiles of bacteria in samples collected from different operational phases and stages of the biofilter. Fig. 4B shows the DGGE profiles of the bacterial community in the natural zeolite-based biofilter during the biofiltration process. Obviously, shifts in the composition of the bacterial community of the biofilter were readily detected at different time points and stages. In each case, the band intensities of samples collected from the middle stage of the biofilter on days 15, 45, 75, and 105 (lane 15m, 45m, 75m and 105m) were intermediate to those found in the bottom and top stages. The band patterns of samples collected from the bottom stage of the biofilter on day 45 (lane 45b) were significantly different from
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Fig. 3. (A) Outlet and inlet carbon dioxide concentration vs. inlet ethylene concentration. (B) Quantity of carbon dioxide produced at the outlet of the biofilter vs. elimination capacity. (C) Carbon dioxide generation profiles along the height of biofilter.
those obtained on day 0 (lane 0) and day 105 (lane 105b). However, the band patterns of samples obtained from the bottom stage on day 75 (lane 75b) were similar to that on day 105 (lane 105b). In general, two high-intensity bands (a and h) were detected on day 15, but the intensity of band (a) rapidly decreased in the rest sampling time points. Similarly, two remarkably intense bands (b and c) were observed on day 45. However, the intensity of band (b) became weaker or even disappeared during the next days. Three new intense bands (d–f) appeared on day 75, and then were present with high-intensity on day 105. In addition, many of the bands present on day 0 were absent after day 15.These results show that the bacterial community composition in the biofilter was highly affected by the biofiltration of ethylene and shifted throughout the experimental period. In other biofiltration systems, stability and persistence in community structure over time have been observed, as well as rapid shifts away from the initial observed inoculum community structure (Babbitt et al., 2009; Sercu et al., 2007). DGGE gel profiles were further analyzed statistically using the Shannon index and PCA. Shannon index is useful as an effective approach to estimate the diversity of microbial communities, i.e., the higher Shannon index, the greater the diversity of the microbial community (Jun and Wenfeng, 2009). As shown in Fig. 4C, the Shannon index of each stage in the biofilter exhibited a similar trend in which there was a decrease followed by an increase with the time. This was attributed to slow microbial
growth and little biomass formation on the packing material during early operation and rapid growth of microbes after the adaptation. At the end of the experiment, the Shannon index of the biofilter appeared to be a slight increase from the bottom to the top stage, likely due to the decrease in loading of ethylene with bioreactor height. This observation is consistent with the previous finding that selective pressures of the changing concentration gradient of introduced pollutant over the biofilter length can result in that diversity in biofilter differed significantly as a function of height along the biofilter (Li and Moe, 2004). As shown in Fig. 4D, 13 samples from days 0, 15, 45, 75 and 105 were classified into four distinct clusters in the PCA plot. This confirms the results obtained from DGGE image, namely community composition shifted throughout the experimental period. The bacterial community composition of samples collected on days 75 and 105 moved towards PC3, suggesting that after increasing the ethylene inlet concentration, the bacterial community composition had dramatic shift. Furthermore, these samples formed a distinct cluster, which indicated that there was a relatively stable bacterial community in phases III and IV. 3.4. Phylogenetic analysis of ethylene-degrading bacteria Selected bands, corresponding to higher relative intensity, were excised, reamplified, purified, and sequenced to determine the
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Fig. 4. (A) Dynamics of the microbial community on TSA media from the bottom, middle, and top stage of the biofilter in different phases. Bars represent treatment means (± standard errors), and different letters above the bars indicate that values differed significantly at a P value of <0.05. (B) Images of DGGE-16S rRNA separated DNA fragments sampled from the biological inoculum and from the biofilter during operation. The lanes are labeled as 0, 15b, 15m, 15t, 45b, 45m, 45t, 75b, 75m, 75t, 105b, 105m, and 105t. 0, 45, 75, 105: samples on days 0, 15, 45, or 105; b, m, t: samples in bottom, middle or top stage of the biofilter. Arrows indicate bands that were subsequently excised. (C) Shannon index analysis of the DGGE patterns of samples from the biofilter (D) PCA analysis of the DGGE profiles of the biofilter. Sampling time: day 0 (plus), day 15 (circle), day 45 (square), day 75 (triangle) and day 105 (diamond). Bottom stage (black), middle stage (gray), and top stage (white). Ellipses indicate samples that were in one cluster.
phylogeny of selected ethylene-degrading bacteria in the biofilter based on natural zeolite. As shown in Fig. 5, eight discriminable bands (a–h) were individually identified as members of different eubacterial groups. Four bands (c–e, and g) were grouped with the class Actinobacteria, and their closest relative showed homology to Mycobacterium vaccae, Rhodococcus erythropolis, Nocardia fluminea, and Arthrobacter sp., respectively. Only the band (f), which was affiliated to Bacillus cereus, belonged to the class Bacilli. Two bands (a and h) were clustered within the class Gammaproteobacteria, they showed high similarity to Pseudomonas sp. or Pseudomonas putida. One band (b) was clustered within the class Betaproteobacteria, namely Xanthomonas sp. These results illustrate the diversity of the bacteria community present in the bioreactor under different operating conditions. Based on the presence of their DGGE bands, two species of Pseudomonas appeared in the biofilter, moreover, the band (h) was consistently present at different inlet concentrations. The result indicates that the Pseudomonas was dominant in the biofilter, which is in agreement with earlier reported biofiltration system
of ethylene packing activated carbon (Kim, 2006). Like the band (h), Arthrobacter sp. was consistently present at different inlet concentrations. Arthrobacter sp., as alkane-utilizer, has been found to be capable of oxidizing ethylene to epoxyethane (Hou et al., 1983). Xanthomonas sp. and M. vaccae were found exclusively at middle concentration of inlet ethylene (200–300 ppm). Xanthobacter sp. has been reported to play an important role in oxidizing ethylene, which can utilize ethylene as sole substrate (Ginkel et al., 1987; Hou et al., 1983). M. vaccae was also known to utilize ethylene, which was immobilized in a bioreactor based on compost, to be responsible for the removal of ethylene (Elsgaard, 1998, 2000). A third bacterial group that includes R. erythropolis and N. fluminea occurred at the relatively high concentration of influent ethylene (600–1000 ppm). They are able to oxidize ethylene, and show high oxidizing activity under conditions with ethylene and L-hexene (Kulikova and Bezborodov, 2001; van Ginkel et al., 1987). Taken together, the results reported here support the hypothesis that biofilter operating strategies such as inlet gas flow rate and loading can impose a selective pressure on the bac-
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Fig. 5. Phylogenetic tree of bacterial populations identified in the biofilter during operation periods, based on the 16S rRNA gene sequences.
terial community that is large enough to influence relative abundance of microbial species that predominate over time.
4. Conclusion Our experimental data demonstrate that the biofilter packing natural zeolite is capable of successfully purifying air containing ethylene. The removal efficiency of this system in different ethylene concentrations was evaluated and found to be satisfactory. The feasibility of this biofilter system needs to be further supported by its design, aiming to prevent pressure drop. The results of DGGE provide valuable information on the roles or functions of bacterial species in the bacterial community during the biofiltration processes. The strains identified in this study are potential candidate strains for the ethylene removal in biofiltration. Acknowledgements This work was supported by Grants from Ministry of Science and Technology of China (2009DFR30650) and the Innovation Foundation of BUAA for PhD Graduates. We also appreciate the Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education for their helps.
Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.biortech.2010.07.119.
References Arnold, M., Reittu, A., von Wright, A., Martikainen, P.J., Suihko, M.L., 1997. Bacterial degradation of styrene in waste gases using a peat filter. Appl. Microbiol. Biotechnol. 48, 738–744. Babbitt, C.W., Pacheco, A., Lindner, A.S., 2009. Methanol removal efficiency and bacterial diversity of an activated carbon biofilter. Bioresour. Technol. 100, 6207–6216. Bagherpour, M.B., Nikazar, M., Welander, U., Bonakdarpour, B., Sanati, M., 2005. Effects of irrigation and water content of packings on alpha-pinene vapours biofiltration performance. Biochem. Eng. J. 24, 185–193. Calvo-Bado, L.A., Pettitt, T.R., Parsons, N., Petch, G.M., Morgan, J.A.W., Whipps, J.M., 2003. Spatial and temporal analysis of the microbial community in slow sand filters used for treating horticultural irrigation water. Appl. Environ. Microbiol. 69, 2116–2125. Clegg, C.D., Lovell, R.D.L., Hobbs, P.J., 2003. The impact of grassland management regime on the community structure of selected bacterial groups in soils. FEMS Microbiol. Ecol. 43, 263–270. Daigger, G.T., 1979. The Interaction of Physiological Adaptation and Transient Response for Pseudomonas putida and its Implications for Dynamic Modeling of Microbial Growth. Purdue University, United States. Ding, Y., Wu, W., Han, Z., Chen, Y., 2008. Correlation of reactor performance and bacterial community composition during the removal of trimethylamine in three-stage biofilters. Biochem. Eng. J. 38, 248–258. Elsgaard, L., 1998. Ethylene removal by a biofilter with immobilized bacteria. Appl. Environ. Microbiol. 64, 4168–4173. Elsgaard, L., 2000. Ethylene removal at low temperatures under biofilter and batch conditions. Appl. Environ. Microbiol. 66, 3878–3882. Garbeva, P., Elsas, J.D., Veen, J.A., 2007. Rhizosphere microbial community and its response to plant species and soil history. Plant Soil 302, 19–32. Ginkel, C.G., Habets-Crützen, A.Q., Last, A.R., Bont, J.A., 1987. A description of microbial growth on gaseous alkenes in a chemostat culture. Biotechnol. Bioeng. 30, 799–804. He, S.B., Xue, G., Kong, H.N., 2007. The performance of BAF using natural zeolite as filter media under conditions of low temperature and ammonium shock load. J. Hazard. Mater. 143, 291–295. Heyder, B.D., Overmeire, A., Langenhove, H.V., Verstraete, W., 1994. Ethene removal from a synthetic waste gas using a dry biobed. Biotechnol. Bioeng. 44, 642–648.
584
Y. Fu et al. / Bioresource Technology 102 (2011) 576–584
Hou, C.T., Patel, R., Laskin, A.I., Barnabe, N., Barist, I., 1983. Epoxidation of shortchain alkenes by resting-cell suspensions of propane-grown bacteria. Appl. Environ. Microbiol. 46, 171–177. Hoyer, L., 1995. Investigations of the ethylene buildup during transport of pot plants in controlled temperature trucks. Postharvest Biol. Technol. 5, 101–108. Jun, Y., Wenfeng, X., 2009. Ammonia biofiltration and community analysis of ammonia-oxidizing bacteria in biofilters. Bioresour. Technol. 100, 3869– 3876. Kim, J.G., 2006. Assessment of ethylene removal with Pseudomonas strains. J. Hazard. Mater. 131, 131–136. Konstantinov, S.R., Zhu, W.Y., Williams, B.A., Tamminga, S., Vos, W.M., Akkermans, A.D., 2003. Effect of fermentable carbohydrates on piglet faecal bacterial communities as revealed by denaturing gradient gel electrophoresis analysis of 16S ribosomal DNA. FEMS Microbiol. Ecol. 43, 225–235. Kulikova, A.K., Bezborodov, A.M., 2001. Assimilation of propane and characterization of propane monooxygenase from Rhodococcus erythropolis 3/ 89. Appl. Biochem. Microbiol. 37, 164–167. Li, C., Moe, W., 2004. Assessment of microbial populations in methyl ethyl ketone degrading biofilters by denaturing gradient gel electrophoresis. Appl. Microbiol. Biotechnol. 64, 568–575. Manning, W.J., Feder, W.A., 1980. Biomonitoring Air Pollutants with Plants. Applied Science Publishers, London. Mathur, A.K., Majumder, C.B., 2008. Biofiltration of benzene emissions: biofilter response to variations in the pollutants inlet concentration and gas flow rate. J Sci Ind Res. (India) 67, 243–248. Möhlenhoff, P., Müller, L., Gorbushina, A.A., Petersen, K., 2001. Molecular approach to the characterisation of fungal communities: methods for DNA extraction, PCR
amplification and DGGE analysis of painted art objects. FEMS Microbiol. Lett. 195, 169–173. Sawada, S., Totsuka, T., 1986. Natural and anthropogenic sources and fate of atmospheric ethylene. Atmos. Environ. 20, 821–832. Schnelle, K., Brown, C., 2002. Air Pollution Control Technology Handbook. CRC Press, Boca Raton. Sercu, B., Boon, N., Beken, S.V., Verstraete, W., Langenhove, H.V., 2007. Performance and microbial analysis of defined and non-defined inocula for the removal of dimethyl sulfide in a biotrickling filter. Biotechnol. Bioeng. 96, 661–672. Stoeckinger, A., 2004. Zeolite Packed Biologically Active Filter (Biofilter) to Reduce Odorous Emissions from a Confined Swine Building. Oregon State University, United States. Tambwekar, J.A., 2002. Biofiltration of Trace Concentrations of Ethylene in Air. Rutgers, The State University of New Jersey, United States. Tamura, K., Dudley, J., Nei, M., Kumar, S., 2007. MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol. Biol. Evol. 24, 1596–1599. Temple, P.J., Sun, E.-J., Krause, G.H.M., 1998. Peroxyacyl Nitrates (PANs) and Other Minor Pollutants. Air & Waste Management Association, Pittsburg, Pennsylvania. van Ginkel, C.G., Welten, H.G.J., de Bont, J.A.M., 1987. Growth and stability of ethene-utilizing bacteria on compost at very low substrate concentrations. FEMS Microbiol. Lett. 45, 65–69. Warmink, J.A., van Elsas, J.D., 2008. Selection of bacterial populations in the mycosphere of Laccaria proxima: is type III secretion involved? ISME J. 2, 887– 900. Yin, J., Xu, W.F., 2009. Ammonia biofiltration and community analysis of ammoniaoxidizing bacteria in biofilters. Bioresour. Technol. 100, 3869–3876.
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Ethylene removal efficiency and bacterial community diversity of a natural zeolite biofilter Yuming Fu, Lingzhi Shao, Ling Tong, Hong Liu * Laboratory of Environmental Biology and Life Support Technology, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
a r t i c l e
i n f o
Article history: Received 30 May 2010 Received in revised form 29 July 2010 Accepted 29 July 2010 Available online 4 August 2010 Keywords: Ethylene Natural zeolite PCR-DGGE Biofilter Bacterial diversity
a b s t r a c t To establish an economical and environmentally friendly technology for ethylene removal from horticultural facilities and industrial point sources, a bench-scale natural zeolite biofiltration system was developed in this study. The system was evaluated for its performance in removing ethylene from an artificially contaminated air stream and characterized for its bacterial diversity under varied ethylene concentrations, and in different spatial stages of the filter. The biofilter enabled to approximately 100% remove ethylene at loading rates of 0.26–3.76 g m3 h1 when operated with inoculum containing enriched ethylene-degrading bacteria. The bacterial diversity and abundance varied with the height of the biofilter. Moreover, the occurrence and predominance of specific bacterial species varied with the concentrations of ethylene introduced into the biofilter, as observed by PCR-DGGE methods. Phylogenetic analysis indicated that the biofilter system supported a diverse community of ethylene-degrading bacteria, with high similarity to species in the classes Betaproteobacteria, Gammaproteobacteria, Bacilli, and Actinobacteria. Ó 2010 Elsevier Ltd. All rights reserved.
1. Introduction Ethylene (C2H4), one of the hazardous volatile organic compounds (VOCs), causes serious air pollution problems, for example, it produces carbon monoxide and ozone, and prevents the removal of chlorine in stratosphere. As an air pollutant, it was shown to originate from a variety of natural and anthropogenic sources such as the biosynthesis of plants and microorganisms in soils (Sawada and Totsuka, 1986), waste gas and leaks in petrochemical complexes, automobile exhaust, and burning of organic materials (Temple et al., 1998). Unlike other air pollutants, ethylene is a plant hormone that controls plant physiological processes such as growth, flowering and senescence. Accumulation of atmospheric ethylene is able to reduce vegetative growth, flower and fruit development and accelerate normal ageing of plant tissues (Manning and Feder, 1980). Growing plants in enclosed or semienclosed environments, such as greenhouse, easily result in an elevated concentration of ethylene. Also, significant accumulation of ethylene may occur in horticultural storage facilities due to endogenous production by the fruit and vegetable (Hoyer, 1995). Thus, it is essential to take removal of such pollutant into consideration when dealing with the gaseous waste products and maintaining plant normal growth and postharvest quality.
* Corresponding author. Tel./fax: +86 10 82339837. E-mail address: [email protected] (H. Liu). 0960-8524/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.biortech.2010.07.119
Despite the effectiveness of physical/chemical methods in destroying ethylene, the disadvantages of requiring replenishing the ethylene-destroying agent and high costs for operation have motivated a desire for more easily and economically beneficial technologies (Kim, 2006; Schnelle and Brown, 2002). One potential alternative is the biological catalysis using biofilter that has been known as a reliable and cost-effective biofiltration technology. In the design and operation of the biofiltration process, the selection of a suitable media is critical to enable the required removal efficiency to be achieved (He et al., 2007). Various types of biofilters removing ethylene, based on different filter media such as peat-soil and activated carbon have been studied (Elsgaard, 1998, 2000). Natural zeolite is also a well-known, traditional packing material for biofilters. It not only provides several advantages similar to other typical packing materials such as high porosity for easy air flow, extensive surface area for biofilm attachment, but also has high moisture holding capacity, diverse nutrient content, very slow degradation rate as well as more economic advantages (Stoeckinger, 2004). However, there is little information available in literature about the removal ethylene by the biofilter packed with natural zeolite. Moreover, since there is also a lack of information on microbial communities in biofilter, there is a need for a database of microbial communities that include the ethylene-degrading bacteria in biofilter materials. In this study, ethylene removal by a natural zeolite as a filter material for a bench-scale biofilter was evaluated at different ethylene loading rates. Analysis of the abundance, diversity, and
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spatial distribution of bacteria in the packing media was conducted using culture-dependent and denaturing gradient gel electrophoresis (DGGE) methods. The dominant ethylene-degrading bacteria in the biofilter were also identified by sequencing. The results show promise for the development of zeolite biofilter systems as an effective option for ethylene control for the plant cultivating chambers, horticultural storage facilities, and petrochemical industries. 2. Methods 2.1. Microorganisms and natural zeolite Potential biofilter inoculum was obtained from activated sludge in the Gaobeidian Wastewater Treatment Plant in the City of Beijing, China. Ten milliliters of the activated sludge was homogenized with 90 mL sterile phosphate-buffered saline (PBS; 137 mM NaCl, 2.7 mM KCl, 4.3 mM Na2HPO4, 1.4 mM KH2PO4, [pH 7.3]) on a rotary shaker at 25 °C and 250 rpm for 1 h. One hundred milliliters of the homogenized mixture was incubated in a 3 L vessels containing 1.5 L of mineral salts medium without added carbon sources, and ethylene was added to a headspace concentration of ca. 1% as recommended by the prior report (Tambwekar, 2002). The culture was incubated with shaking (180 rpm) at 25 °C, and the ethylene was replenished to ca. 1% when its concentration dropped below 0.5% (assayed by gas chromatographic analysis) under the aerobic condition for 20 days. The mineral salts medium had the following components according to the previous report (Daigger, 1979),on a mg L1 basis: K2HPO4, 4350; KH2P04, 3400; NH4C1, 1010; MgSO47H2O, 15; HCl, 3.93; CaCl22H20, 2; FeCl36H20, 1.5; MnS04H20, 0.45; CoCl26H20, 0.15; ZnCl2, 0.15; CuCl22H20, 0.05; Na2Mo042H20, 0.05; H3BO3, 0.015. All chemicals used were obtained from Sigma–Aldrich (Beijing, China) and were of analytical grade or higher. The natural zeolite used as a filter media in this study was a commercial sample, supplied from Kaibiyuan Company, Beijng, China. Its characteristics were shown in Table 1. After washed with tap water and dried at a room temperature, the natural zeolite was transferred into the biofilter. To investigate the ability of this material to adsorb ethylene without bacteria, batch studies were performed on 10 g of the packing samples. The packing samples were first sterilized by autoclaving, and their moisture contents were adjusted to 50%. The samples were added to a 50 mL vial inletting 100, 500, or 1000 ppm of ethylene. The weight change of the natural zeolite was measured at 24, 48, 72 h and on the 7th day using an Ohaus dv/80–210 balance (Ohaus, USA), respectively. No change among 48, 72 h, and day 7 was observed, suggesting the equilibrium of the system. Equilibrium concentrations in the gas phase (Ce) and absorbed ethylene concentrations in the packing materials (qe) were used to estimate the Freundlich model coefficients (KF and N) with a best fit method, according to the Freundlich model equation (qe ¼ K F C Ne ). The KF and N estimated for zeolite were shown in Table S1. The results indicated the low ethylene adsorptive capacity of the zeolite. The Freundlich model equation yielded the abiotic ethylene adsorption capacities for zeolite of 4.68 mg/kg, at the equilibrium gas-phase concentration of 50 ppm. Using the abiotic adsorption capacities and a simple mass balance, the adsorptive capacity of zeolite was Table 1 Characteristics of the natural zeolite. Size range (mm) Density (kg m3) Bulk density (kg m3) Specific surface area (m2 g1) Porosity (%) Silicon/aluminum ratio
3–5 2315 1014 6.84 43.83 4.1–5.7
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predicted to be exhausted during 18 h and that ethylene removal after that time point would likely be attributed to the bacterial activity in the biofilter. 2.2. Biofilter and operation To assess the feasibility of the proposed biofiltration system, a lab-scale biofilter was built, consisting of a transparent rigid plexiglass column with 8 cm diameter, 70 cm length and 45 cm filter bed height (Fig. 1). The filter bed was composed of three identical stages, each equipped with gas and medium sampling ports. The biofilter was inoculated with the culture enriched in the mineral salts medium described above and the initial volatile suspended solid concentration of inoculated solution was 50 mg L 1. The nutrient solution (mineral salts medium) was introduced at the top of the biofilter through a water distributor using a Cole-Parmer metering pump (USA) at a rate of 800 mL day1. The solution was provided for the maintenance of 43–51% moisture content of zeolite in the biofilter. A mixture of atmospheric air and ethylene in nitrogen (N2) (Haipu, Beijing, China) was supplied to the biofilter via two mass flow controllers. Before reaching the inlet, the gas was humidified by being bubbled through a flask containing distilled water. The ethylene concentration of the gas flow was kept constant by adjusting the flow rate of the air stream and ethylene. Biofilter operation was characterized in room temperature by four consecutive sets of operating conditions, described here and summarized in Table 2. 2.3. Sampling and gas analysis Gaseous samples were periodically collected at the inlet and outlet of each stage of the bioreactors by 1.6 L Tedlar gas sampling bags (Cole-Parmer, USA). Sampling was conducted over a 7 min period. Before every sampling, the bags were filled with air and cleaned out by an air pump for three times. Packing samples were collected from each stage of the biofilter on days 0 (original inoculum), 15, 45, 75, and 105 for subsequent analysis. A sterile metal corer was used to take samples of ca. 10 g (wet weight) of zeolite from the biofilter via sampling ports, when biofilter was taken down. Each packing sample was divided into two parts for determination of bacterial amounts and DNA extraction. The parts for determination of bacterial amounts and DNA extraction were stored at 4 and 20 °C, respectively. Ethylene and carbon dioxide (CO2) were analyzed with a gas chromatography (GC) 7890 (Tianmei, Shanghai, China) using a glass column packed with GDX-401. The ethylene detection limit was 105 ppm. The GC was coupled to a flame ionization detector (FID) and N2 served as the carrier gas at a flow rate of 40 mL min1. Temperatures for column, injector, and detector were 60, 130, and 380 °C, respectively. The samples from the gas sampling bags were directly injected into the injector port of GC using a 1 mL gas syringe (Agilent, USA) with a push-button valve. Twice sample injections and a standard curve (R2 = 0.99) were used for all data analyses. In order to display the results of this study, three quantitative parameters including the inlet loading, the removal efficiency and the elimination capacity (EC) have been used and were presented in Table 3. 2.4. Viable bacterial plate counts and DNA extraction Routinely, 5 g (wet weight) of packing sample for determination of bacterial amounts was placed in 50 mL of sterile water and vortexed for 10 s every 2–3 min for 15 min. A tenfold dilution series of these samples was made by using sterile water. The dilutions were plated in triplicate on tryptic soy agar (TSA; Oxoid Ltd., United Kingdom). All plates were incubated at 20 °C for 7 days, and plates
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Fig. 1. Schematic of the biofilter system. (1) cylinder, (2) air blower, (3) gas flow meter, (4) mixing tank, (5) humidifier, (6) gas sampling port, (7)inlet gas port, (8) drainage, (9) filtering material sampling ports, (10) outlet gas port, (11) metering pump, and (12) water & nutrients.
Table 2 Summary of biofilter operating conditions. Phase
Days
Ethylene concentration (ppm)
Gas retention time (min)
Ethylene loading rate (g m3 h1)
I II III IV
1–20 21–50 51–90 91–109
50 200–300 600–700 1000
13 13 13 13
0.27 1.07–1.61 3.21–3.75 5.35
Table 3 Quantitative parameters. Definitions Inlet loading (IL) (g m3 h1)
in IL ¼ Q C V
Removal efficiency (RE) %
out 100% RE ¼ C in CC in
Elimination capacity (EC) (g m3 h1)
EC ¼ ðC in CVout ÞQ ¼ IL RE 3
where: Cin: the inlet ethylene concentration in g m Cout: outlet ethylene concentration in g m3. Q: the air flow rate in m3 h1. V: the biofilter bed volume in m3.
.
with between 30 and 200 colonies were counted (Calvo-Bado et al., 2003). For DNA extraction assay, packing samples of 5 g were mixed with 15 mL of extraction buffer (100 mM Tris–HCl [pH 8.0], 100 mM sodium EDTA [pH 8.0], 100 mM sodium phosphate [pH 8.0], 1.5 M NaCl, 1% CTAB) in 50 mL centrifuge tubes by horizontal shaking at 225 rpm for 30 min at 37 °C (Yin and Xu, 2009). Total DNA was extracted directly from the samples mixed buffer using a FastPrep DNA isolation kit according to the manufacturer’s instruction (QBIOGENE, USA). DNA extracts were stored at 70 °C before use. 2.5. PCR amplification and DGGE analysis Bacterial primers F968 with attached GC clamp (F968-GC) and R1378 were used for amplification of 16S rRNA of the total
bacterial community (Warmink and van Elsas, 2008). The PCR reactions were performed in 50 ll solution containing ca. 100 ng of the template DNA, 0.2 lM of each primer, 200 lM of each dNTP, 3.75 mM MgCl2, 6 PCR buffer and 5 U/ll Taq DNA polymerase (TakaRa, Japan). The thermal cycling was as follows: denaturation at 94 °C for 5 min, two cycles of: 1 min at 94 °C, 1 min at 60 °C, and 2 min 72 °C, followed by 10 of the same cycles with every cycle at 0.5 °C lower annealing temperature (until 55 °C), 20 cycles of 94 °C (1 min), 55 °C (1 min) and 72 °C (2 min), followed by final extension at 72 °C (10 min) (Garbeva et al., 2007). PCR products of high quality were purified and analyzed by denaturing gradient gel electrophoresis (DGGE). DGGE analysis was performed in the Bio-Rad D-GENE System (Bio-Rad, USA) using 35–70% gradients of denaturants. The separated amplicon bands in the gel were visualized on a UV-illuminator after staining with GelRed (Biotium, USA). To evaluate the bacterial community in the bioreactor of different stages, the positions and signal intensities of detected bands in the gel track were determined with a gel documentation system, Gel Doc 2000, Quantity-one 4.5.2 (Bio-Rad, USA). As a parameter for the structural diversity of the microbial community, the Shannon index of general diversity, H’ (Möhlenhoff et al., 2001), was calculated according to methods of Konstantinov et al. (2003). Based on the presence or absence of individual bands (Clegg et al., 2003), principal component analysis (PCA) was performed using SPSS 13.0 (SPSS Inc., USA). 2.6. Sequencing and phylogenetic analysis To further characterize the bacteria community present during biofilter operation and in the original inoculums, selected DGGE bands were excised from the gel with a sterile blade. The gel fragments were eluted, and DNA templates were prepared according to previously described method (Babbitt et al., 2009). These templates were reamplified using the same methods as described above and checked on original samples. Sequencing was carried out by Sangon Bioengineering Ltd (Beijing, China). Analysis of DNA sequences and homology searches were completed with the BLAST server of the National Centre for Biotechnology Information
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using the BLAST algorithm for the comparison of a nucleotide query sequence against a nucleotide sequence database (blastn). Phylogenetic tree was then generated by the neighbor-joining algorithm and Kimura-2 parameter model of base substitution within the MEGA4.1 package (Tamura et al., 2007), which was confirmed by 1000-fold bootstrapping.
3. Results and discussion 3.1. Ethylene removal tests Biofiltration of ethylene was carried out for more than consecutive three months at various concentrations of inlet ethylene ranging from 50 to 1000 ppm. In each phase, effect of inlet concentration on total performance of the biofilter was investigated. The results of ethylene removal by the biofilter were shown in Fig. 2A. Removal efficiencies in each phase gradually increased, reached stable, and rapidly decreased after a sudden increase in influent concentration. The system was started with flow rate of 174 mL min1 resulting in a gas retention time of 13 min with an inlet ethylene concentration of 50 ppm (loading rate 0.27 g m3 h1). After one day of operation in phase I, removal efficiency in biofilter was 49.8% and by day 5, it was more than 80.2%. The removal efficiency was up to 96% after 13 days. Steady-state conditions were observed after day 15 of the operation, with the removal efficiency of almost 100%. The results are consistent with the previous report that microorganisms exposed to new environment may require adaptation time before they start vigorous biodegradation (He et al., 2007). Inoculation of biofilter media with adapted microbial aggregates greatly reduces adaptation time of biofilter to as low as about 10 days (Arnold et al., 1997; Mathur and Majumder, 2008). On day 21, the start of phase II, loading rate was increased by nearly five times from 0.27 g m3 h1 to a range of 1.071.61 g m3 h1. Due to sudden change in loading rate to the biofilter, removal efficiency declined to 81.5%. The removal efficiency in the reactor reached to an average of more than 97% by day 25. The reason may be that ethylene is an extremely volatile and slowly adsorbed compound, sufficient time for microorganisms to adapt the increased ethylene might be required (Kim, 2006). During the 40-day phase III influent ethylene concentration was further increased and ranged from 600 to 700 ppm, with loading rate 3.213.75 g m3 h1. Same response, similar to phase II, was observed once again. There was initial high sudden decrease in removal efficiency from 100% to 80.1%, and then recovery up to100%. To achieve loading rate of 5.35 g m3 h1 nearer to the same as in phase IV, inlet ethylene concentration was increased up to 1000 ppm. In this phase, removal efficiency of ethylene <83% was achieved. This could be due to restriction of microbial activity or capability limitation of ethylene-degrading bacteria in the reactor at high concentration of ethylene. The biofilter performance was also evaluated in terms of ethylene EC for various loading rates (Fig. 2B). As a whole, ECs of ethylene increased with the increase in influent concentration. ECs of ethylene also increased with the increase of removal efficiency and then reached to a maximum level at a constant loading rate. These results are related to the dynamics of changing of EC with days (Fig. 2B). Significant variation of EC in various phases was observed due to change in influent concentration. When influent ethylene loadings were <5.35 g m3 h1, 100% removal could be achieved. Maximum EC of biofilter was 4.44 g m3 h1 at inlet ethylene load of 5.34 g m3 h1 in phase IV. In a comparable study, Kim reported the maximum EC of ethylene removal by a biofilter using Pseudomonas packed with activated carbon was 1.42 g m3 h1 at a loading rate of 1.42 g m3 h1 (Kim, 2006). Elsgaard (1998) employed a peat-soil biofilter inoculated with
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ethylene-degrading bacterial strain RD-4 to remove ethylene and obtained maximum EC of 0.86 g m3 h1 at loading rate 0.88 g m3 h1, resulting in 99.9% removal. Heyder et al. (1994) studied the removal of ethylene by a packed granular activated carbon biobed inoculated with Mycobacterium strain E3 and observed maximum EC of 4.67 g m3 h1 with constant wetting, which corresponded to a removal efficiency of 84.9%. These findings implied that the different filter media and microorganisms have shown different performance of ethylene removal. The appropriate filter media and microorganisms are important operation factors for the biofiltration process of ethylene removal (Kim, 2006). Our results suggested that natural zeolite biofilter appeared to be a promising tool for ethylene removal because it combined a high removal efficiency and a good EC. In order to understand the dynamics of ethylene removal in the biofilter, the ethylene concentration profiles in different phases were obtained as a function of the biofilter height. The ratio between the outlet (C) and inlet (Co) ethylene concentration is presented in Fig. 2C. We found that the removal was more efficient in the lower part of the biofilter than that in the upper part of the biofilter. Nearly 70%, 20% and 10% of the ethylene was removed in the three stages from low to high of the biofilter in day 17 with an inlet ethylene concentration of 200 ppm, respectively. With the increase of inlet ethylene concentration, the removal proportions of ethylene of the upper two stages gradually increased. However, the ethylene removal was mainly attributed to the bottom stage in all tested operating phases. This may be due to a higher concentration of microbial population in the lower section of the filter bed. Similar dynamics were reported in the benzene removal using activated carbon as a filter medium (Kim, 2006). 3.2. Carbon dioxide production by ethylene degradation In the biofiltration process, the organic pollutants are aerobically degraded to carbon dioxide and water used as the essential carbon source for the microbial growth. Hence, the carbon dioxide concentration profile in the gas phase at the inlet and the outlet of the biofilter provides useful information on the biofilter performance. A positive gradient of carbon dioxide concentration in the gas phase through the biofilter indicates that there is carbon dioxide production due to the biodegradation of the organic pollutants. Fig. 3A shows the inlet and outlet carbon dioxide concentration versus the ethylene inlet concentration. In all operation duration, the outlet carbon dioxide concentration is always higher than the inlet carbon dioxide concentration, indicating biodegradation of ethylene in the biofilter. The production of carbon dioxide as a function of EC for the various tested operating phases is presented in Fig. 3B. In this figure, the mean experimental data lie reasonably around the line y = 2.82x. This indicates that the ratio between production carbon dioxide and EC, i.e. the mass of carbon dioxide produced per mass of ethylene removed, is on average equal to 2.82 for all tested conditions with a R2 value of 0.96. Theoretically, this ratio should be 3.14 in the case of complete oxidation of ethylene to water and carbon dioxide according to the following stoichiometry:
C2 H4 þ 3O2 ! 2CO2 þ 2H2 O: In case of biodegradation of organic pollutants, a fraction of consumed organic carbon is used for the microbial growth. Ethylene degradation might have resulted in the growth of biofilm and a mineralization of ethylene in the biofilter (Elsgaard, 1998). This explains the observed deficit in carbon dioxide production in comparison with the case of complete chemical oxidation of ethylene, meanwhile, they may also partly explain the fluctuations of the experimental ratio. In addition, the small difference between the experimental ratio and the theoretical one of complete
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Fig. 2. (A) Removal efficiency of biofilter as a function of inlet ethylene concentration with time. (B) Elimination capacity (EC) of biofilter as a function of inlet load of contaminated gas stream. Square symbols represent experimental data of ethylene and the dotted line indicates 100% removal. The small figure shows the dynamics of changing of elimination capacity with days. (C) Ethylene concentration profiles according to biofilter height.
oxidation is evidence of the removal of ethylene exclusively by aerobic degradation, excluding other factors like leakage or incomplete oxidation of ethylene in explaining the decrease of ethylene concentration through the biofilter. Carbon dioxide generation profiles along the height of the biofilter were presented for days 17, 28, 59 and 105 (Fig. 3C). Carbon dioxide formulation was by consistency in ethylene disappearance. With a higher influent concentration, both loading and EC of ethylene were higher, leading to the production of even more carbon dioxide. Carbon dioxide generation profiles along the height of the biofilter were similar to that previously reported for alpha-pine degrading biofilter (Bagherpour et al., 2005). 3.3. Dynamics of the microbial population and community structure The natural zeolite samples withdrawn from different stages of the packing were collected during the assessment of different phase for microbial population dynamics. The results of population dynamics of the packing medium in the biofilter are presented in Fig. 4A. The initial cell numbers of inoculums just before transient loading were approximately 106 CFU/g of dry packing material in each stage. Irrespective of the operation conditions, the cell numbers of microorganisms ranged from 103 to 107 CFU/g of dry packing material for the three stages of the filter bed during the transient loading period, however, were statistically different
(p < 0.05), except for that for middle stage and top stage in the phase I. With different loading rates of ethylene, the change of bacteria count in the bottom stage was the most obvious among the three stages. Moreover, microbial population in the bottom stage was always significantly higher two orders of magnitude than those in the other stages. These behaviors are probably due to that the inlet ethylene load gradually decreased from bottom to top. Microbial population in each stage exhibited a similar trend in which there was a decrease in the phase I followed by an increase. We think this was attributed to bacterial adaptation and lower ethylene loading rate in the phase I. Our view is supported by the reports from other three-stage biofiltration process (Ding et al., 2008). PCR-DGGE was performed to compare the 16S rRNA gene fragment profiles of bacteria in samples collected from different operational phases and stages of the biofilter. Fig. 4B shows the DGGE profiles of the bacterial community in the natural zeolite-based biofilter during the biofiltration process. Obviously, shifts in the composition of the bacterial community of the biofilter were readily detected at different time points and stages. In each case, the band intensities of samples collected from the middle stage of the biofilter on days 15, 45, 75, and 105 (lane 15m, 45m, 75m and 105m) were intermediate to those found in the bottom and top stages. The band patterns of samples collected from the bottom stage of the biofilter on day 45 (lane 45b) were significantly different from
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Fig. 3. (A) Outlet and inlet carbon dioxide concentration vs. inlet ethylene concentration. (B) Quantity of carbon dioxide produced at the outlet of the biofilter vs. elimination capacity. (C) Carbon dioxide generation profiles along the height of biofilter.
those obtained on day 0 (lane 0) and day 105 (lane 105b). However, the band patterns of samples obtained from the bottom stage on day 75 (lane 75b) were similar to that on day 105 (lane 105b). In general, two high-intensity bands (a and h) were detected on day 15, but the intensity of band (a) rapidly decreased in the rest sampling time points. Similarly, two remarkably intense bands (b and c) were observed on day 45. However, the intensity of band (b) became weaker or even disappeared during the next days. Three new intense bands (d–f) appeared on day 75, and then were present with high-intensity on day 105. In addition, many of the bands present on day 0 were absent after day 15.These results show that the bacterial community composition in the biofilter was highly affected by the biofiltration of ethylene and shifted throughout the experimental period. In other biofiltration systems, stability and persistence in community structure over time have been observed, as well as rapid shifts away from the initial observed inoculum community structure (Babbitt et al., 2009; Sercu et al., 2007). DGGE gel profiles were further analyzed statistically using the Shannon index and PCA. Shannon index is useful as an effective approach to estimate the diversity of microbial communities, i.e., the higher Shannon index, the greater the diversity of the microbial community (Jun and Wenfeng, 2009). As shown in Fig. 4C, the Shannon index of each stage in the biofilter exhibited a similar trend in which there was a decrease followed by an increase with the time. This was attributed to slow microbial
growth and little biomass formation on the packing material during early operation and rapid growth of microbes after the adaptation. At the end of the experiment, the Shannon index of the biofilter appeared to be a slight increase from the bottom to the top stage, likely due to the decrease in loading of ethylene with bioreactor height. This observation is consistent with the previous finding that selective pressures of the changing concentration gradient of introduced pollutant over the biofilter length can result in that diversity in biofilter differed significantly as a function of height along the biofilter (Li and Moe, 2004). As shown in Fig. 4D, 13 samples from days 0, 15, 45, 75 and 105 were classified into four distinct clusters in the PCA plot. This confirms the results obtained from DGGE image, namely community composition shifted throughout the experimental period. The bacterial community composition of samples collected on days 75 and 105 moved towards PC3, suggesting that after increasing the ethylene inlet concentration, the bacterial community composition had dramatic shift. Furthermore, these samples formed a distinct cluster, which indicated that there was a relatively stable bacterial community in phases III and IV. 3.4. Phylogenetic analysis of ethylene-degrading bacteria Selected bands, corresponding to higher relative intensity, were excised, reamplified, purified, and sequenced to determine the
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Fig. 4. (A) Dynamics of the microbial community on TSA media from the bottom, middle, and top stage of the biofilter in different phases. Bars represent treatment means (± standard errors), and different letters above the bars indicate that values differed significantly at a P value of <0.05. (B) Images of DGGE-16S rRNA separated DNA fragments sampled from the biological inoculum and from the biofilter during operation. The lanes are labeled as 0, 15b, 15m, 15t, 45b, 45m, 45t, 75b, 75m, 75t, 105b, 105m, and 105t. 0, 45, 75, 105: samples on days 0, 15, 45, or 105; b, m, t: samples in bottom, middle or top stage of the biofilter. Arrows indicate bands that were subsequently excised. (C) Shannon index analysis of the DGGE patterns of samples from the biofilter (D) PCA analysis of the DGGE profiles of the biofilter. Sampling time: day 0 (plus), day 15 (circle), day 45 (square), day 75 (triangle) and day 105 (diamond). Bottom stage (black), middle stage (gray), and top stage (white). Ellipses indicate samples that were in one cluster.
phylogeny of selected ethylene-degrading bacteria in the biofilter based on natural zeolite. As shown in Fig. 5, eight discriminable bands (a–h) were individually identified as members of different eubacterial groups. Four bands (c–e, and g) were grouped with the class Actinobacteria, and their closest relative showed homology to Mycobacterium vaccae, Rhodococcus erythropolis, Nocardia fluminea, and Arthrobacter sp., respectively. Only the band (f), which was affiliated to Bacillus cereus, belonged to the class Bacilli. Two bands (a and h) were clustered within the class Gammaproteobacteria, they showed high similarity to Pseudomonas sp. or Pseudomonas putida. One band (b) was clustered within the class Betaproteobacteria, namely Xanthomonas sp. These results illustrate the diversity of the bacteria community present in the bioreactor under different operating conditions. Based on the presence of their DGGE bands, two species of Pseudomonas appeared in the biofilter, moreover, the band (h) was consistently present at different inlet concentrations. The result indicates that the Pseudomonas was dominant in the biofilter, which is in agreement with earlier reported biofiltration system
of ethylene packing activated carbon (Kim, 2006). Like the band (h), Arthrobacter sp. was consistently present at different inlet concentrations. Arthrobacter sp., as alkane-utilizer, has been found to be capable of oxidizing ethylene to epoxyethane (Hou et al., 1983). Xanthomonas sp. and M. vaccae were found exclusively at middle concentration of inlet ethylene (200–300 ppm). Xanthobacter sp. has been reported to play an important role in oxidizing ethylene, which can utilize ethylene as sole substrate (Ginkel et al., 1987; Hou et al., 1983). M. vaccae was also known to utilize ethylene, which was immobilized in a bioreactor based on compost, to be responsible for the removal of ethylene (Elsgaard, 1998, 2000). A third bacterial group that includes R. erythropolis and N. fluminea occurred at the relatively high concentration of influent ethylene (600–1000 ppm). They are able to oxidize ethylene, and show high oxidizing activity under conditions with ethylene and L-hexene (Kulikova and Bezborodov, 2001; van Ginkel et al., 1987). Taken together, the results reported here support the hypothesis that biofilter operating strategies such as inlet gas flow rate and loading can impose a selective pressure on the bac-
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Fig. 5. Phylogenetic tree of bacterial populations identified in the biofilter during operation periods, based on the 16S rRNA gene sequences.
terial community that is large enough to influence relative abundance of microbial species that predominate over time.
4. Conclusion Our experimental data demonstrate that the biofilter packing natural zeolite is capable of successfully purifying air containing ethylene. The removal efficiency of this system in different ethylene concentrations was evaluated and found to be satisfactory. The feasibility of this biofilter system needs to be further supported by its design, aiming to prevent pressure drop. The results of DGGE provide valuable information on the roles or functions of bacterial species in the bacterial community during the biofiltration processes. The strains identified in this study are potential candidate strains for the ethylene removal in biofiltration. Acknowledgements This work was supported by Grants from Ministry of Science and Technology of China (2009DFR30650) and the Innovation Foundation of BUAA for PhD Graduates. We also appreciate the Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education for their helps.
Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.biortech.2010.07.119.
References Arnold, M., Reittu, A., von Wright, A., Martikainen, P.J., Suihko, M.L., 1997. Bacterial degradation of styrene in waste gases using a peat filter. Appl. Microbiol. Biotechnol. 48, 738–744. Babbitt, C.W., Pacheco, A., Lindner, A.S., 2009. Methanol removal efficiency and bacterial diversity of an activated carbon biofilter. Bioresour. Technol. 100, 6207–6216. Bagherpour, M.B., Nikazar, M., Welander, U., Bonakdarpour, B., Sanati, M., 2005. Effects of irrigation and water content of packings on alpha-pinene vapours biofiltration performance. Biochem. Eng. J. 24, 185–193. Calvo-Bado, L.A., Pettitt, T.R., Parsons, N., Petch, G.M., Morgan, J.A.W., Whipps, J.M., 2003. Spatial and temporal analysis of the microbial community in slow sand filters used for treating horticultural irrigation water. Appl. Environ. Microbiol. 69, 2116–2125. Clegg, C.D., Lovell, R.D.L., Hobbs, P.J., 2003. The impact of grassland management regime on the community structure of selected bacterial groups in soils. FEMS Microbiol. Ecol. 43, 263–270. Daigger, G.T., 1979. The Interaction of Physiological Adaptation and Transient Response for Pseudomonas putida and its Implications for Dynamic Modeling of Microbial Growth. Purdue University, United States. Ding, Y., Wu, W., Han, Z., Chen, Y., 2008. Correlation of reactor performance and bacterial community composition during the removal of trimethylamine in three-stage biofilters. Biochem. Eng. J. 38, 248–258. Elsgaard, L., 1998. Ethylene removal by a biofilter with immobilized bacteria. Appl. Environ. Microbiol. 64, 4168–4173. Elsgaard, L., 2000. Ethylene removal at low temperatures under biofilter and batch conditions. Appl. Environ. Microbiol. 66, 3878–3882. Garbeva, P., Elsas, J.D., Veen, J.A., 2007. Rhizosphere microbial community and its response to plant species and soil history. Plant Soil 302, 19–32. Ginkel, C.G., Habets-Crützen, A.Q., Last, A.R., Bont, J.A., 1987. A description of microbial growth on gaseous alkenes in a chemostat culture. Biotechnol. Bioeng. 30, 799–804. He, S.B., Xue, G., Kong, H.N., 2007. The performance of BAF using natural zeolite as filter media under conditions of low temperature and ammonium shock load. J. Hazard. Mater. 143, 291–295. Heyder, B.D., Overmeire, A., Langenhove, H.V., Verstraete, W., 1994. Ethene removal from a synthetic waste gas using a dry biobed. Biotechnol. Bioeng. 44, 642–648.
584
Y. Fu et al. / Bioresource Technology 102 (2011) 576–584
Hou, C.T., Patel, R., Laskin, A.I., Barnabe, N., Barist, I., 1983. Epoxidation of shortchain alkenes by resting-cell suspensions of propane-grown bacteria. Appl. Environ. Microbiol. 46, 171–177. Hoyer, L., 1995. Investigations of the ethylene buildup during transport of pot plants in controlled temperature trucks. Postharvest Biol. Technol. 5, 101–108. Jun, Y., Wenfeng, X., 2009. Ammonia biofiltration and community analysis of ammonia-oxidizing bacteria in biofilters. Bioresour. Technol. 100, 3869– 3876. Kim, J.G., 2006. Assessment of ethylene removal with Pseudomonas strains. J. Hazard. Mater. 131, 131–136. Konstantinov, S.R., Zhu, W.Y., Williams, B.A., Tamminga, S., Vos, W.M., Akkermans, A.D., 2003. Effect of fermentable carbohydrates on piglet faecal bacterial communities as revealed by denaturing gradient gel electrophoresis analysis of 16S ribosomal DNA. FEMS Microbiol. Ecol. 43, 225–235. Kulikova, A.K., Bezborodov, A.M., 2001. Assimilation of propane and characterization of propane monooxygenase from Rhodococcus erythropolis 3/ 89. Appl. Biochem. Microbiol. 37, 164–167. Li, C., Moe, W., 2004. Assessment of microbial populations in methyl ethyl ketone degrading biofilters by denaturing gradient gel electrophoresis. Appl. Microbiol. Biotechnol. 64, 568–575. Manning, W.J., Feder, W.A., 1980. Biomonitoring Air Pollutants with Plants. Applied Science Publishers, London. Mathur, A.K., Majumder, C.B., 2008. Biofiltration of benzene emissions: biofilter response to variations in the pollutants inlet concentration and gas flow rate. J Sci Ind Res. (India) 67, 243–248. Möhlenhoff, P., Müller, L., Gorbushina, A.A., Petersen, K., 2001. Molecular approach to the characterisation of fungal communities: methods for DNA extraction, PCR
amplification and DGGE analysis of painted art objects. FEMS Microbiol. Lett. 195, 169–173. Sawada, S., Totsuka, T., 1986. Natural and anthropogenic sources and fate of atmospheric ethylene. Atmos. Environ. 20, 821–832. Schnelle, K., Brown, C., 2002. Air Pollution Control Technology Handbook. CRC Press, Boca Raton. Sercu, B., Boon, N., Beken, S.V., Verstraete, W., Langenhove, H.V., 2007. Performance and microbial analysis of defined and non-defined inocula for the removal of dimethyl sulfide in a biotrickling filter. Biotechnol. Bioeng. 96, 661–672. Stoeckinger, A., 2004. Zeolite Packed Biologically Active Filter (Biofilter) to Reduce Odorous Emissions from a Confined Swine Building. Oregon State University, United States. Tambwekar, J.A., 2002. Biofiltration of Trace Concentrations of Ethylene in Air. Rutgers, The State University of New Jersey, United States. Tamura, K., Dudley, J., Nei, M., Kumar, S., 2007. MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol. Biol. Evol. 24, 1596–1599. Temple, P.J., Sun, E.-J., Krause, G.H.M., 1998. Peroxyacyl Nitrates (PANs) and Other Minor Pollutants. Air & Waste Management Association, Pittsburg, Pennsylvania. van Ginkel, C.G., Welten, H.G.J., de Bont, J.A.M., 1987. Growth and stability of ethene-utilizing bacteria on compost at very low substrate concentrations. FEMS Microbiol. Lett. 45, 65–69. Warmink, J.A., van Elsas, J.D., 2008. Selection of bacterial populations in the mycosphere of Laccaria proxima: is type III secretion involved? ISME J. 2, 887– 900. Yin, J., Xu, W.F., 2009. Ammonia biofiltration and community analysis of ammoniaoxidizing bacteria in biofilters. Bioresour. Technol. 100, 3869–3876.