Co-Treatment with Single and Ternary Mixture Gas of Dimethyl Sulfide, Propanethiol, and Toluene by a Macrokinetic Analysis in a Biotrickling Filter Seeded with Alcaligenes sp. SY1 and Pseudomonas Putida S1

The biotrickling filter (BTF) treatment is an effective way of dealing with air pollution caused by volatile organic compounds (VOCs). However, this approach is typically used for single VOCs treatment but not for the mixtures of VOC and volatile organic sulfur compounds (VOSCs), even if they are often encountered in industrial applications. Therefore, we investigated the performance of BTF for single and ternary mixture gas of dimethyl sulfide (DMS), propanethiol, and toluene, respectively. Results showed that the co-treatment enhanced the removal efficiency of toluene, but not of dimethyl sulfide or propanethiol. Maximum removal rates (rmax) of DMS, propanethiol and toluene were calculated to be 256.41 g·m−3·h−1, 204.08 g·m−3·h−1 and 90.91 g·m−3·h−1, respectively. For a gas mixture of these three constituents, rmax was measured to be 114.94 g·m−3·h−1, 104.17 g·m−3·h−1 and 99.01 g·m−3·h−1, separately. Illumina MiSeq sequencing analysis further indicated that Proteobacteria and Bacteroidetes were the major bacterial groups in BTF packing materials. A shift of bacterial community structure was observed during the biodegradation process.


Introduction
The removal of odorous waste, including volatile organic sulfur compounds (VOSCs) has been paid increasing attention for air pollution control solutions, considering their aqueous solubility and gradual diffusion into the atmosphere [1][2][3]. VOSCs are extremely toxic, corrosive, and malodorous compounds, which have significant effects on animal and human health as well as the environment [4]. Moreover, VOSCs very often co-exist with volatile organic compounds (VOCs). BTEX, including benzene, toluene, ethylbenzene, and xylene as paint thinner, are widely applied in machining operations and plating shops. The mixture of dimethyl sulfide (DMS), propanethiol, and toluene can be found in the exhaust gas from pharmaceutical, pesticide, and rubber industries. For example, an exhaust gas from a pesticide company can contain DMS (C DMS = 100 mg·m −3~3 00 mg·m −3 ), propanethiol (C Propanethiol = 30 mg·m −3~1 50 mg·m −3 ), and toluene (C Toluene = 100 mg·m −3~4 00 mg·m −3 ). Thus, it is worthwhile to focus on treatment of typical VOSCs and VOCs in terms of those contaminants, which are common in reality.
In this work, a BTF, inoculated with the DMS isolator Alcaligenes sp. SY1 [23], propanethiol isolator Pseudomonas putida S1 [41], and the acclimated activated sludge with toluene degradability, was set up for the treatment of the mixture containing DMS, propanethiol, and toluene. Furthermore, the biofilms from three different periods were collected and sequenced using the Illumina MiSeq platform for a comprehensive understanding of microbial compositions and structures.

Microorganism Culture and Medium Preparation
The microorganism seeding method and the degradation ability for DMS and propanethiol of Alcaligenes sp. SY1 and Pseudomonas putida S1, were the same methods utilized in our previous research [26,41]. A few acclimatized activated sludges were also used in system.
A mineral salt medium (MSM) was contained: 4.5 g Na 2 HPO 4 ·12H 2 O, 2.5 g KH 2 PO 4 , 1.0 g NH 4 [38]. 12 L DMS and propanethiol was injected into each flask and the total volume of solution was 500 mL for each bacteria strain. After being cultured at 30 • C and 160 r/min, suspension containing a specific bacteria strain was obtained as the inoculant for the biofilter.

BTF Setup and Operation Condition
The schematic of a multi-layer BTF is shown in Supplementary Materials Figure S1; the BTF was constructed using a plexi-glass with a total height of 90 cm, an inner diameter 12 cm, an outer diameter of 15 cm, and the height of 25 cm for each layer. The BTF was packed with a polyurethane pall ring, which has an initial porosity 0.91. Gas sampling ports were located along the height of the biofilter, with another two sampling ports located in each layer for the collection of biomass samples.
The air stream for the BTF was built from two sub air streams. One air stream carries pollutants by passing air through a glass bubbler of 250 mL containing liquid VOCs at room temperature and then mixed with major air stream in mixture reactor in order to homogeneous mixing trough BTF reactor. Concentrations of VOCs in the synthetic gas stream were varied by changing the air flow rate through the bubbler. The pH of the system was adjusted by HCl (10%) solution through an auto-pH adjustor (Kesheng, Hangzhou, China) and was controlled in the range of 6.86 to 7.20. Pressure drop in the gas phase through the fixed bed reactor was measured by a manometer (AZ8252, Guangzhou, China). The nutrient solution was sprayed over the top of the column at 6 L·h −1 by a peristaltic pump (Longerpump ® BT600-2J, Hangzhou, China). Gas samples were collected by gas tight syringes (Gaoge, Shanghai, China) fitted with 3-way luer-lock and measured by GC analysis. The measurement procedure for weight of packing material, porosity, and liquid maintaining capacity was based on our previous work [32].
During the startup period, BTFs were operated in a continuous manner, i.e., the nutrient liquid trickled through the packing for 24 h. The trickling rate was controlled at 6 L·h −1 . 50% of the trickling liquid was replaced every 5 days. The reactor was operated in a closed loop mode with respect to liquid to maximize cell adhesion to the packing material. The start-up method of the BTF was the method reported by Jin [34]. The BTF was initially started up with synthesized gas flow and the corresponding empty bed retention time (EBRT) was 56 s. Initial concentrations were 200.0 mg·m −3 for DMS and 100.0 mg·m −3 for propanethiol.

Analytical Method
DMS, propanethiol, and toluene were measured by gas chromatography (SHIMADZU GC-14B, Kyoto, Japan,) coupled with flame photometric detector (FPD, SHIMADZU, Japan) and flame ionization detector (FID, SHIMADZU, Japan). Hydrogen and air flow rates for FPD and FID were 50 mL·min −1 and nitrogen used as carrier gas was 200 mL·min −1 . Temperatures of the injection, oven, and detection were 180 • C, 100 • C, and 180 • C, respectively.
The CO 2 content was determined through GC9790 gas chromatograph (Fuli TDX-01, 30 m × 0.32 mm × 20µm, Technologies, Taizhou, China). The pH value of the sample was adjusted to 2.0, making sure the inorganic HCO 3 − transfer to CO 2 completely. The detected samples were collected by the microsampler from headspace vapors of closed system and analyzed by using thermal conductivity detector (TCD). The temperature of the oven and detection were 100 • C and 150 • C, separately. The column flow rate was set as 5 mL·min −1 . The external standard method was utilized to calculate CO 2 concentration.
The startup period of BTF was from days 0-days 20, the steady period was from days 21-days 140, the end period was from days 141-days 252.
Operational taxonomic units (OTUs) were assigned by applying UPARSE, and with 97% of sequences similarity were clustered into OTUs. Each OTU was assigned by using the Ribosomal Database Project (RDP) classifier to identify the typical sequence [44].

Operation Parameters of BTF
The inlet loading rate (ILR) of BTF is defined as, where C i and Q are the mass concentration of the contaminants (%) and the mass flow rate of the inlet stream (g·h −1 ), respectively. V is the volume of BTF bioreactor (m 3 ). The performance of the BTF is evaluated by eliminate capacity (EC) (g·m −3 ·h −1 ), EBRTs, and RE (%). EC is the measurement of contaminant removal capacity at a given ILR. EBRT is the measurement of gas residence time within the reactor medium. ILR, EC, EBRT, and RE were calculated using the following equations: Eliminate Capacity: Empty bed resistance time: Removal efficiency:

BTFs Operation and Startup Period
BTFs operated for 252 days to treat individual and synthesis gas. The study was performed for individual and ternary co-treatment with various parameters, such as inlet loading rate (ILR) and empty bed retention time (EBRT). The ILR and EBRT experiment conditions changes are presented in detail in Table S1.
During the startup period (day 1 to day 22), the inlet concentration of the mixture pollutants was maintained around 200.0 mg·m −3 at the ratio of DMS, propanethiol and toluene at 2:1:1 with a gas flow rate of 0.2 m 3 ·h −1 . In other words, the ILR and EBRT were maintained at 11.4 g·m −3 ·h −1 and 56 s, respectively. Over 80.0% of removal efficiency (RE) was observed in the BTF treating DMS on day 20, while the removal efficiency of propanethiol and toluene was stable after 14 and 19 days, respectively. The system was seeded with Alcaligenes sp. SY1 and Pseudomonas putida S1.

Kinetic Analysis
At the steady state, the growth rate of biofilms was equaled by their decay rate, the biological system was balanced. Therefore, a Michaelis-Menten (M-M) model can be applied as a macrokinetic analysis to the BTF system, which in terms of kinetic constants, was stable during the period. The degradation rate of contaminants within the biofilms was investigated in the gas-phase BTF and could be estimated by following equation: (5) in which r max is the maximum biodegradation rate (g·m −3 ·h −1 ) and K s is the saturation M-M model constant (mg·L −1 ) in the gas phase. C ln is the natural logarithm mean con- According to the linear relationship between 1/C ln and [V/Q(C i − C o )] could be calculated from the intercept and slope, respectively [45,46].

Performance of BTF for Mixed Gas during Different Phases
After the startup period, the BTF was tested under different conditions from phase I to phase III. The variations of inlet and outlet concentration of mixture pollutants in different phases are shown in Figure 1. EBRTs of 56 s, 28 s and 20 s were designed for phase I to phase III.  During phase I (from day 23 to day 39), initially, RE was increased with the growth of inlet concentration. However, due to sudden enhancement of inlet concentration to 998.67 mg·m −3 from 895.64 mg·m −3 on day 37, the RE was decreased from 89.56% to 86.45% During phase I (from day 23 to day 39), initially, RE was increased with the growth of inlet concentration. However, due to sudden enhancement of inlet concentration to 998.67 mg·m −3 from 895.64 mg·m −3 on day 37, the RE was decreased from 89.56% to 86.45% and maintained constantly until the end of phase I. The similar tendency was observed during phase II (day 40 to day 56), RE was slightly increased with an enhancement of inlet concentration until day 46. When the inlet concentration was enhanced from increased with the growth of inlet concentration. However, due to sudden enhancement of inlet concentration to 621.07 mg·m −3 to 714.70 mg·m −3 , RE was suddenly dropped from 90.30% to 86.20% and keep gradually decreased to the end of phase II at 81.10%. During the phase III (day 57 to day 77), the tendency was different. An obvious outlet concentration increase was observed during phase III, while no significant outlet concentration enhancement was observed during phase I and phase II. Moreover, RE drops from 88.41% to 80.90% without an obvious increasing period during phase III.

Effect of ILR (Inlet Loading Rate) on the EC of Mixture Treatment
The different EC corresponding to ILR variations for the mixed pollutants treatment is presented in Figure 2. The behavior of BTF in mixture pollutants treatment also can be categorized into two parts according to liner regression: (I) diffusion constraints (DC, up to 130.00 g·m −3 ·h −1 of ILR according to Figure 2); and (II) reaction constraints (RC, ILRs greater than 130.00 g·m −3 ·h −1 ). Diffusion rate and reaction rate both significantly affected the total behavior of BTF during the operation [47][48][49]. In DC, reaction rate in the biofilm was greater than the diffusion rate from the gaseous phase to aqueous phase, and as a result, diffusion rate was the limiting factor, in terms of a lower ILR. Contrarily, with a higher ILR, the diffusion rate was greater than the reaction rate; the resulting reaction rate was to be the control factor. Thus, it could be due to the restriction of reaction rate, data slightly deviated from line of 100% of EC when ILR grew higher. 100% of EC 20s Figure 2. Effect of ILR on RE of BTF in mixture treatment during different phases.
The variation of EC with different ILR under different EBRTs for DMS, propanethiol, and toluene in mixture treatment by BTF is presented in Figure 3a-c. At high ILR, ECs of DMS did not deviate far from the ideal line of the 100% removal line. The tendency of propanethiol and toluene were similar. As shown in Figure 3a-c, the maximum EC of DMS and propanethiol were observed on maximum ILR under EBRT of 20 s; however, the maximum EC of toluene occurred under EBRT of 28 s. It confirmed that marginal toluene ILR of RC was lower than the other two contaminants.   Figure 3a-c, the maximum EC of DMS and propanethiol were observed on maximum ILR under EBRT of 20 s; however, the maximum EC of toluene occurred under EBRT of 28 s. It confirmed that marginal toluene ILR of RC was lower than the other two contaminants.     Among these pollutants, the value of ILR in terms of certain EC followed the order: DMS > propanethiol > toluene; DMS was thus the most stubborn chemical among these three in treatment.

Effect of ILR on the RE
According to Figure 2, total RE of mixture contaminants was maintained above 83.10%, 74.00%, and 68.90%, corresponding with EBRTs of 56 s, 28 s, and 20 s, respectively.
The variation of RE in mixture was affected not only by ILR, but also by the chemical property of individual contaminant. According to our experiment, the EC of toluene in mixture is enhanced in comparison with the performance as sole treatment in BTF, because of the existing co-metabolism during the mixture contaminant degradation process. Moreover, there are also competitive interactions among different contaminates as Amani has previously indicated [50]. Nevertheless, a competitive effect was not only dependent on the nature of contaminants but also relying on the structure of micro-communities in the environment. Deshusses stated that toluene could be co-treated well with H2S in order to enhance the performance of BTF [51]. On the contrary, Bentley has reported that VOSCs would have a competitive inhibition by other contaminants during the mixture treatment [23], which was also confirmed by Shu during DMS degradation by BTF system [44]. To conclude, RE was affected by ILR, chemical properties of contaminants, and structure of micro-communities.  Among these pollutants, the value of ILR in terms of certain EC followed the order: DMS > propanethiol > toluene; DMS was thus the most stubborn chemical among these three in treatment.

Effect of ILR on the RE
According to Figure 2, total RE of mixture contaminants was maintained above 83.10%, 74.00%, and 68.90%, corresponding with EBRTs of 56 s, 28 s, and 20 s, respectively.
The variation of RE in mixture was affected not only by ILR, but also by the chemical property of individual contaminant. According to our experiment, the EC of toluene in mixture is enhanced in comparison with the performance as sole treatment in BTF, because of the existing co-metabolism during the mixture contaminant degradation process. Moreover, there are also competitive interactions among different contaminates as Amani has previously indicated [50]. Nevertheless, a competitive effect was not only dependent on the nature of contaminants but also relying on the structure of micro-communities in the environment. Deshusses stated that toluene could be co-treated well with H 2 S in order to enhance the performance of BTF [51]. On the contrary, Bentley has reported that VOSCs would have a competitive inhibition by other contaminants during the mixture treatment [23], which was also confirmed by Shu during DMS degradation by BTF system [44]. To conclude, RE was affected by ILR, chemical properties of contaminants, and structure of micro-communities.

Performance of BTF for Single Pollutant Degradation
To compare between degradation of single contaminants and mixtures, each contaminant was tested under different operating parameters (phase I to phase III). The ILR, EC,  Figure 4a. Due to the sudden increases in ILR on day 82, 86, 90, and 94, there are several RE drops and EC increases suddenly. The flow rate was increased to 0.40 m 3 ·h −1 in order to achieved EBRTs of 28 s in phase II on day 98. ILR was decreased to 13.08 g·m −3 ·h −1 from 162.89 g·m −3 ·h −1 . The similar RE tendency was observed in terms of ILR was suddenly increased. In phase III (day 123 to day 140), the air stream was adjusted to 0.60 m 3 ·h −1 to achieve EBRT of 20 s. Difference appeared when the RE was not able to recover by time on day 138, an eliminated capacity was saturated. The maximum EC were observed 141.39 g·m −3 ·h −1 (phase I), 115.20 g·m −3 ·h −1 (phase II) and 160.54 g·m −3 ·h −1 (phase III).     The description propanethiol and toluene are shown in Figure 4b,c. Compared with EC and RE of propanethiol, toluene was more sensitive with suddenly enhanced ILR, and the variation gaps of EC and RE were amplified. Figures indicated that the BTF was saturated at the end of phase III (day 248), so that continued increasing ILR was not able to enhance EC. On the contrary, an inhibition effect was not negligible in terms of high inlet concentration. The maximum EC of propanethiol and toluene were observed 106.49 g·m −3 ·h −1 and 34.69 g·m −3 ·h −1 (phase I); 88.65 g·m −3 ·h −1 and 50.19 g·m −3 ·h −1 (phase II); 113.64 g·m −3 ·h −1 and 47.17 g·m −3 ·h −1 (phase III). According to Figure 4, the lowest EC was toluene. There are two main reasons: (1) As mentioned in Section 3.5.2, Betaproteobacteria (35.61%) and Gammaproteobacteria (15.56%) was correlated with DMS and propanehtiol biodegradation. Sphingobacteriia (20.54%) and Alphaproteobacteria (11.9%) was correlated with toluene biodegradation. (2) The BTF was overall operated 248 days, toluene was exposure up to days 77, and then switched to DMS (days 78-140), propanthiole (days 141-200), finally toluene (days 201-248). Thus there is a starving period 123 days for toluene, it also affected toluene biodegradation performance.
As discussed earlier in Section 3.1, DMS and propanethiol actually performed better in the single treatment process, while toluene was preferred in the ternary treatment rather than single treatment. As shown in Figures 3 and 4, the value of EC max in terms of this study was in order as follows: DMS single > propanethiol single > DMS in mixture > propanethiol in mixture > toluene in mixture > toluene single. This indicated that toluene was the most difficult pollutant to degrade among the three pollutants in either single or mixture system; however, its EC was larger under mixture circumstances revealing that the co-metabolism happened rather than competitive inhibition. Corresponding maximum EC data in previous studies was shown in Table 1.

Carbon Dioxide Production
In the biofiltration process, the organic contaminants are eventually converted to either water and carbon dioxide or biomass. Therefore, the CO 2 production (P CO 2 ) is an essential parameter corresponding with mineralization level. The effect of P CO 2 on the EC for various EBRTs is presented in Figure 5. The linear fitting of experiment data under different EBRTs during the mixture gas treatment were y = 2.26x (EBRT of 56 s), y = 1.88x (EBRT of 28 s), and y = 1.72x (EBRT of 20 s). In case of the inlet concentration ratio of DMS, propanethiol and toluene were 2:1:1; therefore, the stoichiometric ratios of P CO 2 per mass of completely degradation of mixture contaminants were 2.0, 3.0 and 7.0 respectively. Maximum ECs and P CO 2 coefficients of different individual pollutants and mixtures were as shown in Table S2, and among them P CO 2 of toluene was studied in various research. Compared to the results in the present study, the P CO 2 values in this study were relatively high, in terms of difference between three typical contaminants. The high mineralization rate of mixture contaminants revealed these compounds were entirely converted to water and CO 2 . The discrepancy between experimental data and stoichiometric values were sensible to explain as an accumulation of biomass in BTFs and partial CO 2 was dissolved in the MSM as formed H 2 CO 3 , HCO 3 2− , or CO 3 2− , in terms of the degradation process taking place in the aqueous phase. eralization rate of mixture contaminants revealed these compounds were entirely con-verted to water and CO2. The discrepancy between experimental data and stoichiometric values were sensible to explain as an accumulation of biomass in BTFs and partial CO2 was dissolved in the MSM as formed H2CO3, HCO3 2− , or CO3 2− , in terms of the degradation process taking place in the aqueous phase.

Biodegradation Kinetics for Single and Ternary Mixture Gas
The rmax and Ks under different EBRTs for DMS, propanethiol and toluene either in a single or in a mixture gas supply were calculated via Equation (5). As shown in Figure  6a,b, the variation of rmax value and Ks corresponded with EBRTs in single and mixture treatment during three phases. For single treatment, rmax of DMS, propanethiol and toluene were initially enhanced since EBRT decreased from 56 s to 28 s, and declined with continued decrease of EBRT from 28 s to 20 s. Ks of DMS and toluene followed the rmax tendency. However, Ks of propanethiol decreased straight if EBRT dropped. The Ks value indicated that during the single contaminant condition, propanethiol > DMS > toluene.

Biodegradation Kinetics for Single and Ternary Mixture Gas
The r max and K s under different EBRTs for DMS, propanethiol and toluene either in a single or in a mixture gas supply were calculated via Equation (5). As shown in Figure 6a,b, the variation of r max value and K s corresponded with EBRTs in single and mixture treatment during three phases. For single treatment, r max of DMS, propanethiol and toluene were initially enhanced since EBRT decreased from 56 s to 28 s, and declined with continued decrease of EBRT from 28 s to 20 s. K s of DMS and toluene followed the r max tendency. However, K s of propanethiol decreased straight if EBRT dropped. The K s value indicated that during the single contaminant condition, propanethiol > DMS > toluene. However, during mixture conditions the comparison was complex, under EBRT 56 s, propanethiol > DMS > toluene, under EBRT 28 s DMS > toluene > propanethiol, under EBRT 20 s propanethiol > toluene > DMS. The solubility of contaminants was propanethiol > DMS > toluene. This confirmed that in a single condition, the solubility would positively relate to K s [52]. But in mixture conditions, the K s value was not only related with solubility but also related with other facts such as reaction effect, and the intermediates would also influence the results.
In previous studies, Shu calculated that a r max of 115.7 g·m −3 ·h −1 and K s of 1.56 g·m −3 during single DMS biofiltration treatment [53], and Menard reported a r max of 39.4 g·m −3 ·h −1 and K s of 4.6 g·m −3 for toluene degradation [48]. As shown in Table 1, our r max data of DMS (single) and toluene (single) were all apparently higher than previous studies, while r max data of DMS mixture and toluene (mixture) were a bit lower than previous studies. r max value. the maximum amount of DMS degrade per unit of bio-filter volume, estimated from the Michaelis-Menten model was higher than that from the Haldane model (0.63 gs·gx −1 ·h −1 ), which is consistent with those reported by a previous study [41]. This result also confirmed by other odor gas degradation through BTF system fitting by the Michaelis-Menten model [50]. enhanced from phase I to phase II, and then declined from phase II to phase III. It is possible that the benefit of the intermediates was to enhance the solubility of toluene. These results of rmax and Ks are comparable within previous studies of rmax of 24.18 g·m −3 ·h −1 and 31.10 g·m −3 ·h −1 , and Ks of 0.62 g·m −3 and0.57 g·m −3 for DMS and toluene, respectively [45,54,55]. In general, a sensible inferring of physical identity for Ks is homoplastically to kinetics of enzyme, hence the lower Ks value and the higher enzymatic affinity for contaminants [56]. This explained treatment performance of toluene was better in mixture treatment The value of r max and K s are shown in Table 1. Compared with single treatment of DMS, either r max or K s decreased in the mixture treatment of DMS, in terms of the additional carbon resource not only available for microbial communities, it also leads to a reaction effect between different contaminants, resulting in reaction constraints; however, the value of toluene was increased. r max and K s of DMS and toluene were both initially enhanced from phase I to phase II, and then declined from phase II to phase III. It is possible that the benefit of the intermediates was to enhance the solubility of toluene. These results of r max and K s are comparable within previous studies of r max of 24.18 g·m −3 ·h −1 and 31.10 g·m −3 ·h −1 , and K s of 0.62 g·m −3 and0.57 g·m −3 for DMS and toluene, respectively [45,54,55].
In general, a sensible inferring of physical identity for K s is homoplastically to kinetics of enzyme, hence the lower K s value and the higher enzymatic affinity for contaminants [56]. This explained treatment performance of toluene was better in mixture treatment rather than single treatment. A possible co-metabolism with toluene was the main mechanism during DC area, in terms of its solubility increasing, resulting in the r max enhancement during this stage and K s decreased under EBRTs 20 s. Co-metabolism/enzymatic affinity is a possible reason why the EC for toluene was enhanced when it was introduced along with the other sulfur-containing compounds. As inlet concentration of mixture gas was continuously increasing and the EBRT was decreasing, co-metabolism plus an occurrence of a reaction effect were both intensified; however, co-metabolism would not compensate the performance loss due to the reaction effect [8,57]. Thus, r max and K s both declined.

Bacterial Community Diversity and Composition
Three samples from the BTF system of 20 days, 75 days, and 120 days were analyzed by Illumina high-throughput sequencing, with every length 430 bp and at least 49,515 sequences obtained for each sample. The objective for this comparison was to understand how residence time and the other simulated conditions, such as concentration, components will affect the microbial colonies. The number of OTUs and α-diversity of these samples were shown in Table S3. Previously, Ma indicated that larger Shannon index values and smaller Simpson index values were both representative of the higher α-diversity [58]. Wang found that bacterial structure became simpler after contaminants degradation [59], which could lead to lower α-diversity and OUT number with time passing by the similar trend being observed: the biofilm sampled at 120 days contained the lowest α-diversity (Shannon index 4.08), while the initial biofilm had the highest α-diversity (Shannon index 5.03) and richness (OTU number 2599). After, microbial diversity had been changed. A large number of secondary intermediate products have been produced in the process of microbial degradation of DMS, propyl mercaptan, and toluene [38,41]. A large number of intermediate products generated from the degradation process made the microbial population keep in dynamic equilibrium.

Microbial Community Structures at the Phylum Level
In the present study, the microbial analysis was focus on bacteria, and over 99.99% of obtained sequences were assigned bacteria. On average, 3.05% of the sequences were not classified at the phylum level. As shown in Figure 7a, the seven major phyla were Proteobacteria (66.42% on average), Bacteroidetes (21.76%), Gemmatimonadetes (2.00%), Acidobacteria (1.89%), Deinococcus-Thermus (1.87%), Firmicutes (1.38%), and Candidate (0.69%). The most abundant phylum was Proteobacteria, which ranged from 63.01% to 68.28% in the samples. Among the Proteobacteria as shown in Figure 7b, Betaproteobacteria ranked first with an average percentage of 35.61%, followed by Sphingobacteriia (20.54%), Gammaproteobacteria (15.56%) and Alphaproteobacteria (11.91%). The high percentage of Betaproteobacteria and Grammaproteobaceria was as a result of anthropogenic inoculation of Alcaligenes sp. SY1 and Pseudomonas.putia S1, which was belonged to these classes [23]. Sphingobacteriia and Alphaproteobacteria were also reported as main class to degrade toluene in bioreactor [60,61]. Thus, these bacteria play key role during VOCs and VOC treatment [62]. As shown in Figure 7b, during the first 20 days operation period, Gammaproteobacteria (28.75%) Sphingobacteriia (21.57%), Alphaproteobacteria (17.63%), Betaproteobacteria (13.84%) were the most abundant bacterial class. However, Betaproteobacteria would dramatically increase to 42.25%, with the decrease percentage of Gammaproteobacteria and Alphaproteobacteria to 10.80% and 11.78% for the next 55 days of operation period. At this period, the Sphingobacteriia class was slightly declined to 2.00%. In the last 45 days of operation, Betaproteobacteria still kept the increased tendency to 50.74%, while Gammaproteobacteria and Alphaproteobacteria continued declined slightly to 7.12% and 6.32%. Sphingobacteriia was increased by 1.50% during this period.
In Figure 7c, Thiobacillus, Pseudomonas, and Alcaligenes were the most abundant genera in this BTF. Thiobacillus was dramatically increased from 0.37% (20 days) to 40.24% (75 days) and then slightly declined to 32.72% (120 days). which correlated with toluene in the mixture of VOCs aeration to BTF from day 1 to days 77, then to DMS aeration from days 78 to days 140. Pseudomonas was declined from 20.08% (20 days) to 4.67% (75 days) and then recovered to 7.25% (120 days). The drop of Pseudomonas is due to Alcaligenes inoculation from day 1 to days 20 in startup period, and Thiobacillus fast growth from day 1 to day 77 and recovered on day 120 was correlated with DMS aeration. Alcaligenes was the most stable genera during three periods, the percentage of Alcaligenes was kept from 13.08% (20 days) to 12.09% (75 days) and then reached to 15.55% (120 days), which was under inoculation Alcaligenes at startup period and DMS single aeration from days 78 to days 140 are reasonable.
The predominant of Gammaproteobacteria during all three periods explained the maximum EC of DMS is relatively higher than the other two contaminants in bottom and middle layer, and also confirmed that Alcaligenes sp. SY1 is a promising strain during co-treatment of DMS removal. Sphingobacteriia remained constant from the beginning to the end of treatment; consequently, the toluene performance of EC and RE were keep stable in either single or ternary treatment of contaminants in upper layer. The initial deterioration of Gammaproteobacteria could be explained the inoculated Pseudomonas putida. S1 was affected either by inhibition in the higher inlet load of contaminants or competition effect by other microbial communities. However, the propanethiol performance of EC and RE was not significantly influenced by deterioration due to the ILR was mostly under DC area. The significant enhancement of Betaproteobacteria was mainly because of the growth of Thiobacillus, which was reported to apply in VOSCs degradation and toluene degradation [63,64].

Microscopic Observations
FESEM was used to observe the biofilm formation and mature as time went by. And The sample for FESEM observation was obtained from the bottom of the first packing layer. As shown in Figure S2a, after 20 days of inoculation, normal density cells number could be observed on the surface of packing material, and between bacterial unit mycelial structures, non-colonized regions on the surface could also be observed. In Figure S2b, high cell growth was observed after 77 days operation, and more than one layer of biofilm adhered on packing material. Globular bacterium and rod-shaped bacterium were predominant in the field. In Figure S2c, the bacterial colonies showed that several layers keep adhesion together with a mycelial structure, could not even distinguish the boundary of a single bacteria unit. The presence of an intensive number of microbial communities was also observed in terms of high density of cell growth. This phenomenon was also observed in toluene and VOCs removal in the BTF system [60,65].

Conclusions
BTF with Alcaligenes sp. SY1 was shown to effectively degrade DMS, propanethiol and, toluene with stable performance. The maximum removal rate (rmax) for single DMS, propanethiol, and toluene was calculated as 256.41 g·m −3 ·h −1 , 204.08 g·m −3 ·h −1 , and 90.91 g·m −3 ·h −1 , respectively. When they were mixed with the other two, VOC or VOSC, the rmax

Microscopic Observations
FESEM was used to observe the biofilm formation and mature as time went by. And The sample for FESEM observation was obtained from the bottom of the first packing layer. As shown in Figure S2a, after 20 days of inoculation, normal density cells number could be observed on the surface of packing material, and between bacterial unit mycelial structures, non-colonized regions on the surface could also be observed. In Figure S2b, high cell growth was observed after 77 days operation, and more than one layer of biofilm adhered on packing material. Globular bacterium and rod-shaped bacterium were predominant in the field. In Figure S2c, the bacterial colonies showed that several layers keep adhesion together with a mycelial structure, could not even distinguish the boundary of a single bacteria unit. The presence of an intensive number of microbial communities was also observed in terms of high density of cell growth. This phenomenon was also observed in toluene and VOCs removal in the BTF system [60,65].

Conclusions
BTF with Alcaligenes sp. SY1 was shown to effectively degrade DMS, propanethiol and, toluene with stable performance. The maximum removal rate (r max ) for single DMS, propanethiol, and toluene was calculated as 256.41 g·m −3 ·h −1 , 204.08 g·m −3 ·h −1 , and 90.91 g·m −3 ·h −1 , respectively. When they were mixed with the other two, VOC or VOSC, the r max increased for toluene, but decreased for DMS and propanethiol. Proteobacteria and Bacteroidetes were the major bacterial groups in BTF packing materials, which confirmed that the inoculation did succeed during the BTF process. Therefore, Alcaligenes sp. SY1 and Pseudomonas putida S1 has significant potential for treating DMS, propanethiol, and toluene either individually or collectively.