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Microbial communities in the functional areas of a biofilm reactor with anaerobic–aerobic process for oily wastewater treatment
Accepted Manuscript Microbial communities in the functional areas of a biofilm reactor with anaerobic–aerobic process for oily wastewater treatment Jianhua Li, Shanshan Sun, Ping Yan, Li Fang, Yang Yu, Yangdong Xiang, Di Wang, Yejing Gong, Yanjun Gong, Zhongzhi Zhang PII: DOI: Reference:
S0960-8524(17)30521-7 http://dx.doi.org/10.1016/j.biortech.2017.04.033 BITE 17928
To appear in:
Bioresource Technology
Received Date: Revised Date: Accepted Date:
8 February 2017 5 April 2017 8 April 2017
Please cite this article as: Li, J., Sun, S., Yan, P., Fang, L., Yu, Y., Xiang, Y., Wang, D., Gong, Y., Gong, Y., Zhang, Z., Microbial communities in the functional areas of a biofilm reactor with anaerobic–aerobic process for oily wastewater treatment, Bioresource Technology (2017), doi: http://dx.doi.org/10.1016/j.biortech.2017.04.033
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Microbial communities in the functional areas of a biofilm reactor with anaerobic– aerobic process for oily wastewater treatment Jianhua Lia, Shanshan Suna*, Ping Yanb, Li Fangc, Yang Yuc, Yangdong Xiangc, Di Wanga, Yejing Gonga, Yanjun Gonga, Zhongzhi Zhanga
a
State Key Laboratory of Heavy Oil Processing, College of Chemical Engineering,
China University of Petroleum, Beijing 102249, China b
Dalian Petrochemical Branch Company, PetroChina, Dalian 116000, China
c
China National Petroleum Corporation Liaohe Petrochemical Company , Panjin
124000, China.
*Corresponding author: Tel.: +86 10 89734284 Fax: +86 10 89734284 E-mail: [email protected](S.Sun)
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Abstract Microbial communities in the functional areas of biofilm reactors with large height–diameter ratio using the anaerobic-aerobic (A/O) reflux process was investigated to treat heavy oil refinery wastewater without pretreatment. In the process, chemical oxygen demand (COD) and total nitrogen (TN) removal reached 93.2% and 82.8%, and the anaerobic biofilm reactor was responsible for 95% and 99%, respectively. Areas for hydrolysis acidification and acetic acid production, methane production, and COD recovery were obvious in the anaerobic reactor. Among all areas, area for hydrolysis acidification and acetic acid production was the key factor to improve COD removal efficiency. High throughput sequencing of 16S rDNA gene showed that the native community was mainly composed of functional groups for hydrocarbon degradation, syntrophic bacteria union body, methanogenesis, nitrification, denitrification, and sulfate reduction. The deviations between predicted values and actual COD and TN removal were less than 5% in the optimal prediction model.
Keywords: Wastewater treatment, Biofilm reactor, Microbial community diversity, COD removal, Optimal prediction model
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1. Introduction Heavy oil refinery wastewater contains high amounts of organic pollutants. This wastewater contain low concentrations of several hydrocarbon substances, such as oil, emulsified oil, and dissolved and dispersed oil, which are unrecoverable (Ji et al., 2009; Lu et al., 2009). Traditional treatment of heavy oil refinery wastewater is time consuming and expensive. The traditional anaerobic-aerobic (A/O) technology cannot be directly used to process this water when the concentration of petroleum or oil is more than 20 mg/L. For example, oil in this wastewater is removed by first using a physicalchemical method, such as oil separation and air floatation, and then anaerobic and aerobic biodegradation (Liu et al., 2013; Zhao et al., 2011). The waste produced by flocculants and emulsion breaker used in the physical-chemical process will cause second pollution (Lasindrang et al., 2015; Qin et al., 2007). Many provinces in China have implemented more stringent regulatory standards to discharge wastewater. Resulting problems would be prevented if the efficiency of biological reactor treatment and organic loading of petroleum or oil would be enhanced. Biological biofilm process is one of the main technologies of wastewater treatment. This process presents great development potential (Diya’uddeen et al., 2011; Ma et al., 2009; Shokrollahzadeh et al., 2008). The anaerobic biofilm reactor is still the core technology for wastewater treatment because of its low operational cost, high volume load, less sludge, biological detoxification, improvement of wastewater biodegradability, and production of methane as clean energy, among others (Zhang et al., 2012; Zimmerman et al., 2009). The water from the inlet to the outlet, given that an up-flow feeding pattern is adopted in an anaerobic reactor, undergoes hydrolysis, acidification, and methanogenesis. These processes occur in different stages of
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anaerobic biofilm formation, because these processes required different reaction substrates and dissolved oxygen (DO) concentrations (Escudie et al., 2011; Fakhru'lRazi et al., 2010). Thus, a biofilm is divided into several functional areas. Each functional area plays an important role in the efficiency of wastewater treatment of the anaerobic biofilm reactor. The A/O process is composed of aerobic and anaerobic reactors. Wastewater treated by an anaerobic reactor can be degraded further by an aerobic reactor (Gannoun et al., 2016; Guo et al., 2009; Haritash & Kaushik, 2009). Ammonia is oxidized to nitrate in an aerobic reactor, and the nitrification liquid is refluxed into an anaerobic reactor to realize total nitrogen (TN) removal by denitrification (Murali et al., 2013; Reddy et al., 2011). The nitrification liquid can be used to dilute the influent of an anaerobic reactor such that the impact of the biological membrane from highconcentration petroleum or oil could be reduced (Jiao et al., 2011; Rizzo, 2011). Therefore, enhancing the efficiency of wastewater treatment by improving the reflux ratio is beneficial (Guo et al., 2014; Reddy et al., 2011). However, the reflux ratio of the A/O reflux process is generally not too high, or the environment of the anaerobic reactor would be destroyed if the reflux ratio is further increased. In an anaerobic reactor, methanogenesis can be conducted smoothly when the oxidation-reduction potential (ORP) is lower than −150 mV. The efficiency of wastewater treatment is improved by not destroying the anaerobic environment to improve the reflux ratio (Song et al., 2011). For a higher reflux ratio, an anoxic reactor, namely, anaerobic-anoxic-aerobic Process (A/A/O), would be used (Gao et al., 2014; Wang et al., 2012), but such requirement increase the cost of wastewater treatment.
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This study focused on the microbial communities in the functional areas of a biofilm reactor without pretreatment A/O process to treat heavy oil refinery wastewater containing petroleum (70.5–95.8mg/L). The no-pretreatment A/O process is established to resolve the problems of time-consuming treatment process and secondary pollution produced by flocculant used in the chemical oil removal unit. The division of the functional areas in a biofilm and microbial diversity in these areas provided important basis for the study of the degradation mechanism of the proposed process. The existence of syntrophic bacteria facilitated the degradation of petroleum and refractory organic compounds. The influence of multiple factors on the efficiencies of chemical oxygen demand (COD) and TN removal were investigated using the optimal prediction model, providing a reference for the industrial application of the proposed process. 2. Materials and methods 2.1 Wastewater treatment by A/O process with biofilm reactor 2.1.1 Wastewater characteristics Heavy oil refinery wastewater was collected from the Petrochemical Industries Co. in Liaoning province, China. Sampling site was located at the inlet of wastewater treatment plants before the physical-chemical process. Wastewater characteristics are shown in Table 1. 2.1.2 Experimental set-up Experiments were performed in a lab-scale A/O reflux process (Fig. 1), which consisted of anaerobic and aerobic biofilm reactors. The A/O reflux setup was made of Plexiglas with a total liquid volume of 28.5 L (anaerobic biofilm reactor: 19 L, 2 m high and with height-to-diameter ratio of 20; aerobic biofilm reactor: 9.5 L, 1 m high and with height-to-diameter ratio of 15). Soft carrier, with 1.3 m long hydroformylation
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fiber (Fig.1S), was placed in the anaerobic biofilm reactor with a packing ratio of 30% (vol/vol). The aerobic biofilm reactor was filled with elastic filler with packing ratio of 30%. An inner loop flow guide tube was installed at the middle of the aerobic reactor. Aeration devices were fixed on the bottom inner loop flow guide tube. Wastewater was first pumped into the anaerobic biofilm reactor from a storage tank and then flowed into the aerobic biofilm reactor and the effluent reflux into the anaerobic biofilm reactor according a certain reflux ratio. COD and TN were removed simultaneously in the anaerobic biofilm reactor, and the aerobic biofilm reactor was used to further remove COD and nitrify ammonia nitrogen. 2.1.3 Reactor start-up and operation The anaerobic biofilm reactor was started up first. After being seeded with sludge collected from the hydrolysis acidification tank of a wastewater treatment plant in Beijing, China. To promote the growth of microorganism, glucose solution (1.33 g/L) and wastewater were separately injected into the reactor with two identical metering pumps at the flow rates of 6.9 mL/h and 184.7 mL/h. Subsequently, tee pipe fitting was mixed. The hydraulic retention time (HRT) of net flow was controlled at 72 h. After 12 days of operation, the microorganisms in the reactor was gradually acclimatized to the fed wastewater, at which point the filler was completely covered by microorganisms, and the effluent COD approached steady removal. The effluent from the anaerobic biofilm reactor was supplied to the aerobic biofilm reactor to start up the latter reactor. Inoculation sludge was collected from the pond at the cyclic activated sludge technology (CAST) of a wastewater treatment plant of the Petrochemical Industries Co. in Liaoning province, China. The reactor temperature was controlled at 30–35 °C. The 48 h after inoculation, the inlet and outlet
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were shut down, and the range of the DO was controlled from 3.5 mg/L to 4.5 mg/L (Zhao et al., 2011). In the reactors of anaerobic and aerobic, ranges of DO were 0.681.39 mg/L and under 0.13 mg/L, respectively. Afterward HRT was controlled at 50 h and then reduced to 36 h until the effluent COD approached steady removal. Then, the anaerobic biofilm reactor outlet and aerobic biofilm reactor inlet were connected to form a gravity flow. Thus, the A/O biofilm reactor was started successfully. 2.2 Water analysis The influent and effluent samples from each reactor were collected daily and analyzed immediately. ORP and pH were monitored using a portable device (WTW, Germany) during the experiment. Electric conductivity was monitored using a portable device (HACH LA-EC20, USA). In anaerobic and aerobic reactors, the ranges of DO were 0.68–1.39 mg/L and < 0.13 mg/L, respectively. DO was monitored using an online DO analyzer (Sungee LD532, China) with a fluorescent DO detection probe. The DO analyzer controller was connected to an air pump to control the DO in the aerobic biofilm reactor set stable in the range of 3.5–4.5 mg/L. The COD, five-day biochemical oxygen demand (BOD5), petroleum, TN, ammonia nitrogen (NH4 +-N), nitrate nitrogen (NO3−-N), volatile phenol, and sulfide contents were determined by following the standard methods (State Environmental Protection Administration of China, 2002). Each measurement was performed in triplicate. The average of the three parallel measurements was reported. Each parameter was detected for 30 days, and numerical ranges were obtained. 2.3 DNA extraction and microbial diversity analysis Five samples were labeled as A2, A4, A11, P1, and O1. A2, A4, and A11 were collected from the anaerobic biofilm, located at sampling ports 2, 4, and 11. P1 was a
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granule sludge sample collected from sampling port 9. O1 was sludge collected from the aerobic biofilm. The DNA of these samples was extracted by E.Z.N.A. Soil DNA Kit (OMEGA, USA).The DNA samples were sequenced by Hiseq 2500 PE 250 Illumina high throughput sequencing platform. Bacterial sequencing primers were Bac349f (5′-AGGCAGCAGTDRGGAAT-3′) and Uni806r (5′GGACTACYVGGGTATCTAAT-3′), and target region was V3+V4. Archaea sequencing primers were Arc113f (5′-ACKGCTSAGTAACACGTGG-3′) and Arc520r (5′-TACCGCGGCKGCTGGCA-3′), and target region was V2+V3. 2.4 Construction and verification of the prediction model Box-Behnken method was used to design the response surface optimal prediction model (Zhao et al., 2016). After approximately 200 days of operation, the influent COD/TN (C/N), reflux ratio, and HRT were selected as independent variables. The response values were the efficiencies of COD and TN removal, which were labeled as ηCOD and ηTN, respectively. The experimental program was designed as 3 factors, 2 levels, and a total of 17 groups of experiments. At least 24 sets of experimental data were achieved in each group, and ηCOD and ηTN were the average values of these data. Independent variable encoding methods were performed using the following formula: Xi = (xi – x0) /∆x (1), where Xi is the encoding value of independent variable, xi is the actual value of the independent variable, x0 is the actual value of independent variables at the experimental center, and ∆x is the step size of independent variables. Design-Expert was used to design a series of experimental group, data analysis, and analysis of interaction between each factor. 3. Results and discussion
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3.1 Evaluation of the performance of the A/O reflux process with the biofilm reactor 3.1.1 Experimental treatment of heavy oil refinery wastewater The anaerobic and aerobic biofilm reactors were started up for three weeks. Then, the two reactors were connected, and reflux flow was started. The reflux ratio was gradually increased from 1 to 4.5, while the influent was fixed at 198 mL/h. TN removal increased with increasing reflux ratio. The A/O reflux process was operated for 30 days when reflux ratio reached 4.5 (Fig. 2a). The operational result showed that the TN of effluent was less than 15 mg/L which satisfied the requirement described in GB18918-2002 “Discharge standard of pollutants for municipal wastewater treatment plant” of China. Moreover, COD and petroleum removal efficiencies were more than 95% and 98%, respectively (Figs. 2b and 2c). In anaerobic and aerobic reactors, the pH ranges of effluent were 7.2–8.1 and 7.3–8.6, respectively. These effluent pH ranges both met the requirement described in GB18918-2002. Therefore, the pH values of the wastewater treatment process were not controlled. Compared with the original wastewater, the final effluent was clear and transparent and without smell, suspension, and oil. The influent of reactor was heavy oil refinery wastewater without pretreatment. Thus, the TN, COD, and oil content in wastewater fluctuates in daily wastewater discharge. The TN of influent fluctuated greatly within 9–12 days, and the range of fluctuation was 37.2–52.3 mg/L (Fig 2a). However, the fluctuation ranges of the TN in the effluent of anaerobic and aerobic reactor were 10.1–12.8 and 9.21–10.0 mg/L, respectively. Compared with influent, the TN of the effluent of the two reactors was stable. The process could withstand the impact of fluctuations in TN in wastewater. The COD and oil content of influent also fluctuated, but the effluent of the two reactors was stable (Figs. 2b and 2c). For the fluctuation of the contaminant concentration in the
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influent, the stable reflux water provided by aerobic reactor was mixed with influent in the anaerobic reactor. This mixture could reduce the impact of the fluctuation of pollutants in the influent on the reactor. Therefore, it had stable effect and good impact resistance for wastewater treatment. 3.1.2 Changes in the ORP in anaerobic reactor under different influent upflow velocities The anaerobic environment in the anaerobic reactor would be destroyed gradually when reflux ratio is improved. Methanogens showed a good activity, while ORP was lower than −150 mV in anaerobic environment. Influent rising velocity affected the change in ORP in the anaerobic biofilm reactor. The rising velocity of the influent in the reactor could be changed by adjusting the HRT. In this experiment, the reflux ratio was fixed at 4, and HRT was adjusted to 28, 36, 44, 52, and 60 h (corresponding increases in influent velocities were 6.5, 5.1, 4.2, 3.5, and 3.1 cm/h), respectively. Under each condition, the reactor was operating for more than 12 days, and the ORPs of the water samples collected from different heights of the reactor were tested. Along with the direction of water flow, the maximum ORPs of the sampling ports from No. 7 to No. 11 (approximately 45% of the effective volume of the reactor) were still lower than −150 mV (Fig. 3). This result indicates that the anaerobic biofilm reactor could provide a good anaerobic environment for methanogens to ensure high removal efficiency of COD. The ORPs of sampling ports from Nos. 1 to 11 increased first and then decreased. Hydrolysis acidification reaction mainly occurred at sampling port Nos. 1 to 3. In an anaerobic environment, hydrolysis acidification is an oxidation process for organic compounds. ORP would increase with increasing oxide. Thus, the ORP was increased first. With uprising of water, methane production began to
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occur above the No. 3 sampling port. Methane production is a reduction process for acetic acid and other organic compounds containing oxygen. ORP would gradually decrease with decreasing oxidation substances in wastewater. Therefore, the curve began to turn, and ORP began to decline. ORP gradually declined, and the curve gradually decreased at the sampling port Nos. 9 to 11. This phenomenon was mainly caused CO2 fixation by autotrophic sulfur-oxidizing bacteria. Thus, the watercontaining organic compounds in water increased, and this content would be described in detail below. 3.2 Division of functional areas in the anaerobic biofilm reactor Stable inflow would form an uprising plug flow in the reactor. Organic matter in wastewater was degraded into volatile fatty acid (VFA), alcohols, and other substances by hydrolysis acidification and acetic acid production, resulting in remarkably increased total VFAs. COD decreased because of CO2 production and organic matter adsorption of the biofilm. Thus, an opposite relationship exists between the change in VFAs and change in COD in the areas of hydrolysis acidification and acetic acid production. With uprising water, acetic acid, methanol, and hydrogen compounds in the wastewater could be used by methanogens to produce methane. At this time, VFAs and COD both decreased. A similar relationship exists between changes in VFAs and COD in the methane production area. Thus, the functional areas are divided according to the changing trend in the CODs and VFAs of the water samples at the different heights of the anaerobic reactor (Li et al., 2014). The coverages of the various functional areas in the anaerobic biofilm reactor under different reflux ratios are shown in Fig. 4. The COD and TN of the influent of anaerobic reactor were in the ranges of 600–700 and 30–45 mg/L, respectively. Reflux
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ratio was adjusted into 0, 2, 3, and 4, while the HRT of net flow of anaerobic reactor was fixed at 68 h. The corresponding rising velocities were 2.9, 8.8, 11.8, and 14.7 cm/h. Under each reflux ratio, the internal environment of anaerobic reactor was stable after more than 30 days of operation. The CODs and VFAs of wastewater samples which were collected from different heights of the reactor were detected to divide the functional areas in anaerobic biofilm. The increase in water velocity was gradual, so the influence of disturbance could be neglected. With increasing reflux ratio, the coverage of the various functional areas in the anaerobic biofilm also changed, further affecting the water quality of the effluent. As reflux ratio increased, the coverage rate of area (1) gradually increased (i.e., 25%, 33%, 42%, and 50%, respectively), area (2) gradually decreased (i.e., 75%, 67%, 58%, and 50%, respectively), and coverage rate of area (3) included in area (2) were gradually decreased (i.e., 50%, 42%, 25% and 17%, respectively) (Fig. 4). Thus, the effect of reflux ratio at the coverage rate of different functional areas in the anaerobic biofilm reactor was remarkable. Improving the reflux ratio would increase the amount of reflux water with dissolved high oxygen to increase the impact on anaerobic environment. The DO could be used in hydrolysis acidification which could be operated under anoxic conditions. Thus, the hydrolysis acidification area would increase as reflux ratio improved, and the impact of the methane production area would be compensated. The area (2) in Fig. 4a is the largest area in the four pictures. However, the effluent COD (148 mg/L) in this area was not the lowest, although a large methane production area indicates a large biomass of methanogens. A large methane production area could not improve COD removal. Various functional areas existed in order in the anaerobic biofilm. Methanogenesis in the methane production area was dependent on
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the product from the hydrolysis acidification area. When the VFAs changed slowly, the change in COD showed a similar trend. This result indicates that the main type of methanogen in the biofilm used VFAs. The concentration of VFAs decreased rapidly during the initial stage of methane production and maintained at low level. Thus, the initial stage of methane production had the highest methanogenic activity, and the rest was limited by the low VFA concentrations. The increase in the reflux ratio improved the dilution times of the influent and reduced toxicity. Additionally the more reflux water, the more DO was carried into the reactor. Consequently, a large number of facultative bacteria multiplied, and area (1) expanded. Thus, the degree of hydrolysis acidification improved, and the VFAs increased. The available VFAs increased, resulting in increased highly active region within the methane production area but reduced the COD of effluent. However, the maximum amount of VFAs did not increase with increasing reflux ratio (Fig. 4). The change in the microbial community on the biofilm had hysteresis, although the reactor has been operating for 30 days under each condition. Methane production already occurred in the methane producing area as shown in Figs. 4b, 4c, and 4d, and part of VFAs had been consumed. These results will not affect the accuracy of the experimental results, because this experiment focused on the mechanism. Thus, improving the efficiency of COD removal with a biofilm reactor is important for the appropriate expansion of the hydrolysis acidification and acetic acid production area. 3.3 Analysis of microbial community diversity Hiseq 2500 PE 250 Illumina high throughput sequencing platform was performed to reveal the microbial diversity and distribution in the five zones of biofilm
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using A/O process. The diversity estimators of the Shannon index for samples from the hydrolysis acidification and acetic acid areas (A2), transition zone between the hydrolysis acidification and acetic acid areas and methane-producing area (A4), methane production area (A11), granular sludge in methane-producing area (P1), and aerobic biofilm (O1) were 8.21, 8.50, 6.49, 7.96, and 7.58, respectively (Table S1). The area for hydrolysis acidification and production of acetic acid area showed the maximum diversity in the bacterial community. The hydrolysis acidification and acetic acid production areas belong to the transition area from aerobic to anaerobic and had rich substrate, leading to the fast growth of various microbes in this area. With the uprising of water, organic species was gradually reduced and DO consumed, and microorganisms were screened more and more strictly. Thus, the diversity of microorganisms decreased. The diversity in the microorganisms of the five samples was ranked as A2 > A4 > P1 > O11 > A11. The microbial communities of the five samples of biofilm significantly differed at the phylum level (Fig. 5). Comparison among the five sample communities indicated that Proteobacteria existed in both anaerobic and aerobic biofilms and was the most abundant in the aerobic environment (A2, 43.03%; A4, 29.61%; P1, 33.62%; A11, 16.93%; and O1, 54.62%). The Chloroflexi was more abundant at the hydrolysis acidification area, but few in the aerobic environment (A2, 20.07%; A4, 23.54%; P1, 14.25%; A11, 7.90%; and O1, 0.39%). The microbial community at the COD recovery area (A11) microcosm was found to be dominated by Chlorobi (48.56%), which was low in other samples (A2, 1.28%; A4, 17.78%; P1, 3.53%; and O1, 0.67%). By contrast, the abundance of Bacteroidetes in anaerobic showed a decreasing trend (A2, 6.23%; A4, 5.82%; P1, 2.60%; and A11, 1.65%).
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In the aerobic biofilm reactor, the air lift inner loop flow guiding tube was equipped to produce a circulating flow. Therefore, aerobic biofilm was not stratified along the vertical direction. The top three most abundant microorganisms of O1 were Proteobacteria, Nitrospirae, and Acidobacteria, with abundances of 54.75%, 14.6%, and 9.85%, respectively (Fig. 5b). Most of these microorganisms were facultative anaerobic and aerobic bacteria. Microbial community of archaea was not complex (Fig.5b). Euryarchaeota was always the predominant archaea, with abundances in A2, A4, P1, and A11 at 98.82%, 96.34%, 87.32% and 90.37%, respectively. The richness of the archaea gradually increased, while the abundance of Crenarchaeota, Thaumarchaeota, and uncultured archaea gradually increased in A2, A4, P1, and A11. These bacteria were mainly methane-producing bacteria. 3.4 Functional microbial groups in the wastewater treatment by A/O process During wastewater treatment, the removal of pollutants was accomplished by the cooperation of all functional microbial groups. A summarized overview of the microbial diversity results facilitated the postulation of a probable mechanism model to better elucidate the interplay of microbial groups during wastewater treatment (Fig. 6). Microbial diversity indicated the presence of three kinds of pollutant degradation processes (i.e., petroleum and refractory organics degradation, other organic pollutant degradation, and TN removal by denitrification) in the samples supported by required functional microbial groups. The functional microbial groups of methanogenic archaea (A2, 1.98%; A4, 0.94%; P1, 9.56%; A11, 0.82%; and O1, 0.24%) and syntrophic bacteria (A2, 5.05%; A4, 6.39%; P1, 9.65%; A11, 3.92%; and O1, 0.14%) were found in the anaerobic
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biofilm reactor. These microorganisms played an important role in the removal of petroleum and refractory organic matters. The combination of methanogenic archaea and syntrophic bacteria resulted in extreme anaerobic metabolism (Stams & Plugge, 2009). The electron transfer between the synergism bodies could reduce the energy needed for the hydrolysis of pollutants (Shen et al., 2016). This process could degrade petroleum and refractory organic matters to directly produce methane through the sharing of low energy. Further analysis of sequencing results showed that more than half of syntrophic bacteria evidently reduced sulfate. Methanogenic process was also a reductive reaction. A competition for electron exists between syntrophic bacteria with function of sulfate reduction and methanogens (Lu et al., 2016). Therefore, only syntrophic bacteria that do not reduce sulfate could form syntrophic bacteria union body with methanogenic archaea. Syntrophic bacteria that can reduce sulfate could unite the body of syntrophic bacteria with hydrolysis acidification bacteria. The process of hydrolysis and acidification for organic compounds was oxidation. In an anaerobic environment, these processes could use sulfate and elemental sulfur as electron acceptor and organic compounds as electron donor to produce hydrogen in the forms of NADH or FADH2 to reduce the activation energy required to degrade refractory organic compounds (Sousa et al., 2009). Hydrolysis acidification and degradation of the syntrophic bacteria union body would produce VFAs and other low-molecular weight organic matters to enhance the biodegradability of wastewater (Narihiro & Sekiguchi, 2007). H2S produced by the effect of sulfate reduction in anaerobic reactor produced smelly effluent. Chlorobiaceae (A2, 0%; A4, 9.09%; P1, 0.68%; A11, 18.67%; O1, 0%), which are non-oxygen photosynthetic sulfur-oxidizing bacteria, were found in the
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COD recovery area of anaerobic environment. These bacteria could reduce the concentration of H2S in the effluent from the anaerobic reactor, thereby reducing the smell during wastewater treatment (Hatamoto et al., 2016). Chlorobiaceae used sulfide and sulfur as electron donors to fix CO2 to simple organic compounds, mainly engaged in anoxygenic photosynthesis (Gregersen et al., 2011). Thus, a COD recovery area emerged because of the CO2 fixing effect of non-oxygen photosynthetic sulfur oxidizing bacteria. The COD recovery area is very important to wastewater treatment. Although it slightly reduced COD removal efficiency, Chlorobiaceae removed H2S and S2 which made the effluent smelly. The reasonable existence of this sulfur oxidation made the anaerobic biofilm form a perfect anaerobic micro ecosystem. Denitrification was one of important functions of the A/O reflux process. NH4+ N entered into the aerobic reactor to produce NO3−-N by nitrosation and nitrification. NO3−-N was returned to the anaerobic reactor to achieve denitrification. Nitrosomonadaceae, Nitrospiraceae, and Rhodocyclaceae were the most abundant in the whole TN removal process, similar results were reported by (Yi et al., 2016). Few studies have reported on the function of denitrification in the syntrophic bacteria union body. However, denitrification was a reductive reaction that can possibly form syntrophic bacteria union body with hydrolysis and acidification bacteria in organic matter degradation. 3.5 Analysis and validation of prediction model 3.5.1 Construction of prediction model The statistical significance of an empirical model with less experimental data can be established based on the response surface method, which is an effective
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multivariate analysis. The experimental design with actual and predicted values is shown in Table S2. The quadratic model was established based on the experimental data, and the coefficients, with statistical significance to all response values, were obtained by polynomial regression analysis. Encoded values were used as independent variables in the quadratic model. After manual fitting (removal of model terms with value “Prob > F” greater than 0.05), the final model equations in terms of code factors were as follows: ηCOD = 88.19 + 1.08X1 + 3.69X2 – 1.58X3 – 0.75X1X3 – 1.57X2X3 – 0.98X2 2– 4.58 X32 (2), ηTN = 76.78 – 0.99X1 + 4.04X2 + 0.90X3 – 1.70X12 – 1.43X32 (3), Within the two models, X1 is C/N, X2 is the reflow ratio, and X3 is HRT. Analysis results of model (2): The F-value of 709.23 implied that the model was significant. The “lack of fit Fvalue” of 1.90 implied that the lack of fit was not significant relative to the pure error. P-values were less than 0.0001. R2 values were 0.9982, very close to 1. Model (2) could be used to navigate the design space. In addition, the effects on ηCOD, X1, X2, X3, X12, X1X3, X2X3, X22, and X32 were extremely significant (P < 0.01). The effect of the independent variables on ηCOD could be ranked as X2 > X3 > X1, as observed from the single factor coefficient. Interaction effects on ηCOD could be ranked as X2X3 > X1X3. The ηCOD of X1, X2, and X3 partial derivatives are as follows: ηCOD' X1 (X1, X2, X3) = 1.08 – 0.75X3 (4), ηCOD' X2 (X1, X2, X3) = 3.69 – 1.57X3 – 1.96X2 (5), ηCOD' X3 (X1, X2, X3) = –1.58 – 0.75X1 – 1.57X2 – 9.16X3 (6).
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The coding values X1, X2, and X3 belong to (–1, 1). Thus, 0.33 < equation (4) < 1.83, which is always greater than 0. ηCOD improved with increasing influent C/N when the reflux ratio and HRT were fixed. Because equation (5) has variable X2, the calculated second derivative was ηCOD'' X2 (X1, X2, X3) = –1.96 < 0. Thus, equation (5) monotonically decreased. Based on the range of independent variables, 0.16 ≤ equation (5) ≤ 7.19 is always greater than 0. Therefore, ηCOD improved with increasing reflux ratio when the influent C/N and HRT were fixed. Equation (6) was treated in the same manner as equation (5). Because ηCOD'' X3 (X1, X2, X3) = –9.16 < 0, equation (6) monotonically decreased. Based on the range of independent variables, –13.06 ≤ equation (6) ≤ 9.9, whereas equation (6) = 0, and X3 = 0.17 – 0.08X1 + 0.17X2 (7). At this point, model (2) had a maximum or minimum value. Because of ηCOD'' X3 (X1, X2, X3) = –9.16 < 0, equation (2) was a convex function. Thus, equation (7) was established, and ηCOD had a maximum value. Therefore, ηCOD improved first and then decreased with increasing HRT when the influent C/N and reflux ratio were fixed. Analysis results of model (3): The F-value of 238.06 implied that the model was significant. The “lack of fit Fvalue” of 1.16 implied that the lack of fit was not significant relative to the pure error. P-values were less than 0.0001. R2 values were 0.9930, very close to 1. Model (3) could be used to navigate the design space. The effects on ηTN, X1, X2, X3, X1 2and X3 2 were extremely significant (P < 0.01). The effect of independent variables on ηTN was X2 > X1 > X3 as observed from single factor coefficient. The ηTN of X1, X2, X3 partial derivatives are as follows: ηTN' X1 (X1, X2, X3) = –0.99 – 3.4X1 (8),
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ηTN' X2 (X1, X2, X3) = 4.04 (9), ηTN' X3 (X1, X2, X3) = 0.90 – 2.86X3 (10), The coding values X1, X2, and X3 belong to (–1, 1). Thus, –1 ≤ X3 < –0.29, equation (8) > 0, and –0.29 < X3 ≤ 1, equation (8) < 0. ηTN improved first and then decreased with the increase of influent C/N when the reflux ratio and HRT were fixed. Equation (9) = 4.04, which is always greater than 0. Therefore, ηTN improved with the increase of reflux ratio when the influent C/N and HRT were fixed. Equation (10) indicated that –1 ≤ X3 < 0.31, equation (10) > 0, and 0.31 < X3 ≤ 1, equation (10) < 0. Therefore, ηTN improved first and then decreased with increasing HRT when the influent C/N and reflux ratio were fixed. 5.2 Validation of prediction model The experimental conditions were optimized by response surface optimization model to obtain appropriate ηCOD and ηTN within the range of experimental design. Three sets of experimental conditions were selected to verify the reliability of the model. In the first set of experimental conditions, the maximum ηCOD predicted can be obtained. In the second set, the maximum ηTN predicted can be obtained. In the third set, moderate values of ηCOD and ηTN were both obtained. Validation results and model predictions are shown in Table 2. The deviation of ηCOD and ηTN between prediction and actual values were both less than 5% (Table 2). Within the scope of experimental design, the model could play a very good role in optimizing the experimental conditions and predicting experimental results. The biofilm reactor with the A/O reflux process could be used to effectively treat heavy oil refinery wastewater containing 70.5–95.8 mg/L petroleum. COD and TN
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removal efficiencies reached 93.2% and 82.8%, respectively. The anaerobic reactor was responsible for 95% of the total COD removal. 4. Conclusion The large height–diameter ratio of the anaerobic biofilm reactor with soft filler guaranteed that anaerobic environment was not destroyed in oily wastewater treatment, although reflux ratio reached 4.5. Different functional areas were evident in the anaerobic biofilm reactor, and COD removal increased because of the expansions in the hydrolysis acidification and acetic acid production area. Syntrophic bacteria union body was beneficial in the degradation of refractory organics. The prediction model was highly consistent with experimental results, providing reference for the industrial application of the proposed process. Acknowledgements This work was funded by the National Natural Science Foundation of China (No. 51474223, 51634008 and 41403068) and China Petroleum Science and Technology Major Project of Low Carbon Emission (No. 2016E-12). The authors are grateful to State Key Laboratory of Heavy Oil Processing of China for their technical assistance and to Liaohe Petrochemical Company for field and logistical assistance during this work.
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List of Tables
Table 1 Characteristics of wastewater of heavy oil processing.
Table 2 Experimental and predicted values for ηCOD and ηTN in the validation experiments
Figure Captions
Fig. 1 A simple schematic diagram of the field-scale A/O biofilm reactor reflux process. (1) Raw water storage, (2) Thermostatic water bath, (3) Peristaltic pump, (4) Anaerobic biofilm reactor, (5) Aerobic biofilm reactor, (6) Air Pump, (7) Discharge water storage
Fig. 2 The changes of content and removal efficiency of TN (a), COD (b) and Petrelom (c) for the effluent and influent over time in A/O reflux process at 4.5 reflux ratio
Fig. 3 Changes of ORP in anaerobic reactor under different HRT.
Fig. 4 Coverages of the various functional areas in the anaerobic biofilm reactor under different reflux ratios. Reflux ratio of (a), (b), (c) and (d) was 0, 2, 3 and 4, respectively. (1) Hydrolysis acidification and production of acetic acid area, (2) Methane production area, (3) COD recovery area
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Fig. 5 Distribution of bacterial (a) and archaeal (b) groups in five samples at phylum level.
Fig. 6 Mechanism model depicting the interplay of functional microbial groups in heavy oil refinery wastewater treatment by A/O process. The labeled species were the most abundant in each functional microbial group. In anaerobic area, below the dotted line was hydrolysis acidification and production of acetic acid area, and above it was methane producing area. (1) Hydrolysis acidification bacteria, (2) Syntrophic bacteria with function of sulfate reduction + hydrolysis acidification bacteria, (3) Non-oxygen photosynthetic sulfur oxidizing bacteria, (4)Syntrophic bacteria without function of sulfate reduction + methanogens, (5) Methanogens, (6) Aerobic heterotrophic bacteria, (7) Nitrite bacteria, (8) Nitrifying bacteria, (9) Denitrification bacteria.
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Fig. 1 A simple schematic diagram of the field-scale A/O biofilm reactor reflux process. (1) Raw water storage, (2) Thermostatic water bath, (3) Peristaltic pump, (4) Anaerobic biofilm reactor, (5) Aerobic biofilm reactor, (6) Air Pump, (7) Discharge water storage.
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Fig. 2 The changes of content and removal efficiency of TN (a), COD (b) and Petrelom (c) for the effluent and influent over time in A/O reflux process at 4.5 reflux ratio.
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Fig. 3 Changes of ORP in anaerobic reactor under different HRT.
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Fig. 4 Coverages of the various functional areas in the anaerobic biofilm reactor under different reflux ratios. Reflux ratio of (a), (b), (c) and (d) was 0, 2, 3 and 4, respectively. (1) Hydrolysis acidification and production of acetic acid area, (2) Methane production area, (3) COD recovery area.
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Fig. 5 Distribution of bacterial (a) and archaeal (b) groups in five samples at phylum level
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Fig. 6 Mechanism model depicting the interplay of functional microbial groups in heavy oil refinery wastewater treatment by A/O process. The labeled species were the most abundant in each functional microbial group. In anaerobic area, below the dotted line was hydrolysis acidification and production of acetic acid area, and above it was methane producing area. (1) Hydrolysis acidification bacteria, (2) Syntrophic bacteria with function of sulfate reduction + hydrolysis acidification bacteria, (3) Non-oxygen photosynthetic sulfur oxidizing bacteria, (4)Syntrophic bacteria without function of sulfate reduction + methanogens, (5) Methanogens, (6) Aerobic heterotrophic bacteria, (7) Nitrite bacteria, (8) Nitrifying bacteria, (9) Denitrification bacteria.
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Table 1 Characteristics of wastewater of heavy oil processing Characteristic pa-
Characteristic paRange
Range
rameters
rameters
COD
650–1150 (mg/L)
B/C
0.4–0.5
Petroleum
70.5–95.8 (mg/L)
ORP
50–80 (mV)
TN
35–70 (mg/L)
NH4 +-N
30–58 (mg/L)
NO3--N
0.1–0.6 (mg/L)
pH
7.5–8.8
2–2.1 (mS/cm)
Volatile phenol
20–28.2 (mg/L)
Sulfide
≤ 2 (mg/L)
Suspended matter
73–99 (mg/L)
Diotoxicity
High
Electric conductivity
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Table 2 Experimental and predicted values for ηCOD and ηTN in the validation experiments Level Reflow
No.
Actual
Predicted
ηCOD
ηCOD
(%)
(%)
HRT (h) C/N (X1)
ratio
Actual
(X3) (X2)
Predicted
ηTN (%) ηTN (%)
1
23
4.5
52.3
93.2
93.8
78.5
79.0
2
19.1
4.5
67.9
89.3
88.0
82.8
83.4
3
21
3
70
86.9
85.3
77.3
76.2
Note: The datas of actual value in table were the mean of three repeated experiments.
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Research Highlights > Anaerobic–aerobic process was used to treat oily wastewater without pretreatment. > Large height–diameter ratio reactor with soft filler could enhance reflux ratio. > Rational functional areas distribution in the reactor increased pollutants removal. > Syntrophic bacteria union body could degrade petroleum and refractory organics. > Prediction model provided a new operational management to treat wastewater.
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S0960-8524(17)30521-7 http://dx.doi.org/10.1016/j.biortech.2017.04.033 BITE 17928
To appear in:
Bioresource Technology
Received Date: Revised Date: Accepted Date:
8 February 2017 5 April 2017 8 April 2017
Please cite this article as: Li, J., Sun, S., Yan, P., Fang, L., Yu, Y., Xiang, Y., Wang, D., Gong, Y., Gong, Y., Zhang, Z., Microbial communities in the functional areas of a biofilm reactor with anaerobic–aerobic process for oily wastewater treatment, Bioresource Technology (2017), doi: http://dx.doi.org/10.1016/j.biortech.2017.04.033
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Microbial communities in the functional areas of a biofilm reactor with anaerobic– aerobic process for oily wastewater treatment Jianhua Lia, Shanshan Suna*, Ping Yanb, Li Fangc, Yang Yuc, Yangdong Xiangc, Di Wanga, Yejing Gonga, Yanjun Gonga, Zhongzhi Zhanga
a
State Key Laboratory of Heavy Oil Processing, College of Chemical Engineering,
China University of Petroleum, Beijing 102249, China b
Dalian Petrochemical Branch Company, PetroChina, Dalian 116000, China
c
China National Petroleum Corporation Liaohe Petrochemical Company , Panjin
124000, China.
*Corresponding author: Tel.: +86 10 89734284 Fax: +86 10 89734284 E-mail: [email protected](S.Sun)
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Abstract Microbial communities in the functional areas of biofilm reactors with large height–diameter ratio using the anaerobic-aerobic (A/O) reflux process was investigated to treat heavy oil refinery wastewater without pretreatment. In the process, chemical oxygen demand (COD) and total nitrogen (TN) removal reached 93.2% and 82.8%, and the anaerobic biofilm reactor was responsible for 95% and 99%, respectively. Areas for hydrolysis acidification and acetic acid production, methane production, and COD recovery were obvious in the anaerobic reactor. Among all areas, area for hydrolysis acidification and acetic acid production was the key factor to improve COD removal efficiency. High throughput sequencing of 16S rDNA gene showed that the native community was mainly composed of functional groups for hydrocarbon degradation, syntrophic bacteria union body, methanogenesis, nitrification, denitrification, and sulfate reduction. The deviations between predicted values and actual COD and TN removal were less than 5% in the optimal prediction model.
Keywords: Wastewater treatment, Biofilm reactor, Microbial community diversity, COD removal, Optimal prediction model
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1. Introduction Heavy oil refinery wastewater contains high amounts of organic pollutants. This wastewater contain low concentrations of several hydrocarbon substances, such as oil, emulsified oil, and dissolved and dispersed oil, which are unrecoverable (Ji et al., 2009; Lu et al., 2009). Traditional treatment of heavy oil refinery wastewater is time consuming and expensive. The traditional anaerobic-aerobic (A/O) technology cannot be directly used to process this water when the concentration of petroleum or oil is more than 20 mg/L. For example, oil in this wastewater is removed by first using a physicalchemical method, such as oil separation and air floatation, and then anaerobic and aerobic biodegradation (Liu et al., 2013; Zhao et al., 2011). The waste produced by flocculants and emulsion breaker used in the physical-chemical process will cause second pollution (Lasindrang et al., 2015; Qin et al., 2007). Many provinces in China have implemented more stringent regulatory standards to discharge wastewater. Resulting problems would be prevented if the efficiency of biological reactor treatment and organic loading of petroleum or oil would be enhanced. Biological biofilm process is one of the main technologies of wastewater treatment. This process presents great development potential (Diya’uddeen et al., 2011; Ma et al., 2009; Shokrollahzadeh et al., 2008). The anaerobic biofilm reactor is still the core technology for wastewater treatment because of its low operational cost, high volume load, less sludge, biological detoxification, improvement of wastewater biodegradability, and production of methane as clean energy, among others (Zhang et al., 2012; Zimmerman et al., 2009). The water from the inlet to the outlet, given that an up-flow feeding pattern is adopted in an anaerobic reactor, undergoes hydrolysis, acidification, and methanogenesis. These processes occur in different stages of
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anaerobic biofilm formation, because these processes required different reaction substrates and dissolved oxygen (DO) concentrations (Escudie et al., 2011; Fakhru'lRazi et al., 2010). Thus, a biofilm is divided into several functional areas. Each functional area plays an important role in the efficiency of wastewater treatment of the anaerobic biofilm reactor. The A/O process is composed of aerobic and anaerobic reactors. Wastewater treated by an anaerobic reactor can be degraded further by an aerobic reactor (Gannoun et al., 2016; Guo et al., 2009; Haritash & Kaushik, 2009). Ammonia is oxidized to nitrate in an aerobic reactor, and the nitrification liquid is refluxed into an anaerobic reactor to realize total nitrogen (TN) removal by denitrification (Murali et al., 2013; Reddy et al., 2011). The nitrification liquid can be used to dilute the influent of an anaerobic reactor such that the impact of the biological membrane from highconcentration petroleum or oil could be reduced (Jiao et al., 2011; Rizzo, 2011). Therefore, enhancing the efficiency of wastewater treatment by improving the reflux ratio is beneficial (Guo et al., 2014; Reddy et al., 2011). However, the reflux ratio of the A/O reflux process is generally not too high, or the environment of the anaerobic reactor would be destroyed if the reflux ratio is further increased. In an anaerobic reactor, methanogenesis can be conducted smoothly when the oxidation-reduction potential (ORP) is lower than −150 mV. The efficiency of wastewater treatment is improved by not destroying the anaerobic environment to improve the reflux ratio (Song et al., 2011). For a higher reflux ratio, an anoxic reactor, namely, anaerobic-anoxic-aerobic Process (A/A/O), would be used (Gao et al., 2014; Wang et al., 2012), but such requirement increase the cost of wastewater treatment.
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This study focused on the microbial communities in the functional areas of a biofilm reactor without pretreatment A/O process to treat heavy oil refinery wastewater containing petroleum (70.5–95.8mg/L). The no-pretreatment A/O process is established to resolve the problems of time-consuming treatment process and secondary pollution produced by flocculant used in the chemical oil removal unit. The division of the functional areas in a biofilm and microbial diversity in these areas provided important basis for the study of the degradation mechanism of the proposed process. The existence of syntrophic bacteria facilitated the degradation of petroleum and refractory organic compounds. The influence of multiple factors on the efficiencies of chemical oxygen demand (COD) and TN removal were investigated using the optimal prediction model, providing a reference for the industrial application of the proposed process. 2. Materials and methods 2.1 Wastewater treatment by A/O process with biofilm reactor 2.1.1 Wastewater characteristics Heavy oil refinery wastewater was collected from the Petrochemical Industries Co. in Liaoning province, China. Sampling site was located at the inlet of wastewater treatment plants before the physical-chemical process. Wastewater characteristics are shown in Table 1. 2.1.2 Experimental set-up Experiments were performed in a lab-scale A/O reflux process (Fig. 1), which consisted of anaerobic and aerobic biofilm reactors. The A/O reflux setup was made of Plexiglas with a total liquid volume of 28.5 L (anaerobic biofilm reactor: 19 L, 2 m high and with height-to-diameter ratio of 20; aerobic biofilm reactor: 9.5 L, 1 m high and with height-to-diameter ratio of 15). Soft carrier, with 1.3 m long hydroformylation
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fiber (Fig.1S), was placed in the anaerobic biofilm reactor with a packing ratio of 30% (vol/vol). The aerobic biofilm reactor was filled with elastic filler with packing ratio of 30%. An inner loop flow guide tube was installed at the middle of the aerobic reactor. Aeration devices were fixed on the bottom inner loop flow guide tube. Wastewater was first pumped into the anaerobic biofilm reactor from a storage tank and then flowed into the aerobic biofilm reactor and the effluent reflux into the anaerobic biofilm reactor according a certain reflux ratio. COD and TN were removed simultaneously in the anaerobic biofilm reactor, and the aerobic biofilm reactor was used to further remove COD and nitrify ammonia nitrogen. 2.1.3 Reactor start-up and operation The anaerobic biofilm reactor was started up first. After being seeded with sludge collected from the hydrolysis acidification tank of a wastewater treatment plant in Beijing, China. To promote the growth of microorganism, glucose solution (1.33 g/L) and wastewater were separately injected into the reactor with two identical metering pumps at the flow rates of 6.9 mL/h and 184.7 mL/h. Subsequently, tee pipe fitting was mixed. The hydraulic retention time (HRT) of net flow was controlled at 72 h. After 12 days of operation, the microorganisms in the reactor was gradually acclimatized to the fed wastewater, at which point the filler was completely covered by microorganisms, and the effluent COD approached steady removal. The effluent from the anaerobic biofilm reactor was supplied to the aerobic biofilm reactor to start up the latter reactor. Inoculation sludge was collected from the pond at the cyclic activated sludge technology (CAST) of a wastewater treatment plant of the Petrochemical Industries Co. in Liaoning province, China. The reactor temperature was controlled at 30–35 °C. The 48 h after inoculation, the inlet and outlet
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were shut down, and the range of the DO was controlled from 3.5 mg/L to 4.5 mg/L (Zhao et al., 2011). In the reactors of anaerobic and aerobic, ranges of DO were 0.681.39 mg/L and under 0.13 mg/L, respectively. Afterward HRT was controlled at 50 h and then reduced to 36 h until the effluent COD approached steady removal. Then, the anaerobic biofilm reactor outlet and aerobic biofilm reactor inlet were connected to form a gravity flow. Thus, the A/O biofilm reactor was started successfully. 2.2 Water analysis The influent and effluent samples from each reactor were collected daily and analyzed immediately. ORP and pH were monitored using a portable device (WTW, Germany) during the experiment. Electric conductivity was monitored using a portable device (HACH LA-EC20, USA). In anaerobic and aerobic reactors, the ranges of DO were 0.68–1.39 mg/L and < 0.13 mg/L, respectively. DO was monitored using an online DO analyzer (Sungee LD532, China) with a fluorescent DO detection probe. The DO analyzer controller was connected to an air pump to control the DO in the aerobic biofilm reactor set stable in the range of 3.5–4.5 mg/L. The COD, five-day biochemical oxygen demand (BOD5), petroleum, TN, ammonia nitrogen (NH4 +-N), nitrate nitrogen (NO3−-N), volatile phenol, and sulfide contents were determined by following the standard methods (State Environmental Protection Administration of China, 2002). Each measurement was performed in triplicate. The average of the three parallel measurements was reported. Each parameter was detected for 30 days, and numerical ranges were obtained. 2.3 DNA extraction and microbial diversity analysis Five samples were labeled as A2, A4, A11, P1, and O1. A2, A4, and A11 were collected from the anaerobic biofilm, located at sampling ports 2, 4, and 11. P1 was a
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granule sludge sample collected from sampling port 9. O1 was sludge collected from the aerobic biofilm. The DNA of these samples was extracted by E.Z.N.A. Soil DNA Kit (OMEGA, USA).The DNA samples were sequenced by Hiseq 2500 PE 250 Illumina high throughput sequencing platform. Bacterial sequencing primers were Bac349f (5′-AGGCAGCAGTDRGGAAT-3′) and Uni806r (5′GGACTACYVGGGTATCTAAT-3′), and target region was V3+V4. Archaea sequencing primers were Arc113f (5′-ACKGCTSAGTAACACGTGG-3′) and Arc520r (5′-TACCGCGGCKGCTGGCA-3′), and target region was V2+V3. 2.4 Construction and verification of the prediction model Box-Behnken method was used to design the response surface optimal prediction model (Zhao et al., 2016). After approximately 200 days of operation, the influent COD/TN (C/N), reflux ratio, and HRT were selected as independent variables. The response values were the efficiencies of COD and TN removal, which were labeled as ηCOD and ηTN, respectively. The experimental program was designed as 3 factors, 2 levels, and a total of 17 groups of experiments. At least 24 sets of experimental data were achieved in each group, and ηCOD and ηTN were the average values of these data. Independent variable encoding methods were performed using the following formula: Xi = (xi – x0) /∆x (1), where Xi is the encoding value of independent variable, xi is the actual value of the independent variable, x0 is the actual value of independent variables at the experimental center, and ∆x is the step size of independent variables. Design-Expert was used to design a series of experimental group, data analysis, and analysis of interaction between each factor. 3. Results and discussion
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3.1 Evaluation of the performance of the A/O reflux process with the biofilm reactor 3.1.1 Experimental treatment of heavy oil refinery wastewater The anaerobic and aerobic biofilm reactors were started up for three weeks. Then, the two reactors were connected, and reflux flow was started. The reflux ratio was gradually increased from 1 to 4.5, while the influent was fixed at 198 mL/h. TN removal increased with increasing reflux ratio. The A/O reflux process was operated for 30 days when reflux ratio reached 4.5 (Fig. 2a). The operational result showed that the TN of effluent was less than 15 mg/L which satisfied the requirement described in GB18918-2002 “Discharge standard of pollutants for municipal wastewater treatment plant” of China. Moreover, COD and petroleum removal efficiencies were more than 95% and 98%, respectively (Figs. 2b and 2c). In anaerobic and aerobic reactors, the pH ranges of effluent were 7.2–8.1 and 7.3–8.6, respectively. These effluent pH ranges both met the requirement described in GB18918-2002. Therefore, the pH values of the wastewater treatment process were not controlled. Compared with the original wastewater, the final effluent was clear and transparent and without smell, suspension, and oil. The influent of reactor was heavy oil refinery wastewater without pretreatment. Thus, the TN, COD, and oil content in wastewater fluctuates in daily wastewater discharge. The TN of influent fluctuated greatly within 9–12 days, and the range of fluctuation was 37.2–52.3 mg/L (Fig 2a). However, the fluctuation ranges of the TN in the effluent of anaerobic and aerobic reactor were 10.1–12.8 and 9.21–10.0 mg/L, respectively. Compared with influent, the TN of the effluent of the two reactors was stable. The process could withstand the impact of fluctuations in TN in wastewater. The COD and oil content of influent also fluctuated, but the effluent of the two reactors was stable (Figs. 2b and 2c). For the fluctuation of the contaminant concentration in the
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influent, the stable reflux water provided by aerobic reactor was mixed with influent in the anaerobic reactor. This mixture could reduce the impact of the fluctuation of pollutants in the influent on the reactor. Therefore, it had stable effect and good impact resistance for wastewater treatment. 3.1.2 Changes in the ORP in anaerobic reactor under different influent upflow velocities The anaerobic environment in the anaerobic reactor would be destroyed gradually when reflux ratio is improved. Methanogens showed a good activity, while ORP was lower than −150 mV in anaerobic environment. Influent rising velocity affected the change in ORP in the anaerobic biofilm reactor. The rising velocity of the influent in the reactor could be changed by adjusting the HRT. In this experiment, the reflux ratio was fixed at 4, and HRT was adjusted to 28, 36, 44, 52, and 60 h (corresponding increases in influent velocities were 6.5, 5.1, 4.2, 3.5, and 3.1 cm/h), respectively. Under each condition, the reactor was operating for more than 12 days, and the ORPs of the water samples collected from different heights of the reactor were tested. Along with the direction of water flow, the maximum ORPs of the sampling ports from No. 7 to No. 11 (approximately 45% of the effective volume of the reactor) were still lower than −150 mV (Fig. 3). This result indicates that the anaerobic biofilm reactor could provide a good anaerobic environment for methanogens to ensure high removal efficiency of COD. The ORPs of sampling ports from Nos. 1 to 11 increased first and then decreased. Hydrolysis acidification reaction mainly occurred at sampling port Nos. 1 to 3. In an anaerobic environment, hydrolysis acidification is an oxidation process for organic compounds. ORP would increase with increasing oxide. Thus, the ORP was increased first. With uprising of water, methane production began to
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occur above the No. 3 sampling port. Methane production is a reduction process for acetic acid and other organic compounds containing oxygen. ORP would gradually decrease with decreasing oxidation substances in wastewater. Therefore, the curve began to turn, and ORP began to decline. ORP gradually declined, and the curve gradually decreased at the sampling port Nos. 9 to 11. This phenomenon was mainly caused CO2 fixation by autotrophic sulfur-oxidizing bacteria. Thus, the watercontaining organic compounds in water increased, and this content would be described in detail below. 3.2 Division of functional areas in the anaerobic biofilm reactor Stable inflow would form an uprising plug flow in the reactor. Organic matter in wastewater was degraded into volatile fatty acid (VFA), alcohols, and other substances by hydrolysis acidification and acetic acid production, resulting in remarkably increased total VFAs. COD decreased because of CO2 production and organic matter adsorption of the biofilm. Thus, an opposite relationship exists between the change in VFAs and change in COD in the areas of hydrolysis acidification and acetic acid production. With uprising water, acetic acid, methanol, and hydrogen compounds in the wastewater could be used by methanogens to produce methane. At this time, VFAs and COD both decreased. A similar relationship exists between changes in VFAs and COD in the methane production area. Thus, the functional areas are divided according to the changing trend in the CODs and VFAs of the water samples at the different heights of the anaerobic reactor (Li et al., 2014). The coverages of the various functional areas in the anaerobic biofilm reactor under different reflux ratios are shown in Fig. 4. The COD and TN of the influent of anaerobic reactor were in the ranges of 600–700 and 30–45 mg/L, respectively. Reflux
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ratio was adjusted into 0, 2, 3, and 4, while the HRT of net flow of anaerobic reactor was fixed at 68 h. The corresponding rising velocities were 2.9, 8.8, 11.8, and 14.7 cm/h. Under each reflux ratio, the internal environment of anaerobic reactor was stable after more than 30 days of operation. The CODs and VFAs of wastewater samples which were collected from different heights of the reactor were detected to divide the functional areas in anaerobic biofilm. The increase in water velocity was gradual, so the influence of disturbance could be neglected. With increasing reflux ratio, the coverage of the various functional areas in the anaerobic biofilm also changed, further affecting the water quality of the effluent. As reflux ratio increased, the coverage rate of area (1) gradually increased (i.e., 25%, 33%, 42%, and 50%, respectively), area (2) gradually decreased (i.e., 75%, 67%, 58%, and 50%, respectively), and coverage rate of area (3) included in area (2) were gradually decreased (i.e., 50%, 42%, 25% and 17%, respectively) (Fig. 4). Thus, the effect of reflux ratio at the coverage rate of different functional areas in the anaerobic biofilm reactor was remarkable. Improving the reflux ratio would increase the amount of reflux water with dissolved high oxygen to increase the impact on anaerobic environment. The DO could be used in hydrolysis acidification which could be operated under anoxic conditions. Thus, the hydrolysis acidification area would increase as reflux ratio improved, and the impact of the methane production area would be compensated. The area (2) in Fig. 4a is the largest area in the four pictures. However, the effluent COD (148 mg/L) in this area was not the lowest, although a large methane production area indicates a large biomass of methanogens. A large methane production area could not improve COD removal. Various functional areas existed in order in the anaerobic biofilm. Methanogenesis in the methane production area was dependent on
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the product from the hydrolysis acidification area. When the VFAs changed slowly, the change in COD showed a similar trend. This result indicates that the main type of methanogen in the biofilm used VFAs. The concentration of VFAs decreased rapidly during the initial stage of methane production and maintained at low level. Thus, the initial stage of methane production had the highest methanogenic activity, and the rest was limited by the low VFA concentrations. The increase in the reflux ratio improved the dilution times of the influent and reduced toxicity. Additionally the more reflux water, the more DO was carried into the reactor. Consequently, a large number of facultative bacteria multiplied, and area (1) expanded. Thus, the degree of hydrolysis acidification improved, and the VFAs increased. The available VFAs increased, resulting in increased highly active region within the methane production area but reduced the COD of effluent. However, the maximum amount of VFAs did not increase with increasing reflux ratio (Fig. 4). The change in the microbial community on the biofilm had hysteresis, although the reactor has been operating for 30 days under each condition. Methane production already occurred in the methane producing area as shown in Figs. 4b, 4c, and 4d, and part of VFAs had been consumed. These results will not affect the accuracy of the experimental results, because this experiment focused on the mechanism. Thus, improving the efficiency of COD removal with a biofilm reactor is important for the appropriate expansion of the hydrolysis acidification and acetic acid production area. 3.3 Analysis of microbial community diversity Hiseq 2500 PE 250 Illumina high throughput sequencing platform was performed to reveal the microbial diversity and distribution in the five zones of biofilm
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using A/O process. The diversity estimators of the Shannon index for samples from the hydrolysis acidification and acetic acid areas (A2), transition zone between the hydrolysis acidification and acetic acid areas and methane-producing area (A4), methane production area (A11), granular sludge in methane-producing area (P1), and aerobic biofilm (O1) were 8.21, 8.50, 6.49, 7.96, and 7.58, respectively (Table S1). The area for hydrolysis acidification and production of acetic acid area showed the maximum diversity in the bacterial community. The hydrolysis acidification and acetic acid production areas belong to the transition area from aerobic to anaerobic and had rich substrate, leading to the fast growth of various microbes in this area. With the uprising of water, organic species was gradually reduced and DO consumed, and microorganisms were screened more and more strictly. Thus, the diversity of microorganisms decreased. The diversity in the microorganisms of the five samples was ranked as A2 > A4 > P1 > O11 > A11. The microbial communities of the five samples of biofilm significantly differed at the phylum level (Fig. 5). Comparison among the five sample communities indicated that Proteobacteria existed in both anaerobic and aerobic biofilms and was the most abundant in the aerobic environment (A2, 43.03%; A4, 29.61%; P1, 33.62%; A11, 16.93%; and O1, 54.62%). The Chloroflexi was more abundant at the hydrolysis acidification area, but few in the aerobic environment (A2, 20.07%; A4, 23.54%; P1, 14.25%; A11, 7.90%; and O1, 0.39%). The microbial community at the COD recovery area (A11) microcosm was found to be dominated by Chlorobi (48.56%), which was low in other samples (A2, 1.28%; A4, 17.78%; P1, 3.53%; and O1, 0.67%). By contrast, the abundance of Bacteroidetes in anaerobic showed a decreasing trend (A2, 6.23%; A4, 5.82%; P1, 2.60%; and A11, 1.65%).
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In the aerobic biofilm reactor, the air lift inner loop flow guiding tube was equipped to produce a circulating flow. Therefore, aerobic biofilm was not stratified along the vertical direction. The top three most abundant microorganisms of O1 were Proteobacteria, Nitrospirae, and Acidobacteria, with abundances of 54.75%, 14.6%, and 9.85%, respectively (Fig. 5b). Most of these microorganisms were facultative anaerobic and aerobic bacteria. Microbial community of archaea was not complex (Fig.5b). Euryarchaeota was always the predominant archaea, with abundances in A2, A4, P1, and A11 at 98.82%, 96.34%, 87.32% and 90.37%, respectively. The richness of the archaea gradually increased, while the abundance of Crenarchaeota, Thaumarchaeota, and uncultured archaea gradually increased in A2, A4, P1, and A11. These bacteria were mainly methane-producing bacteria. 3.4 Functional microbial groups in the wastewater treatment by A/O process During wastewater treatment, the removal of pollutants was accomplished by the cooperation of all functional microbial groups. A summarized overview of the microbial diversity results facilitated the postulation of a probable mechanism model to better elucidate the interplay of microbial groups during wastewater treatment (Fig. 6). Microbial diversity indicated the presence of three kinds of pollutant degradation processes (i.e., petroleum and refractory organics degradation, other organic pollutant degradation, and TN removal by denitrification) in the samples supported by required functional microbial groups. The functional microbial groups of methanogenic archaea (A2, 1.98%; A4, 0.94%; P1, 9.56%; A11, 0.82%; and O1, 0.24%) and syntrophic bacteria (A2, 5.05%; A4, 6.39%; P1, 9.65%; A11, 3.92%; and O1, 0.14%) were found in the anaerobic
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biofilm reactor. These microorganisms played an important role in the removal of petroleum and refractory organic matters. The combination of methanogenic archaea and syntrophic bacteria resulted in extreme anaerobic metabolism (Stams & Plugge, 2009). The electron transfer between the synergism bodies could reduce the energy needed for the hydrolysis of pollutants (Shen et al., 2016). This process could degrade petroleum and refractory organic matters to directly produce methane through the sharing of low energy. Further analysis of sequencing results showed that more than half of syntrophic bacteria evidently reduced sulfate. Methanogenic process was also a reductive reaction. A competition for electron exists between syntrophic bacteria with function of sulfate reduction and methanogens (Lu et al., 2016). Therefore, only syntrophic bacteria that do not reduce sulfate could form syntrophic bacteria union body with methanogenic archaea. Syntrophic bacteria that can reduce sulfate could unite the body of syntrophic bacteria with hydrolysis acidification bacteria. The process of hydrolysis and acidification for organic compounds was oxidation. In an anaerobic environment, these processes could use sulfate and elemental sulfur as electron acceptor and organic compounds as electron donor to produce hydrogen in the forms of NADH or FADH2 to reduce the activation energy required to degrade refractory organic compounds (Sousa et al., 2009). Hydrolysis acidification and degradation of the syntrophic bacteria union body would produce VFAs and other low-molecular weight organic matters to enhance the biodegradability of wastewater (Narihiro & Sekiguchi, 2007). H2S produced by the effect of sulfate reduction in anaerobic reactor produced smelly effluent. Chlorobiaceae (A2, 0%; A4, 9.09%; P1, 0.68%; A11, 18.67%; O1, 0%), which are non-oxygen photosynthetic sulfur-oxidizing bacteria, were found in the
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COD recovery area of anaerobic environment. These bacteria could reduce the concentration of H2S in the effluent from the anaerobic reactor, thereby reducing the smell during wastewater treatment (Hatamoto et al., 2016). Chlorobiaceae used sulfide and sulfur as electron donors to fix CO2 to simple organic compounds, mainly engaged in anoxygenic photosynthesis (Gregersen et al., 2011). Thus, a COD recovery area emerged because of the CO2 fixing effect of non-oxygen photosynthetic sulfur oxidizing bacteria. The COD recovery area is very important to wastewater treatment. Although it slightly reduced COD removal efficiency, Chlorobiaceae removed H2S and S2 which made the effluent smelly. The reasonable existence of this sulfur oxidation made the anaerobic biofilm form a perfect anaerobic micro ecosystem. Denitrification was one of important functions of the A/O reflux process. NH4+ N entered into the aerobic reactor to produce NO3−-N by nitrosation and nitrification. NO3−-N was returned to the anaerobic reactor to achieve denitrification. Nitrosomonadaceae, Nitrospiraceae, and Rhodocyclaceae were the most abundant in the whole TN removal process, similar results were reported by (Yi et al., 2016). Few studies have reported on the function of denitrification in the syntrophic bacteria union body. However, denitrification was a reductive reaction that can possibly form syntrophic bacteria union body with hydrolysis and acidification bacteria in organic matter degradation. 3.5 Analysis and validation of prediction model 3.5.1 Construction of prediction model The statistical significance of an empirical model with less experimental data can be established based on the response surface method, which is an effective
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multivariate analysis. The experimental design with actual and predicted values is shown in Table S2. The quadratic model was established based on the experimental data, and the coefficients, with statistical significance to all response values, were obtained by polynomial regression analysis. Encoded values were used as independent variables in the quadratic model. After manual fitting (removal of model terms with value “Prob > F” greater than 0.05), the final model equations in terms of code factors were as follows: ηCOD = 88.19 + 1.08X1 + 3.69X2 – 1.58X3 – 0.75X1X3 – 1.57X2X3 – 0.98X2 2– 4.58 X32 (2), ηTN = 76.78 – 0.99X1 + 4.04X2 + 0.90X3 – 1.70X12 – 1.43X32 (3), Within the two models, X1 is C/N, X2 is the reflow ratio, and X3 is HRT. Analysis results of model (2): The F-value of 709.23 implied that the model was significant. The “lack of fit Fvalue” of 1.90 implied that the lack of fit was not significant relative to the pure error. P-values were less than 0.0001. R2 values were 0.9982, very close to 1. Model (2) could be used to navigate the design space. In addition, the effects on ηCOD, X1, X2, X3, X12, X1X3, X2X3, X22, and X32 were extremely significant (P < 0.01). The effect of the independent variables on ηCOD could be ranked as X2 > X3 > X1, as observed from the single factor coefficient. Interaction effects on ηCOD could be ranked as X2X3 > X1X3. The ηCOD of X1, X2, and X3 partial derivatives are as follows: ηCOD' X1 (X1, X2, X3) = 1.08 – 0.75X3 (4), ηCOD' X2 (X1, X2, X3) = 3.69 – 1.57X3 – 1.96X2 (5), ηCOD' X3 (X1, X2, X3) = –1.58 – 0.75X1 – 1.57X2 – 9.16X3 (6).
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The coding values X1, X2, and X3 belong to (–1, 1). Thus, 0.33 < equation (4) < 1.83, which is always greater than 0. ηCOD improved with increasing influent C/N when the reflux ratio and HRT were fixed. Because equation (5) has variable X2, the calculated second derivative was ηCOD'' X2 (X1, X2, X3) = –1.96 < 0. Thus, equation (5) monotonically decreased. Based on the range of independent variables, 0.16 ≤ equation (5) ≤ 7.19 is always greater than 0. Therefore, ηCOD improved with increasing reflux ratio when the influent C/N and HRT were fixed. Equation (6) was treated in the same manner as equation (5). Because ηCOD'' X3 (X1, X2, X3) = –9.16 < 0, equation (6) monotonically decreased. Based on the range of independent variables, –13.06 ≤ equation (6) ≤ 9.9, whereas equation (6) = 0, and X3 = 0.17 – 0.08X1 + 0.17X2 (7). At this point, model (2) had a maximum or minimum value. Because of ηCOD'' X3 (X1, X2, X3) = –9.16 < 0, equation (2) was a convex function. Thus, equation (7) was established, and ηCOD had a maximum value. Therefore, ηCOD improved first and then decreased with increasing HRT when the influent C/N and reflux ratio were fixed. Analysis results of model (3): The F-value of 238.06 implied that the model was significant. The “lack of fit Fvalue” of 1.16 implied that the lack of fit was not significant relative to the pure error. P-values were less than 0.0001. R2 values were 0.9930, very close to 1. Model (3) could be used to navigate the design space. The effects on ηTN, X1, X2, X3, X1 2and X3 2 were extremely significant (P < 0.01). The effect of independent variables on ηTN was X2 > X1 > X3 as observed from single factor coefficient. The ηTN of X1, X2, X3 partial derivatives are as follows: ηTN' X1 (X1, X2, X3) = –0.99 – 3.4X1 (8),
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ηTN' X2 (X1, X2, X3) = 4.04 (9), ηTN' X3 (X1, X2, X3) = 0.90 – 2.86X3 (10), The coding values X1, X2, and X3 belong to (–1, 1). Thus, –1 ≤ X3 < –0.29, equation (8) > 0, and –0.29 < X3 ≤ 1, equation (8) < 0. ηTN improved first and then decreased with the increase of influent C/N when the reflux ratio and HRT were fixed. Equation (9) = 4.04, which is always greater than 0. Therefore, ηTN improved with the increase of reflux ratio when the influent C/N and HRT were fixed. Equation (10) indicated that –1 ≤ X3 < 0.31, equation (10) > 0, and 0.31 < X3 ≤ 1, equation (10) < 0. Therefore, ηTN improved first and then decreased with increasing HRT when the influent C/N and reflux ratio were fixed. 5.2 Validation of prediction model The experimental conditions were optimized by response surface optimization model to obtain appropriate ηCOD and ηTN within the range of experimental design. Three sets of experimental conditions were selected to verify the reliability of the model. In the first set of experimental conditions, the maximum ηCOD predicted can be obtained. In the second set, the maximum ηTN predicted can be obtained. In the third set, moderate values of ηCOD and ηTN were both obtained. Validation results and model predictions are shown in Table 2. The deviation of ηCOD and ηTN between prediction and actual values were both less than 5% (Table 2). Within the scope of experimental design, the model could play a very good role in optimizing the experimental conditions and predicting experimental results. The biofilm reactor with the A/O reflux process could be used to effectively treat heavy oil refinery wastewater containing 70.5–95.8 mg/L petroleum. COD and TN
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removal efficiencies reached 93.2% and 82.8%, respectively. The anaerobic reactor was responsible for 95% of the total COD removal. 4. Conclusion The large height–diameter ratio of the anaerobic biofilm reactor with soft filler guaranteed that anaerobic environment was not destroyed in oily wastewater treatment, although reflux ratio reached 4.5. Different functional areas were evident in the anaerobic biofilm reactor, and COD removal increased because of the expansions in the hydrolysis acidification and acetic acid production area. Syntrophic bacteria union body was beneficial in the degradation of refractory organics. The prediction model was highly consistent with experimental results, providing reference for the industrial application of the proposed process. Acknowledgements This work was funded by the National Natural Science Foundation of China (No. 51474223, 51634008 and 41403068) and China Petroleum Science and Technology Major Project of Low Carbon Emission (No. 2016E-12). The authors are grateful to State Key Laboratory of Heavy Oil Processing of China for their technical assistance and to Liaohe Petrochemical Company for field and logistical assistance during this work.
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List of Tables
Table 1 Characteristics of wastewater of heavy oil processing.
Table 2 Experimental and predicted values for ηCOD and ηTN in the validation experiments
Figure Captions
Fig. 1 A simple schematic diagram of the field-scale A/O biofilm reactor reflux process. (1) Raw water storage, (2) Thermostatic water bath, (3) Peristaltic pump, (4) Anaerobic biofilm reactor, (5) Aerobic biofilm reactor, (6) Air Pump, (7) Discharge water storage
Fig. 2 The changes of content and removal efficiency of TN (a), COD (b) and Petrelom (c) for the effluent and influent over time in A/O reflux process at 4.5 reflux ratio
Fig. 3 Changes of ORP in anaerobic reactor under different HRT.
Fig. 4 Coverages of the various functional areas in the anaerobic biofilm reactor under different reflux ratios. Reflux ratio of (a), (b), (c) and (d) was 0, 2, 3 and 4, respectively. (1) Hydrolysis acidification and production of acetic acid area, (2) Methane production area, (3) COD recovery area
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Fig. 5 Distribution of bacterial (a) and archaeal (b) groups in five samples at phylum level.
Fig. 6 Mechanism model depicting the interplay of functional microbial groups in heavy oil refinery wastewater treatment by A/O process. The labeled species were the most abundant in each functional microbial group. In anaerobic area, below the dotted line was hydrolysis acidification and production of acetic acid area, and above it was methane producing area. (1) Hydrolysis acidification bacteria, (2) Syntrophic bacteria with function of sulfate reduction + hydrolysis acidification bacteria, (3) Non-oxygen photosynthetic sulfur oxidizing bacteria, (4)Syntrophic bacteria without function of sulfate reduction + methanogens, (5) Methanogens, (6) Aerobic heterotrophic bacteria, (7) Nitrite bacteria, (8) Nitrifying bacteria, (9) Denitrification bacteria.
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Fig. 1 A simple schematic diagram of the field-scale A/O biofilm reactor reflux process. (1) Raw water storage, (2) Thermostatic water bath, (3) Peristaltic pump, (4) Anaerobic biofilm reactor, (5) Aerobic biofilm reactor, (6) Air Pump, (7) Discharge water storage.
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Fig. 2 The changes of content and removal efficiency of TN (a), COD (b) and Petrelom (c) for the effluent and influent over time in A/O reflux process at 4.5 reflux ratio.
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Fig. 3 Changes of ORP in anaerobic reactor under different HRT.
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Fig. 4 Coverages of the various functional areas in the anaerobic biofilm reactor under different reflux ratios. Reflux ratio of (a), (b), (c) and (d) was 0, 2, 3 and 4, respectively. (1) Hydrolysis acidification and production of acetic acid area, (2) Methane production area, (3) COD recovery area.
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Fig. 5 Distribution of bacterial (a) and archaeal (b) groups in five samples at phylum level
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Fig. 6 Mechanism model depicting the interplay of functional microbial groups in heavy oil refinery wastewater treatment by A/O process. The labeled species were the most abundant in each functional microbial group. In anaerobic area, below the dotted line was hydrolysis acidification and production of acetic acid area, and above it was methane producing area. (1) Hydrolysis acidification bacteria, (2) Syntrophic bacteria with function of sulfate reduction + hydrolysis acidification bacteria, (3) Non-oxygen photosynthetic sulfur oxidizing bacteria, (4)Syntrophic bacteria without function of sulfate reduction + methanogens, (5) Methanogens, (6) Aerobic heterotrophic bacteria, (7) Nitrite bacteria, (8) Nitrifying bacteria, (9) Denitrification bacteria.
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Table 1 Characteristics of wastewater of heavy oil processing Characteristic pa-
Characteristic paRange
Range
rameters
rameters
COD
650–1150 (mg/L)
B/C
0.4–0.5
Petroleum
70.5–95.8 (mg/L)
ORP
50–80 (mV)
TN
35–70 (mg/L)
NH4 +-N
30–58 (mg/L)
NO3--N
0.1–0.6 (mg/L)
pH
7.5–8.8
2–2.1 (mS/cm)
Volatile phenol
20–28.2 (mg/L)
Sulfide
≤ 2 (mg/L)
Suspended matter
73–99 (mg/L)
Diotoxicity
High
Electric conductivity
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Table 2 Experimental and predicted values for ηCOD and ηTN in the validation experiments Level Reflow
No.
Actual
Predicted
ηCOD
ηCOD
(%)
(%)
HRT (h) C/N (X1)
ratio
Actual
(X3) (X2)
Predicted
ηTN (%) ηTN (%)
1
23
4.5
52.3
93.2
93.8
78.5
79.0
2
19.1
4.5
67.9
89.3
88.0
82.8
83.4
3
21
3
70
86.9
85.3
77.3
76.2
Note: The datas of actual value in table were the mean of three repeated experiments.
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Research Highlights > Anaerobic–aerobic process was used to treat oily wastewater without pretreatment. > Large height–diameter ratio reactor with soft filler could enhance reflux ratio. > Rational functional areas distribution in the reactor increased pollutants removal. > Syntrophic bacteria union body could degrade petroleum and refractory organics. > Prediction model provided a new operational management to treat wastewater.
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