Intensified heterotrophic denitrification in constructed wetlands using four solid carbon sources: Denitrification efficiency and bacterial community structure

Bioresource Technology 267 (2018) 416–425

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Bioresource Technology journal homepage: www.elsevier.com/locate/biortech

Intensified heterotrophic denitrification in constructed wetlands using four solid carbon sources: Denitrification efficiency and bacterial community structure

T

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Zhihao Si, Xinshan Song , Yuhui Wang, Xin Cao, Yufeng Zhao, Bodi Wang, Yan Chen, Awet Arefe College of Environmental Science and Engineering, State Environmental Protection Engineering Center for Pollution Treatment and Control in Textile Industry, Donghua University, Shanghai 201620, China

G R A P H I C A L A B S T R A C T

A R T I C LE I N FO

A B S T R A C T

Keywords: Solid carbon source Constructed wetland Denitrification Nitrate removal Bacterial community

Biodenitrification using solid carbon sources is a cost-effective way for nitrate removal. In the study, wheat straw, cotton, poly(butylene succinate), and newspaper was chosen as the carbon source to compare the denitrification efficiency and bacterial communities in constructed wetlands. Parameters including COD, NO3−-N, NO2−-N and total nitrogen (TN) were analyzed. Results indicated that newspaper provided significantly higher NO3−-N and TN removal efficiency than the other three solid carbon sources in low-temperature condition. Moreover, both newspaper and wheat straw allowed high NO3−-N and TN removal efficiency in high-temperature condition. According to pyrosequencing analysis, denitrifying bacteria Dechloromonas and Thauera were the predominant genus in the anaerobic zone of CO- (3.92 and 2.35%, respectively), WS- (1.97 and 1.02%, respectively) and NP-CWs (1.71 and 1.31%, respectively). Genus of Levilinea was enriched in NP- (1.02%) and WS-CWs (0.91%). Furthermore, genus Paludibacter (2.69%) and Saccharofermentans (3.14%) showed high relative abundance in WS-CWs.

1. Introduction

less operation and maintenance requirements for wastewater treatment (Wu et al., 2015), and it has proved to be a reliable treatment technology for nitrate containing wastewater. As a primary mechanism for

Constructed wetlands (CWs) are engineered systems with low-cost,

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Corresponding author. E-mail address: [email protected] (X. Song).

https://doi.org/10.1016/j.biortech.2018.07.029 Received 5 May 2018; Received in revised form 3 July 2018; Accepted 6 July 2018 Available online 07 July 2018 0960-8524/ © 2018 Elsevier Ltd. All rights reserved.

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nitrate removal from wastewater, microbial denitrification plays a decisive role in CWs (Hang et al., 2016; Pan et al., 2015). Heterotrophic denitrifying microorganisms are the main participants in most of the denitrification processes. They utilize NO3− as electron acceptor in the electron transfer chain under anaerobic or anoxic conditions to restore NO3− (Mu et al., 2016). However, heterotrophic denitrification efficiency is affected by carbon sources and electron donors and the lack of carbon source often leads to low nitrate removal efficiency (Zhang et al., 2016). Solid-phase denitrification (SPD) is a denitrification way in which a solid carbon source (SCS) is used as the only carbon source or a supplement to traditional liquid carbon sources (Zhao et al., 2017). Firstly the SCS was decomposed into soluble and small molecule organic matter, which was catalyzed by the hydrolases secreted by the microbes. Following this, a majority of the organic matter was utilized by denitrifying microbes as the electron donor to reduce NO3− to NO2−, NO, N2O and finally to N2 (Wang and Chu, 2016). The application of SCS reduces the risk of effluent quality deterioration, which caused by overdose of habitual liquid carbon source. Generally, carbon release performance is an important index for evaluating the denitrification enhancement. An ideal SCS should be cheap and widely accessible and possess the characteristics of high carbon content, easy decomposition, slow release, strong effect and little nitrogen or phosphorus release (Li et al., 2016). In recent years, the application of synthetic and natural wastes as SCS for biological denitrification has been extensively explored. Polyacetic acid and poly-3-hydroxybutyrate-co-3-hydroxyvalerate were proved to be a carbon source of CWs for denitrification and the maximum denitrification efficiency was up to 97.3% (Yang et al., 2018). In the CWs with corn starch-polycaprolactone as a carbon source, nitrate was mainly removed from the layer filled with SCS and the removal efficiency of nitrate nitrogen was up to 98.23% (Shen et al., 2015b). Warneke et al. (2011) demonstrated that maize cobs could provide high-efficiency of nitrate removal, but there was also relatively higher organic carbon leaching in the effluent. By contrast, woodchips exhibited moderate and sustained denitrification performance. In addition, different SCS including maize cob, woodchips, green waste and wheat straw have been trialed in denitrification beds and suggested that the nitrate removal efficiencies for maize cob, green waste and wheat straw were significantly higher than that of wood media (Cameron and Schipper, 2010). Volokita et al. (1996) used newspaper as the sole carbon source of lab-scale reactors and achieved the complete denitrification in simulated wastewater containing 100 mg L−1 nitrate. However, the denitrification efficiency of cellulose carbon source was sensitive to temperature change. In SPD system, the organic carbon release rate of SCS depends on degradation of microorganisms and degradation products can be utilized by denitrifying bacteria. The study on the function and structure of the microbial community in the SPD system can provide the basis for their application in nitrate removal (Wang and Chu, 2016). At present, the effect of single SCS on the bacterial community structure in SPD systems has been extensively explored (Chu and Wang, 2011; Zhu et al., 2015). However, the comparison of bacterial communities in constructed wetlands with different solid carbon sources was rarely reported. In the study described here, four solid carbon sources (Wheat straw, cotton, poly(butylene succinate) and newspaper) were utilized as supplementary electron donors to traditional liquid carbon sources in CWs. The biodenitrification efficiency was explored both in low- and hightemperature stage. Furthermore, the effects of different SCS on the structure and function of bacterial communities were studied with 16S rRNA macro genome sequencing technology. Bacteria governing the solid-phase denitrification process were identified and reported.

Table 1 Composition analysis of four solid carbon sources and material mass in CWs. Materials

Wheat straw Cotton PBS Newspaper

Mass fractions of elements (%) C

H

N

Carbon mass (g)

Material mass (g)

43.81 42.52 55.48 39.14

6.11 6.52 7.12 5.76

0.29 ≤0.05 ≤0.05 ≤0.05

43.81 43.81 43.81 43.81

100 103 79 112

2. Materials and methods 2.1. Solid carbon sources and simulated wastewater Four solid carbon sources used in this study were wheat straw, cotton, poly(butylene succinate) granules (PBS 3001MD, Showa Highpolymer Co., Ltd.) and newspaper. The elemental compositions of four solid carbon sources and their dosages in CWs were shown in Table 1. Although the dosages of the four carbon sources were various, the carbon element of equal mass was added to each experimental device. All the solid carbon sources were washed with distilled water and dried naturally in the experiment. Simulated wastewater was prepared with tap water according to the following composition: 105 mg L−1 Glucose, 100 mg L−1 CH3COONa, 43 mg L−1 NaNO3, 0.5 mg L−1 K2HPO4·3H2O, 17.7 mg L−1 MgCl2·6H2O, 7.5 mg L−1 ZnCl2, 17.5 mg L−1 CaCl2, 10.0 mg L−1 CuSO4·5H2O, 0.25 mg L−1 −1 −1 FeSO4·7H2O, 1 mg L MnSO4·H2O, 0.25 mg L Na2MoO4·2H2O, 0.025 mg L−1 CoCl2·6H2O, and 6.2 mg L−1 H3BO4. 2.2. Experimental devices and operation A total of 30 polyethylene plastic containers (height: 50 cm; diameter: 16 cm) were used to simulate lab-scale vertical downflow constructed wetland, and the sample ports were 8 cm above the bottom of containers. In the experimental devices, quartz sand (particle size: 2–4 mm; thickness: 10 cm) was firstly added at the bottom and then covered with the homogeneous mixture of SCS and quartz sand (thickness: 35 cm) (Fig. 1). Disease-free Acorus calamus L. in the same growth phase with the same fresh weight was transplanted in CWs (5 rhizomes per unit), and the roots of wetland plant were placed in the upper portion of the CWs. In this case, the experimental devices give a liquid volume of 3.0 ± 0.2 L. Two batches of experimental devices were operating at the lowtemperature stage (12.5 ± 4.0 °C, from December to January) and the high-temperature stage (24.55 ± 2.35 °C, from May to June), respectively. Five units were set up in triplicate for each stage. The CK-CWs without SCS were the blank control and WS-CWs, CO-CWs, PBS-CWs, and NP-CWs were filled with wheat straw, cotton, PBS, and newspaper respectively. The experimental period of each stage was 36 days, including 21 days of acclimation for CWs system and 15 days of operation. The hydraulic retention time (HRT) and influent pH of CWs were 24 h and 7.3 ± 0.3, respectively. At the beginning of the acclimation stage, each CW device was inoculated with an equal volume of anaerobic sludge (1.0 L) which collected from the Songjiang Wastewater Treatment Plant (Songjiang, China). Anaerobic sludge was first diluted with simulated wastewater and then fed into the CWs from the top via a metering pump. Also, synthetic wastewater was fed into the CWs in accordance with the above operation during the operation stage. 2.3. Sample collection and analysis To remove suspended solids (SS), all the water samples were filtered through 0.45-μm filter membrane (NAVIGATOR, China) before the determination of water quality parameters. The temperature, pH and 417

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Fig. 1. Schematic diagram of experimental devices with different solid carbon sources addition.

addition, the effluent pH almost unaffected by the temperature changes. These findings indicating that the effluent pH of CWs was not further reduced after the use of SCS. The average DO value in influent was 7.44 mg L−1 in low-temperature stage and this was similar to that in high-temperature stage (7.69 mg L−1). Whereas the effluent DO values of all CWs were < 2 mg L−1 throughout the whole process. The high denitrification performance requires neutral or near neutral pH conditions, however, the effluent of CWs was accompanied by different degrees of pH reduction (Al-Omari and Fayyad, 2003). Moreover, the denitrification process required a DO concentration below 2 mg L−1 (Waki et al., 2018). The pH or DO in effluent showed no significant difference between SCS-CWs and CK-CWs, indicating that the four solid carbon sources had no significant effect on pH or DO in effluent and could be further utilized in CWs to explore the denitrification process.

DO in influent and effluent were measured with a dual-probe multiparameter meter (HQ40d, HACH, USA). COD was measured with a multi-parameter portable colorimeter (DR900, HACH, USA). NO3−-N and total nitrogen (TN) were measured with an ultraviolet spectrophotometer (UV-2000, Unico, China) according to the standard method (GB3838-2002). The surface morphology of fresh and used SCS was examined by scanning electron microscope (Quanta 250, FEI, USA) in the high-temperature stage 2.4. High-throughput 16S rRNA sequencing analysis of bacteria community At the end of the high-temperature operation stage, the biofilm at the bottom of the CWs was used for bacteria community analysis and the extraction of microbial genome from the surface of quartz sand according to the previously described method (Wang et al., 2016). Primers 515F (5′ -Linker A (barcode) GTGCCAGCMGCCGCGGTAA -3′) and 909 R (5′ -Linker B-CCCCGYCAATTCMTTTRAGT-3′) were used for the amplification of V4-V5 regions of bacterial genome. PCR conditions were performed the previously described method (Prest et al., 2014). PCR products were sequenced on Illumina MiSeq platform according to standard protocols by Sangon Biotech Co., Ltd (Shanghai, China).

3.2. Effects of SCS on effluent COD After the acclimatization stage of CWs, the effluent COD in SCS-CWs reached a stable level. It meant that excessively released organic carbon had been consumed or discharged with effluent during the acclimation stage (Dhamole et al., 2009). Variations of COD in different types of CWs in low- and high-temperature stages were shown in Fig. 2(a), in general, the COD releasing efficiency of wheat straw, cotton and newspaper significantly increased in the high-temperature stage. However, wheat straw showed a decreased trend in COD releasing efficiency after ten days in CWs. Moreover, comparing to other three solid carbon sources, PBS showed relatively low but stable COD releasing efficiency throughout the entire operation condition. Fig. 2(b) showed that the average influent COD in low- and high-temperature stages were respectively 108.50 ± 4.69 and 105.01 ± 4.27 mg L−1. The average effluent COD values of CK-CWs, WS-CWs, CO-CWs, PBS-CWs, and NPCWs were respectively 29.25 ± 8.60, 40.21 ± 7.41, 56.03 ± 12.33, 27.94 ± 11.75, and 57.65 ± 10.56 mg L−1 at low-temperature stage, and respectively 32.03 ± 7.11, 89.76 ± 21.41, 89.47 ± 8.08, 32.57 ± 5.96, and 196.59 ± 45.51 mg L−1 in high-temperature stage. It was observed that the COD removal performance showed no significant difference between CK-CWs and PBS-CWs in effluent, and it was higher than the other CWs. Notably, the COD removal efficiency of CK-CWs and PBS-CWs in the high-temperature stage were not significantly different from that in the low-temperature stage. In contrast, the COD removal efficiency of WS-CWs, CO-CWs, and NP-CWs were respectively 62.89 ± 6.96%, 48.42 ± 11.04%, and 46.96 ± 9.40% in the low-temperature stage and significantly reduced to 14.41 ± 21.07%, 14.79 ± 7.41%, and -87.72 ± 45.50% in the high-

2.5. Statistical analysis Statistical analysis of COD and NO3−-N, NO2−-N and TN removal efficiency in CWs with different SCS was conducted by one-way ANOVA test in SPSS 20.0 and the significant differences were assessed by Duncan’s multiple range test. P < 0.05 was considered as the significant level. The beta diversity distance matrix was calculated with computing method of Bray-Curtis according to the functional abundance of each sample, and the unweighted pair group method with arithmetic mean (UPGMA) was used for generating the bray tree plot via R software. 3. Results and discussion 3.1. pH and DO in CWs pH and DO are important influencing factors of the biodenitrification process (Luo et al., 2014). Table 2 shows the effects of four solid carbon sources on pH and DO in effluent of constructed wetlands. The pH values in influents of all the four CWs were neutral or slightly alkaline throughout the experiment. However, the average pH values in effluent were slightly acidic. The minimum pH values in low- and hightemperature were respectively 6.44 (CK-CWs) and 6.32 (NP-CWs). In 418

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Table 2 Changes in pH and DO during low- and high-temperature stages. Parameter pH DO

Influent Low temperature High temperature Low temperature High temperature

7.04 7.12 7.44 7.69

± ± ± ±

CK-CWs 0.03 0.06 0.35 0.29

6.44 6.64 1.63 1.52

± ± ± ±

0.09 0.10 0.52 0.24

WS-CWs

CO-CWs

6.59 ± 0.09 6.57 ± 0.06 1.22 ± 0.28 0.834 ± 0.25

6.49 6.48 1.18 1.09

± ± ± ±

0.15 0.08 0.36 0.28

PBS-CWs

NP-CWs

6.5 ± 0.13 6.61 ± 0.09 1.85 ± 0.48 1.3 ± 0.29

6.53 6.32 1.24 0.91

± ± ± ±

0.14 0.11 0.26 0.17

increasing organic carbon from low to high-temperature stage resulted in a significant increase in effluent COD and a decrease in COD removal efficiency when the influent COD remained unchanged. Besides, the effluent COD of wheat straw in the high-temperature stage showed a

temperature stage (P < 0.05). Previous studies had demonstrated that the organic carbon release rate of cellulose-rich solid carbon source was positively correlated with temperature (Cameron and Schipper, 2010). As presented in Fig. 2(a),

Fig. 2. Variations of COD in different types of CWs (CK-CWs, WS-CWs, CO-CWs, PBS-CWs, and NP-CWs) in low- and high-temperature stages. (a) Variations of COD concentration in different CWs under 24-h HRT; (b) Variations of average COD concentration in effluent. Error bars indicate mean ± standard deviation of 3 replicates. 419

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Fig. 3. Variations of NO3−-N, NO2−-N and TN in different types of CWs (CK-CWs, WS-CWs, CO-CWs, PBS-CWs, and NP-CWs) in low- and high-temperature stages under 24-h HRT. (a) Variations of NO3−-N concentration in different CWs; (b) Performance of NO3−-N removal in different CWs; (c) Variations of effluent NO2−-N concentration in different CWs; (d) Variations of effluent TN concentration in different CWs; (e) Performance of TN removal in different CWs. Error bars indicate mean ± standard deviation of 3 replicates.

CWs and WS-CWs (P > 0.05) and the NO3−-N removal performance showed no significant difference between CK-CWs and PBS-CWs (P > 0.05). In the high-temperature stage, the average removal efficiency of NO3−-N in all the CWs were decreased according to the following order: NP-CWs > WS-CWs > CO-CWs > PBS-CWs > CKCWs. The NO3−-N removal performance of NP-CWs showed no significant difference compared with WS-CWs and was significantly better than that in other CWs (P < 0.05). The average removal efficiency of NO3−-N in NP-CWs increased from 67.86 ± 10.79% (low-temperature stages) to 98.87 ± 1.13% (high-temperature stages), which were 3.21 and 3.89 times of that in CK-CWs, respectively. The NO3−-N removal efficiency of WS-CWs (49.16 ± 13.57%) showed no significant compared to that of CO-CWs (53.89 ± 7.66%) in the low-temperature stage, whereas the NO3−-N removal efficiency of WS-CWs (98.32 ± 2.13%) was significantly better than that of CO-CWs (70.86 ± 5.26%) in the high-temperature stage, suggesting that the denitrification performance of wheat straw as solid carbon source in CWs was more sensitive to temperature change. The NO3−-N removal efficiency of PBS-CWs in low- and high-temperature stages were

decreasing trend, indicating that the carbon release stability of cotton and newspaper were better than that of wheat straw and newspaper. Previous research (Cho et al., 2011) found that the biodegradability of PBS was remarkably weakened under anaerobic conditions. For PBSCWs, the average effluent COD showed no significant difference with CK-CWs. (Fig. 2(b)). Thus, it was inferred that the anoxic condition of CWs might be responsible for the low degradation performance of PBS granules. 3.3. Effects of SCS on effluent NO3−-N, NO2−-N and TN According to Fig. 3(a) and (b), the NO3−-N removal efficiency of CK-CWs in low- and high-temperature stages are respectively 15.33 ± 3.17% and 25.24 ± 3.55%. The result showed that temperature significantly affected the NO3−-N removal performance (P < 0.05). In the low-temperature stage, the average removal efficiency of NO3−-N in all the CWs decreased in the following order: NPCWs > CO-CWs > WS-CWs > PBS-CWs > CK-CWs. The NO3−-N removal performance showed no significant difference between CO420

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in the effluent.

Table 3 Alpha diversity index of bacterial communities in the anaerobic zone of CWs. Sample

Sequences

OTUs

Coverage

Chao1 index

Shannon index

3.4. Morphological observation of solid carbon sources

CK-CWs WS-CWs CO-CWs PBS-CWs NP-CWs

28,141 24,774 31,916 25,239 29,244

2404 2616 2477 2250 2416

0.95 0.94 0.96 0.95 0.96

5512.28 6136.59 4939.64 5004.11 5224.10

5.97 6.18 5.98 5.98 6.03

The four solid carbon sources used in CWs was examined by SEM before and after the high-temperature stage. The surface of cotton fiber is clean and smooth, whereas the other samples display irregular surfaces. Used wheat straw and newspaper was seriously damaged, meanwhile, rupture and disorder appeared on cotton fiber. However, different results were observed in PBS and the surface turned from rough to smooth although few pits and pores occurred on the surface. As shown in the images of fresh and used SCS, biodegradation of all the four solid carbon sources was visible.

respectively 18.29 ± 5.38% and 29.15 ± 4.92%, which were slightly better than that of CK-CWs, but the difference was not significant (P > 0.05). In general, the highest NO3−-N removal efficiency was obtained in NP-CWs in both low- and high-temperature stages. The NO2−-N accumulation trends in different CWs (HRT: 24 h) was shown in Fig. 3(c). In the low-temperature stage, the CWs exhibited different degrees of NO2−-N accumulation in effluent. Both CK-CWs and PBS-CWs showed significant NO2−-N accumulation compared to the other three CWs, and the maximum NO2−-N accumulation was found in CK-CWs (1.76 mg L−1) at day 10. Even the increasing trend of effluent NO2−-N concentration was also observed in WS-, CO-, and NPCWs after 3-days operation, the effluent NO2−-N concentrations were below 1.0 mg L−1 throughout the low-temperature stage. Similarly, the effluent NO2−-N also significant accumulated in CK-, PBS-, and CO-CWs during high-temperature stage, and the overall trend of NO2−-N accumulation in CK- and PBS-CWs was stronger than that in the low-temperature stage. However, the concentration of NO2−-N in effluents of both WS- and NP-CWs was below 0.1 mg L−1. The TN removal performances of all the CWs were shown in Fig. 3(d) and (e). As NO3−-N was the sole nitrogen source in the influent, besides, the effluent was low in NO2−-N concentration. Therefore, the tendencies in TN removal were similar to NO3−-N removal, and this also indicated that the four types of solid carbon source exhibited low nitrogen releasing efficiency. In low temperature stage, the average TN removal efficiency of WS-, CO- and WS-CWs was 51.89 ± 13.58%, 54.87 ± 5.38%, and 69.42 ± 9.08% respectively, which was 37.82%, 40.79% and 55.34% significantly higher than that of CK-CWs(14.07 ± 3.46%), respectively (P > 0.05). However, no significant difference was observed between CK- and PBS-CWs. In high temperature stage, both wheat straw and newspaper allowed the high TN removal efficiency (90.82 ± 2.89% and 89.62 ± 1.64%, respectively), and significantly higher than that of CO- (65.81 ± 5.38%), PBS- (23.08 ± 5.15%) and CK-CWs (17.55 ± 3.40%). Similar to the NO3−-N removal performance, the TN removal efficiency in SCS-CWs was higher in high-temperature than in low-temperature stage. As the physiological activity of microorganism involved in biodegradation and denitrification was affected by temperature changes (Spieles and Mitsch, 1999), the denitrification performances were different in the low- and high-temperature stages in SCS-CWs, particularly, in NP-CWs, WS-CWs, and CO-CWs with cellulose-rich solid carbon source (Volokita et al., 1996). The biodegradation of PBS required a long-term process and it was reported that the weight loss of pure PBS film was only 31.4% after 180 days of biodegradation (Liu et al., 2009; Zumstein et al., 2015)。Therefore, the low NO3−-N removal efficiency in PBS-CWs might be ascribed to its low carbon releasing efficiency. The insufficient supplement of carbon source for denitrification may lead to a low denitrification efficiency and NO2−-N accumulation (Akbari and Naeimpoor, 2014). In addition, there are studies reported that the excessive carbon source can also induce the accumulation of NO2−-N (Ge et al., 2012). The relatively low NO3−-N removal efficiency and high NO2−-N accumulation in the low-temperature stage indicating that all the four types of solid carbon sources cannot provide sufficient electron acceptor for denitrification. While in the high-temperature stage, the effluent COD in WS- and NP-CWs increased significantly, indicating that the carbon source was sufficient to ensure high denitrification performance and thus, there was no significant NO2−-N accumulation

3.5. Alpha diversity of bacterial communities As a relatively high COD releasing efficiency and denitrification performance was observed in high-temperature stage. Pyrosequencing analysis was employed to investigate the bacterial communities at the end of the experiment. The alpha diversity index of the bacterial communities in the anaerobic zone of CWs was shown in Table 3. A total 25,239–31,916 high-quality sequences were obtained after quality control process of raw sequence data. The number of OTUs ranged from 2250 (PBS-CWs) to 2616 (WS-CWs). The coverage index in all the CWs ranged from 0.94 to 0.96, indicating that the sequencing results were reliable and representative. The Chao1 index in all the CWs decreased according to the following order: WS-CWs > CK-CWs > NP-CWs > PBS-CWs > CO-CWs. The Shannon index decreased according to the following order: WS-CWs > NP-CWs > CO-CWs, PBS-CWs > CKCWs. According to the Alpha diversity index, the highest species richness was found in WS-CWs. In general, SCS decreased the species richness and increased the evenness of CWs. It was speculated that the highest OTUs of WS-CWs was attributed to its high Chao1 index (Qiu et al., 2016). 3.6. Functional clustering of bacterial communities A Bray tree plot based on cluster of orthologous group (COG) is shown in Fig. 4. Similar to the NO3−-N and TN removal efficiency, the classification results showed that PBS-CWs were clustered together with CK-CWs. Indicating that they were highly similar in the bacterial community structure, and the role of PBS as a solid carbon source was limited. Accordingly, the limited role coupled with the low carbon release rates may be the reasons for the low denitrification performance in PBS-CWs (Zumstein et al., 2015). In the high-temperature stage, WSCWs were clustered together with NP-CWs. To a certain degree, the similarity explained the similar denitrification performance between WS-CWs and NP-CWs.

Fig. 4. Bray tree plot of different types of CWs based on COG. The length of branches represents the distance between different samples. 421

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Fig. 5. Distribution of 16S rRNA assigned on phylum (a) and class (b) in different types of CWs.

denitrification performance in CWs. Although phylum Planctomycetes was enriched in CK- (7.99%), NP- (7.46%) and PBS-CWs (7.24%), nevertheless, the removal efficiency of NO3−-N was significantly lower in CK- and PBS-CWs than that in NP-CWs (Fig. 3). Moreover, phylum Planctomycetes was associated with anammox process (Ye and Thomas, 2001), and carbon sources had no effect on the community structure of AAOB (Feng et al., 2017). Therefore, phylum Planctomycetes was not the factor leading to the different denitrification performances in CWs. As shown in Fig. 5b, the top 10 classes were Betaproteobacteria (13.83–24.03%), Alphaproteobacteria (9.60–11.74%), Anaerolineae (6.23–10.72%), Bacteroidia (5.77–12.20%), Sphingobacteriia (4.93–10.08%), Planctomycetia (4.44–7.76%), Clostridia (3.60–9.33%), Gammaproteobacteria (3.96–7.07%), Actinobacteria (2.43–4.26%), and Deltaproteobact (2.08–3.05%), whose total sequence abundance accounted for 73.00–77.75%. The classes of Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria, which contained abundant nitrobacteria, anaerobic ammonia oxidizing bacteria (AAOB) and nitrite oxidizing bacteria (NOB), were the three major classes assigned to Proteobacteria (Fig. 5(b)) and they were the main participants in nitrogen removal in wastewater treatment system (Kumar and Lin, 2010). Betaproteobacteria which assigned to phylum Proteobacteria was the most dominant class in all the CWs. In CO-CWs, the relative abundance of Betaproteobacteria (24.03%) was remarkably higher than that in NP(17.17%), WS- (16.64%), PBS- (14.74%) and CK-CWs (13.83%), however, the class Anaerolineae (6.23%) and Planctomycetia (4.44%) in COCWs was shown lower relative abundance than other CWs. Besides, WSCWs showed predominance in Clostridia (9.33%) and Bacteroidia (12.20%). In general, the different solid carbon sources resulted in diverse bacterial community distribution both in phylum and class level. The taxonomic classification of five predominant phyla in different

3.7. Analysis of bacterial community structure The bacterial community structure at the phylum and class level was shown in Fig. 5(a) and (b). In all CWs, a total 36 phyla and 56 classes were identified from the anaerobic zone of CWs. Proteobacteria (31.14–45.85%), Bacteroidetes (17.54–20.58%), Chloroflexi (7.54–13.16%), Firmicutes (4.38–11.33%), and Planctomycetes (4.58–7.99%) were the top 5 phyla of 36 identified phyla and accounted for 75.83–83.11% of all the bacterial sequences. Proteobacteria, as the key dominant phylum in all CWs was showed the highest abundance in CO-CWs (45.85%) and followed by NP- (36.47%), WS(33.88%), PBS- (31.60%) and CK-CWs (31.14%) (Fig. 5(a)). It was reported that Proteobacteria was the dominant phylum contributing to denitrification under different water ecological conditions (Chen et al., 2017; Chen et al., 2018; Meng et al., 2017). Phylum of Bacteroidetes showed similar distribution in five types of CWs (Fig. 6(b)), and it is known as ubiquitous organic nutrient bacteria in a variety of aquatic environments and can degrade macromolecular organic compounds, such as cellulose, proteins, and lipids (Navarronoya et al., 2013). The relative abundance of Chloroflexi was higher in CK-CWs (13.16%) and PBS-CWs (13.02%) than other three CWs. Although nitrite oxidizing bacterium has been separated from Chloroflexi, the role of Chloroflexi in CWs had not been clearly reported (Sorokin et al., 2012). Bacteria involved in denitrification and cellulose degradation were identified in the phylum Firmicutes (Eichorst et al., 2013). Also, the present results showed that the OTUs of Firmicutes in WS-, CO-, and NP-CWs respectively accounted for 11.33%, 7.60% and 7.03% of the total OUTs. However, the proportions were respectively 4.38% and 5.70% in CKCWs and PBS-CWs (Fig. 6(d)). Consequently, the high relative abundance of Firmicutes may lead to better carbon source replenishment and 422

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Fig. 6. Taxonomic classification of five predominant phyla in different types of CWs. Average value of percentage indicates the relative abundance of different phyla, class, orders, families, and genera.

biodegradation and denitrification processes in the anoxic system (Shen et al., 2015a). Its significant enrichment (2.69%) in WS-CWs might be partly responsible for the high COD release and outstanding performance in denitrification. Genus of Levilinea which play an important role in carbohydrates metabolism and organic acids synthesis (Yamada et al., 2006) was enriched in NP- (1.02%) and WS-CWs (0.91%) (Fig. 6(c)). It was reported to produce hydrogen and acetate with carbohydrates and amino acids in anaerobic conditions (Yamada et al., 2007). The genus Saccharofermentans affiliated to the class Clostridia was the predominant genus in phylum Firmicutes (Fig. 6(d)), and it was also an important bacterium involved in the carbohydrate fermentation process (Chen et al., 2010). The relative abundance of

types of CWs was shown in Fig. 6. Dechloromonas and Thauera were enriched in CO- (3.92 and 2.35%, respectively), WS- (1.97 and 1.02%, respectively) and NP-CWs (1.71 and 1.31%, respectively), and the three types of CWs were filled with cellulose-rich solid carbon source. In contrast, the relative abundance of Dechloromonas and Thauera in PBSand CK-CWs was below 0.5% (Fig. 6(a)). It was reasonable to presume that Dechloromonas and Thauera were involved in cellulose biodegradation and denitrification (Chakraborty and Picardal, 2013; Ge et al., 2018; Mao et al., 2013). As shown in Fig. 6(b), Paludibacter was an abundant genus WS-CWs (2.69%), however, it was observed extremely low relative abundance in CK- (0.23%) and PBS-CWs (0.33%). Previous study reported that genus Paludibacter was involved in 423

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Saccharofermentans was significantly enriched in WS-CWs (3.14%), however, the other four CWs were observed with a relative abundance below 1.0%. Thus, it could be inferred that Saccharofermentans might be an important participant in anaerobic fermentation process of wheat straw.

source for denitrification by constructed wetland and bioreactor: review of recent development. Environ. Sci. Pollut. R. 23 (9), 8260–8274. Kumar, M., Lin, J.-G., 2010. Co-existence of anammox and denitrification for simultaneous nitrogen and carbon removal—Strategies and issues. J. Hazard. Mater. 178 (1), 1–9. Li, P., Zuo, J., Wang, Y., Zhao, J., Tang, L., Li, Z., 2016. Tertiary nitrogen removal for municipal wastewater using a solid-phase denitrifying biofilter with polycaprolactone as the carbon source and filtration medium. Water Res. 93, 74–83. Liu, L., Yu, J., Cheng, L., Yang, X., 2009. Biodegradability of poly(butylene succinate) (PBS) composite reinforced with jute fibre. Polym. Degrad. Stabil. 94 (1), 90–94. Luo, G., Li, L., Qian, L., Xu, G., Tan, H., 2014. Effect of dissolved oxygen on heterotrophic denitrification using poly(butylene succinate) as the carbon source and biofilm carrier. Bioresour. Technol. 171 (10), 152–158. Mao, Y., Yu, X., Tong, Z., 2013. Characterization of Thauera -dominated hydrogen-oxidizing autotrophic denitrifying microbial communities by using high-throughput sequencing. Bioresour. Technol. 128 (1), 703–710. Meng, H., Wu, R., Wang, Y.-F., Gu, J.-D., 2017. A comparison of denitrifying bacterial community structures and abundance in acidic soils between natural forest and revegetated forest of Nanling Nature Reserve in southern China. J. Environ. Manage. 198, 41–49. Mu, L., Su, Y., Chen, Y., Rui, W., Xiong, Z., Liu, K., 2016. The effects of fulvic acid on microbial denitrification: promotion of NADH generation, electron transfer, and consumption. Appl. Microbiol. Biotechnol. 100 (12), 5607–5618. Navarronoya, Y.E., Suárezarriaga, M.C., Rojasvaldes, A., Montoyaciriaco, N.M., Gómezacata, S., Fernándezluqueño, F., Dendooven, L., 2013. Pyrosequencing analysis of the bacterial community in drinking water wells. Microb Ecol. 66 (1), 19–29. Pan, Y., Ni, B.-J., Lu, H., Chandran, K., Richardson, D., Yuan, Z., 2015. Evaluating two concepts for the modelling of intermediates accumulation during biological denitrification in wastewater treatment. Water Res. 71 (Supplement C), 21–31. Prest, E.I., El-Chakhtoura, J., Hammes, F., Saikaly, P.E., Loosdrecht, M.C.M.V., Vrouwenvelder, J.S., 2014. Combining flow cytometry and 16S rRNA gene pyrosequencing: A promising approach for drinking water monitoring and characterization. Water Res. 63 (63), 179–189. Qiu, T., Liu, L., Min, G., Zhang, L., Tursun, H., Wang, X., 2016. Effects of solid-phase denitrification on the nitrate removal and bacterial community structure in recirculating aquaculture system. Biodegradation. 27 (2–3), 165–178. Shen, J., Chen, Y., Wu, S., Wu, H., Liu, X., Sun, X., Li, J., Wang, L., 2015a. Enhanced pyridine biodegradation under anoxic condition: the key role of nitrate as the electron acceptor. Chem. Eng. J. 277, 140–149. Shen, Z., Zhou, Y., Liu, J., Xiao, Y., Cao, R., Wu, F., 2015b. Enhanced removal of nitrate using starch/PCL blends as solid carbon source in a constructed wetland. Bioresour. Technol. 175, 239–244. Sorokin, D.Y., Lücker, S., Vejmelkova, D., Kostrikina, N.A., Kleerebezem, R., Rijpstra, W.I.C., Damsté, J.S.S., Paslier, D.L., Muyzer, G., Wagner, M., 2012. Nitrification expanded: discovery, physiology and genomics of a nitrite-oxidizing bacterium from the phylum Chloroflexi. ISME. J. 6 (12), 2245–2256. Spieles, D.J., Mitsch, W.J., 1999. The effects of season and hydrologic and chemical loading on nitrate retention in constructed wetlands: a comparison of low- and highnutrient riverine systems. Eco. Eng. 14 (1–2), 77–91. Volokita, M., Belkin, S., Abeliovich, A., Soares, M.I.M., 1996. Biological denitrification of drinking water using newspaper. Water Res. 30 (4), 965–971. Waki, M., Yasuda, T., Fukumoto, Y., Béline, F., Magrí, A., 2018. Treatment of swine wastewater in continuous activated sludge systems under different dissolved oxygen conditions: Reactor operation and evaluation using modelling. Bioresour. Technol. 250, 574–582. Wang, J., Chu, L., 2016. Biological nitrate removal from water and wastewater by solidphase denitrification process. Biotechnol. Adv. 34 (6), 1103–1112. Wang, J., Song, X., Wang, Y., Abayneh, B., Yi, D., Yan, D., Bai, J., 2016. Microbial community structure of different electrode materials in constructed wetland incorporating microbial fuel cell. Bioresour. Technol. 221, 697–702. Warneke, S., Schipper, L.A., Matiasek, M.G., Scow, K.M., Cameron, S., Bruesewitz, D.A., Mcdonald, I.R., 2011. Nitrate removal, communities of denitrifiers and adverse effects in different carbon substrates for use in denitrification beds. Water Res. 45 (17), 5463–5475. Wu, H., Zhang, J., Ngo, H.H., Guo, W., Hu, Z., Liang, S., Fan, J., Liu, H., 2015. A review on the sustainability of constructed wetlands for wastewater treatment: Design and operation. Bioresour. Technol. 175, 594–601. Yamada, T., Imachi, H., Ohashi, A., Harada, H., Hanada, S., Kamagata, Y., Sekiguchi, Y., 2007. Bellilinea caldifistulae gen. nov., sp. nov. and Longilinea arvoryzae gen. nov., sp. nov., strictly anaerobic, filamentous bacteria of the phylum Chloroflexi isolated from methanogenic propionate-degrading consortia. Int. J. Syst. Evol. Microbiol. 57 (10), 2299–2306. Yamada, T., Sekiguchi, Y., Hanada, S., Imachi, H., Ohashi, A., Harada, H., Kamagata, Y., 2006. Anaerolinea thermolimosa sp. nov., Levilinea saccharolytica gen. nov., sp. nov. and Leptolinea tardivitalis gen. nov., sp. nov., novel filamentous anaerobes, and description of the new classes Anaerolineae classis nov. and Caldilineae classis nov. in the bcterial phylum Chloroflexi. Int. J. Syst. Evol. Microbiol. 56 (Pt 6), 1331–1340. Yang, Z., Yang, L., Wei, C., Wu, W., Zhao, X., Lu, T., 2018. Enhanced nitrogen removal using solid carbon source in constructed wetland with limited aeration. Bioresour. Technol. 248 (Part B), 98–103. Ye, R.W., Thomas, S.M., 2001. Microbial nitrogen cycles: physiology, genomics and applications. Curr. Opin. Microbiol. 4 (3), 307–312. Zhang, Y., Wang, X.C., Cheng, Z., Li, Y., Tang, J., 2016. Effect of fermentation liquid from food waste as a carbon source for enhancing denitrification in wastewater treatment. Chemosphere 144 (42), 689–696. Zhao, J., Feng, C., Tong, S., Chen, N., Dong, S., Peng, T., Jin, S., 2017. Denitrification

4. Conclusion For the first time, newspaper was reported can intensify the biological heterotrophic denitrification process in constructed wetlands both in low- and high-temperature condition. Moreover, wheat straw allowed the high NO3−-N removal efficiency in high-temperature condition. Genus of Levilinea which play an important role in carbohydrates metabolism and organic acids synthesis was enriched in NP- (1.02%) and WS-CWs (0.91%). Furthermore, genus Paludibacter (2.69%) and Saccharofermentans (3.14%) showed high relative abundance in WSCWs. Classification results based on COG of bacterial communities indicated that NP-CWs showed the high similarity to WS-CWs whereas PBS-CWs were clustered together with CK-CWs. Acknowledgments This work was funded by the National Natural Science Foundation of China (Grant No. 51679041 and 41471089) and Science and Technology Commission of Shanghai Municipality Program (Grant No. 17DZ1202204). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.biortech.2018.07.029. References Akbari, S.Z., Naeimpoor, F., 2014. Enhanced heterotrophic denitrification: effect of dairy industry sludge acclimatization and operating conditions. Appl. Biochem. Microbiol. 173 (3), 741–752. Al-Omari, A., Fayyad, M., 2003. Treatment of domestic wastewater by subsurface flow constructed wetlands in Jordan. Desalination 155 (1), 27–39. Cameron, S.G., Schipper, L.A., 2010. Nitrate removal and hydraulic performance of organic carbon for use in denitrification beds. Ecol. Eng. 36 (11), 1588–1595. Chakraborty, A., Picardal, F., 2013. Neutrophilic, nitrate-dependent, Fe(II) oxidation by a Dechloromonas species. World. J. Microbiol. Biotechnol. 29 (4), 617–623. Chen, C., Xu, X.-J., Xie, P., Yuan, Y., Zhou, X., Wang, A.-J., Lee, D.-J., Ren, N.-Q., 2017. Pyrosequencing reveals microbial community dynamics in integrated simultaneous desulfurization and denitrification process at different influent nitrate concentrations. Chemosphere 171, 294–301. Chen, D., Wang, H., Yang, K., Ma, F., 2018. Performance and microbial communities in a combined bioelectrochemical and sulfur autotrophic denitrification system at low temperature. Chemosphere 193, 337–342. Chen, S., Niu, L., Zhang, Y., 2010. Saccharofermentans acetigenes gen. nov., sp. nov., an anaerobic bacterium isolated from sludge treating brewery wastewater. Int. J. Syst. Evol. Microbiol. 60 (12), 2735–2738. Cho, H.S., Moon, H.S., Kim, M., Nam, K., Kim, J.Y., 2011. Biodegradability and biodegradation rate of poly(caprolactone)-starch blend and poly(butylene succinate) biodegradable polymer under aerobic and anaerobic environment. Waste Manage. 31 (3), 475–480. Chu, L., Wang, J., 2011. Nitrogen removal using biodegradable polymers as carbon source and biofilm carriers in a moving bed biofilm reactor. Chem. Eng. J. 170 (1), 220–225. Dhamole, P.B., Nair, R.R., D'Souza, S.F., Lele, S.S., 2009. Simultaneous removal of carbon and nitrate in an airlift bioreactor. Bioresour. Technol. 100 (3), 1082–1086. Eichorst, S.A., Varanasi, P., Stavila, V., Zemla, M., Auer, M., Singh, S., Simmons, B.A., Singer, S.W., 2013. Community dynamics of cellulose-adapted thermophilic bacterial consortia. Environ. Microbiol. 15 (9), 2573–2587. Feng, Y., Zhao, Y., Guo, Y., Liu, S., 2017. Microbial transcript and metabolome analysis uncover discrepant metabolic pathways in autotrophic and mixotrophic anammox consortia. Water Res. 128, 402–411. Ge, C.H., Sun, N., Kang, Q., Ren, L.F., Ahmad, H.A., Ni, S.Q., Wang, Z., 2018. Bacterial community evolutions driven by organic matter and powder activated carbon in simultaneous anammox and denitrification (SAD) process. Bioresour. Technol. 251, 13–21. Ge, S., Peng, Y., Wang, S., Lu, C., Cao, X., Zhu, Y., 2012. Nitrite accumulation under constant temperature in anoxic denitrification process: the effects of carbon sources and COD/NO(3)-N. Bioresour. Technol. 114 (3), 137–143. Hang, Q., Wang, H., Chu, Z., Ye, B., Li, C., Hou, Z., 2016. Application of plant carbon

424

Bioresource Technology 267 (2018) 416–425

Z. Si et al.

emission. Bioresour. Technol. 186, 44–51. Zumstein, M.T., Kohler, H.E., Mcneill, K., Sander, M., 2015. Enzymatic hydrolysis of polyester thin films: real-time analysis of film mass changes and dissipation dynamics. Environ. Sci. Technol. 50 (1), 197–206.

behavior and microbial community spatial distribution inside woodchip-based solidphase denitrification (W-SPD) bioreactor for nitrate-contaminated water treatment. Bioresour. Technol. 249, 869–879. Zhu, S., Zheng, M., Li, C., Gui, M., Qian, C., Ni, J., 2015. Special role of corn flour as an ideal carbon source for aerobic denitrification with minimized nitrous oxide

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