Effects of extracellular polymeric substances and microbial community on the anti-scouribility of sewer sediment

Science of the Total Environment 687 (2019) 494–504

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Effects of extracellular polymeric substances and microbial community on the anti-scouribility of sewer sediment Daizong Meng a,c,e, Jun Wu a,c,e,1, Keli Chen b, Huaizheng Li a,c,e,⁎, Wei Jin a,c,d,e, Shuzhen Shu a,d, Jin Zhang f a

College of Environmental Science and Engineering, Tongji University, 200092 Shanghai, China Urban & Rural Construction Design Institute CO, LTD, 310020 Hangzhou, China Key Laboratory of Yangtze River Water Environment, Ministry of Education, Tongji University, 200092 Shanghai, China d State Key Laboratory of Pollution Control and Resource Reuse, Tongji University, 200092 Shanghai, China e Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China f Institute of Groundwater and Earth Sciences, Jinan University, 510632 Guangzhou, China b c

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• The distribution of anti-scouribility of sewer sediment is regulated. • The EPS and microbial communities affect the anti-scouribility. • Bacteroidetes and Firmicutes cause the difference of anti-scouribility.

a r t i c l e

i n f o

Article history: Received 13 March 2019 Received in revised form 23 May 2019 Accepted 25 May 2019 Available online 30 May 2019 Editor: Jay Gan Keywords: Anti-scouribility Sewer sediments Extracellular polymeric substances Microbial community

a b s t r a c t Sewer sediment is the main source of overflow pollution, and the anti-scouribility of sewer sediment directly determines the amount of the discharged contaminants. In this study, sewer sediments of different depths were collected from combined and storm sewers in Shanghai, China. The anti-scouribility, represented by the shear stress of each layer of sewer sediment, was detected in situ. The microbial community and extracellular polymeric substances (EPS), including carbohydrates and proteins present in the sewer sediments were characterized. The results indicated that the distribution of the anti-scouribility of sewer sediment is regulated. There were positive correlations between the content of EPS, proteins, and carbohydrates, and the anti-scouribility of sediments (Pearson Corr. = 0.604, sig. = 0.219; Pearson Corr. = 0.623, sig. = 0.234; Pearson Corr. = 0.727, sig. = 0.359, respectively). Furthermore, the microbial community had a positive influence on anti-scouribility. In particular, the gram-positive bacterial phyla of Bacteroidetes and Firmicutes may be important and influential for the improvement of anti-scouribility of sediment owing to their production of cellulose. © 2019 Elsevier B.V. All rights reserved.

1. Introduction ⁎ Corresponding author at: College of Environmental Science and Engineering, Tongji University, 200092 Shanghai, China. E-mail address: [email protected] (H. Li). 1 Co-first author.

https://doi.org/10.1016/j.scitotenv.2019.05.387 0048-9697/© 2019 Elsevier B.V. All rights reserved.

The urban drainage system is an important part of the municipal water system (Kaeseberg et al., 2018a). The long-term use of a drainage system inevitably leads to sediment deposition in sewers, which

D. Meng et al. / Science of the Total Environment 687 (2019) 494–504

decreases the capacity of drainage systems and causes pipeline corrosion (Wang et al., 2019). Ahyerre et al. (2000) found that 30 % of the particles in sewage eventually settle as a part of sediments, causing siltation of the sewer; similarly, Ávila et al. (2013) found serious siltation in southern Spain and confirmed this conclusion. In addition to decreasing the drainage capacity, sewer sediments cause pollution problems (Kaeseberg et al., 2018b). Specifically, during wet-season periods, a large amount of pollutants such as antibiotics, heavy metals, and other organic materials accumulated in the sewer sediments, which are not naturally present in water, are eroded and discharged into the receiving water, consequently threatening the aquatic environments (Fan et al., 2018; Jing et al., 2019; Kaeseberg et al., 2018c; Liu et al., 2015b; Liu et al., 2016; Zhang et al., 2019). It has been reported that approximately 80% of the pollutants discharged by combined drainage overflows (CSOs) come from the sewer sediments (Li et al., 2019a; Liu et al., 2015a). Therefore, controlling the amount of sewer sediments in the drainage system is a global challenge and the analysis of sewer sediment provides valuable information for the control of the overflow pollution (Xu et al., 2018a). Sewer sediment has been the focus of many investigations, and many researchers have studied methods to analyse and control sediment contaminants (Chen et al., 2017). However, there are fewer studies related to the assessment of anti-scouribility. Anti-scouribility is an important aspect in the control of pollution caused by sewer sediments because it determines the amount of sediment contaminants that will be washed into the receiving water during wet weather (Khozani et al., 2017a; Khozani et al., 2018). Vardy et al. (2007) found that the hydraulic erosion resistance of consolidated clay was increased by more viscous substances. This is therefore applicable to sewer sediments. Celestini et al. (2007) studied the motion characteristics of different types of viscous sediments and demonstrated that viscous substances improved the anti-scouribility of sewer sediments, providing a theoretical basis for sewer design. Extracellular polymeric substances (EPS), considered as a “city of microbes” (Flemming and Wingender, 2010), are commonly considered as a type of viscous substance in studies focusing on biofilms, water retention, and activated sludge (Adessi et al., 2018; Desmond et al., 2018a; Hou et al., 2015). It was found that EPS were able to protect the microbial community from adverse conditions (Bridier et al., 2014), and could affix microorganisms and organic matter onto the wall of the sewer, thereby preventing erosion (Chebbo et al., 2013; Rocher et al., 2003). However, few studies have shown a direct correlation between EPS and the antiscouribility of sewer sediments, and the impact of certain components of EPS on anti-scouribility has not been determined. Additionally, the microbial community is an important factor in sewer sediments and it was found that microorganisms in sewer sediments exhibit considerable biological activity (Harvey and Mcbean, 2015; Hvitved-Jacobsen et al., 2002a; Zhang et al., 2008). However, studies have reported that bacteria constitute only 5% to 20% of organic compounds in flocs (CydzikKwiatkowska and Zielinska, 2016), and EPS drives the construction of the biofilm morphology, which plays an important role in determining its mechanical response to hydraulic shear stress (Desmond et al., 2018b; Ebrahimi et al., 2005; Gerbersdorf et al., 2009). Nonetheless, certain studies have shown that bacterial strains can efficiently resist wetting by water and oils; thus, wetting the biofilm is necessary to remove the biofilm (Garcia et al., 2019; Kobayashi and Iwano, 2012; Werb et al., 2017). Moreover, the growth of bacteria increased the secretion of EPS and the microbial community significantly influenced EPS synthesis and degradation (Choi et al., 2002; Gao et al., 2013; Meng et al., 2006; Zhang et al., 2015a). In addition, external chemical and biological factors influence bacterial development, which subsequently influence the secretion of EPS and the resistance of biofilm (Hubas et al., 2010). From these studies, it appears that EPS, a viscous secretion of the microbial community, may have a positive effect on the anti-scouribility of sewer sediments and the microbial community is positively related to the improved resistance of sewer sediments.

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Therefore, our study investigated the following aspects: (1) the characterization of the anti-scouribility of sewer sediments; (2) the relationship between EPS, proteins, and the anti-scouribility of sewer sediments; (3) the characterization of the microbial community in sewer conditions, and (4) the relationship between the microbial community and anti-scouribility of sewer sediments. 2. Materials and methods 2.1. Study area The city of Shanghai is the home to approximately 24,000,000 inhabitants and is located on the east coast of China. A Shanghai government report from 2017 stated that N30% of drainage pipelines located in Hong Kou District, Chang Ning District, and Yang Pu District had the problem of blockage. Therefore, the 10 sampling points were selected from these areas (Table S1). 2.2. Determination of anti-scouribility of sewer sediments Anti-scouribility is the ability of sediment to resist the scour of flow, which is represented by shear stress. Therefore, the shear stress required to scour the sediment completely was considered to represent the anti-scouribility of sediments. In the current study, the antiscouribility of sewer sediment was measured by the Cohesive Strength Meter MK IV (CSM, Partrac company) and calculated from Eq. (1) (Nardi and Rinaldi, 2013).    1 0 0 P P − −
 B B C τ0 N=m2 ¼ 66:6734  @1−e 310:09433 −195:27552  @1−e 1622:56738 A

ð1Þ

P—injecting intensity, kPa; τ0—shear stress, N/m2; This equation transforms the injecting intensity of flow scouring toward the surface of sediments into a shear stress; the Mud7 model was used and the specific parameters are shown in Table S2. The construction and principium of the measure were based on a previous study (Vardy et al., 2007). The detection of anti-scouribility and sample collection was performed in June 2018. Sediments from combined and storm sewers were collected separately. Owing to municipal maintenance in the combined sewers of Shanghai, only three samples could be obtained from the combined sewers; however, these samples were representative as they were all obtained from populated areas. The following four categories of pipe diameters were considered in this study: small, medium, large, and extra-large. The diameter of each category and the location of each sample are shown in Table S1. The naming scheme for the samples is shown in Fig. S1. Furthermore, several practical steps were put in place. Firstly, the water in the sewer was drained, and the detection of anti-scouribility was conducted immediately after the drainage to avoid changes in the microbial community that normally occur shortly after the environment changes. Secondly, since it was not possible for a person to enter the small and middle diameter sewers, anti-scouribility was assessed 20 cm away from the upstream pipe orifice. Additionally, at a same distance away from the upstream pipe orifice, replicate samples were obtained from three paralleled regions. Thirdly, due to the difference in the thickness of sewer sediment from different sewers and the aim to compare the anti-scouribility and chemical and biological factors of sediments from different depths, the sediment was separated into different layers based on depth. The thickness of each layer was 5 cm and the

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sediments were ordered from the surface to the bottom; the first layer was the surface layer and the last layer was the bottom layer. Finally, the determination of anti-scouribility of each layer of sediments was measured before the collection of each layer of sample for chemical and biological analysis, because the collection process altered the structure of the sediment, which would influence the anti-scouribility of the sediment. 2.3. Sampling methods In practice, sampling was conducted after the detection of antiscouribility for each layer of sewer sediment. During the collection, a suction device, comprising a peristaltic pump and polyethylene tube, was used for the collection of each layer to avoid blending sewer sediment from different layers. A schematic diagram of the sampling device is shown in Fig. S2. After collection, the samples were mixed and stored on ice in polypropylene containers to control the temperature to below −4 °C until the sample was delivered to the laboratory (Xu et al., 2018b). The samples were separated into three equal portions to create three biological replicates; all were stored below −80 °C to prevent alteration of the microbial community. The remaining parts of each sample were separated into three equal sections and two were processed as replicates for the chemical analysis. 2.4. Chemical analysis The chemical analyses were conducted by the State Key Laboratory of Pollution Control and Resource Reuse in Shanghai. 2.4.1. Extraction of extracellular polymeric substances Twenty grams of sediment was mixed with NaCl (0.05%, 10 ml) and extracted by high-speed centrifugation (5000 ×g for 15 min). The extracted solutions were then treated with formaldehyde (36.5%, 0.3 ml) and NaOH (1 mol/l, 20 ml) for 3 h under continuous stirring (900 rpm). The solutions were extracted by high-speed centrifugation (2000 ×g for 20 min). The extracted residues in the solution were removed by dialysis (0.45 μm membrane) before treatment. Finally, EPS was determined in units of mg/gVSS (Liu and Fang, 2002). 2.4.2. Protein detection The concentration of protein in EPS was measured by the modified Lowry method using a BCA protein kit (Gosset et al., 2016). Two replicate measurements were conducted, and 2 ml EPS was used for each test. 2.4.3. Carbohydrate detection The concentration of carbohydrates in EPS was measured by the phenol-concentrated sulfuric acid method (Xi et al., 2010). EPS was mixed with phenol (5%) and concentrated sulfuric acid and heated (40 °C for 30 min). Two replicate measurements were conducted and 2 ml EPS was used for each test.

2.6. Microbial diversity analysis The biological analysis in this study was conducted by Majorbio (http://www.majorbio.com/) who used I-sanger (https://www.isanger.com/) as the analytical platform.

2.6.1. DNA extraction and polymerase chain reaction (PCR) amplification The Fast DNA Spin Kit for Soil (MP Bio Company) was used for microbial DNA extraction from the sediments. The V4–V5 region of the bacterial 16S ribosomal RNA gene was amplified by PCR (95 °C for 3 min; followed by 25 cycles of 95 °C for 30 s, 55 °C for 30 s, 72 °C for 30 s; and a final extension at 72 °C for 10 min). This process used the primers 338F 5′-barcode-ACTCCTACGGGAGGCAGCA)-3′ and 806R 5′GGACTACHVGGGTWTCTAAT-3′, where the barcode was an eight-base sequence unique to each sample (Zhang et al., 2018). PCR was performed in triplicate with a 20 μl mixture containing 4 μl of 5× FastPfu Buffer, 2 μl of 2.5 mM dNTPs, 0.8 μl of each primer (5 μM), 0.4 μl of FastPfu Polymerase, and 10 ng of template DNA.

2.6.2. Illumina MiSeq sequencing The Illumina MiSeq sequencing platform was used to generate read lengths of up to 2 × 300 bp. Amplicons were extracted from 2% agarose gels, purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA), and quantified by using QuantiFluor™ST (Promega, USA). Purified amplicons were pooled in equimolar amounts and pair-end sequenced (2 × 250) on an Illumina MiSeq platform in accordance with the standard protocols (Tian et al., 2017). The raw reads were deposited into the NCBI Sequence Read Archive database SRR9039964SRR9040000 and there are 37 samples).

2.6.3. Processing of sequencing data Raw fast files were demultiplexed and quality-filtered using QIIME (version 1.9.1) according to the following criteria: (i) the 300 bp reads were truncated at any site receiving an average quality score below 20 over a 50 bp sliding window, discarding the truncated reads that were shorter than 50 bp; (ii) exact barcode matching: two nucleotide mismatches in primer matching and reads containing ambiguous characters were removed, and (iii) only sequences that overlap for N10 bp were assembled according to their overlap sequence. The reads that could not be assembled were discarded. Operational taxonomic units (OTUs) were clustered with a 97% similarity cut-off using UPARSE (Edgar, 2013) (version 7.1, www.drive5. com/uparse). The chimeric sequences were identified and removed by using UCHIME (Edgar et al., 2011). The taxonomy of each 16S rRNA gene sequence was analysed by using RDP (Cole et al., 2009; Wang et al., 2007) classified (www.rdp.cme.msu.edu) against the SILVA (SSU123) 16S rRNA database, with a confidence threshold of 70% (Amato et al., 2013).

2.5. Three-dimensional excitation emission matrix (3-DEEM)

2.7. Statistical analysis

Before detection, EPS was filtered through a 0.45 μm membrane. Two replicate measurements were conducted, and 3 ml EPS was used for each test. A fluorescence spectrometer (HORIBA) was used to determine the content of organic components. Pure water (Milli-Q) was used as the reference sample. The analysis was conducted in a 1 cm fluorescence cell using synchronous scanning mode. The colorimetric slit width was 5 nm, the excitation wavelength range was 250–450 nm, the emission wavelength range was 300–550 nm, the scanning interval was 5 nm, and the scanning speed was 1200 nm/min. The maximum peak intensity range was 1000 A.U.

Statistical analysis was computed by using the software OriginPro2018bit (Origin Pro Lab Corp., Northampton, MA, USA). The Pearson correlation coefficient (Rp) was used to evaluate linear correlation (Li et al., 2019b). The confidence interval (Pearson Corr.) was used to indicate the degree of correlation and the term Sig. was used to indicate a statistically significant difference. The measurements were expressed in terms of mean value. The Pearson coefficient is between −1 and 1, where −1 denotes a perfect negative correlation and 1 denotes a perfect positive correlation; 0 indicates the absence of a relationship.

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3. Results and discussion

3.2. The distribution of EPS and its components in sewer sediments

3.1. Anti-scouribility of sewer sediment

The EPS, protein, and carbohydrate content are illustrated in Fig. 2 (a)–(c). ‘Bulk’ reflects the general content of different sized fractions.

The anti-scouribility of each layer of sewer sediment in different sewers is shown in Fig. 1. ‘Bulk’ reflects the anti-scouribility of different sized fractions.

3.1.1. The anti-scouribility of combined sewer sediment In the combined sewers, the anti-scouribility range of sediment was 0.97–2.22 N/m2; the first layer of CM-05 had the lowest anti-scouribility and the third layer of CL-11 had the highest shear stress. The average anti-scouribility of sediment in combined sewers was 1.45 N/m2. This result is higher than the results predicted by the entropy model of Amin et al. (2018), who predicted an anti-scouribility range of 0.6–0.8 N/m2. The reason for this difference appears to be that the sewers studied by Amin et al. were open channels and the sewer diameter in our study was smaller. In addition, as shown in Fig. 1, for most of the combined sewers, the sediment at a deeper depth had a higher antiscouribility and tended to increase in an almost regular manner, as seen in CL-11. Furthermore, it appears that the anti-scouribility of the same ordinal layer in the larger diameter sewer was higher than that in the smaller diameter one. These trends are consistent with those predicted by models regarding the relationship between the sewer diameter and the depth and anti-scouribility of sediments. This indicated that for combined sewers, sediments from deeper layers or larger diameter sewers are more stable and resistant to water erosion (Bareš et al., 2008; Najafzadeh et al., 2017; Perrusquía et al., 1995).

3.1.2. The anti-scouribility of storm sewer sediment In the storm sewers, the anti-scouribility range of sediment was 0.55–1.93 N/m2, with an average of 0.94 N/m2. The lowest shear force was 0.55 N/m2, found in the second layer of RL-01, whereas the highest anti-scouribility was 2.22 N/m2, found in the third layer of CL-11. This result was similar to the predictions based on gene expression programming (Khozani et al., 2017b), who predicted an anti-scouribility range of 0.8–1.2 N/m2, and the parameter of the depth of water in the sewer is based on the data from storm sewers, which appears to be the reason for the similarity. In addition, as shown in Fig. 1, it can be noted that in almost all sewers, an increase in the depth of sediment was correlated with a decrease in anti-scouribility, as clearly shown in RM-07. This was different from the result of combined sewers, in which anti-scouribility increased as the depth increased. Furthermore, in terms of the relationship between diameter and anti-scouribility, there were no clear trends.

3.2.1. The distribution of EPS and its components in combined sewer sediments For the combined sewers, the EPS content was 2.5–7.1 mg/gVSS, with an average of 9.1 mg/gVSS. The protein content ranged from 1.5 to 14.0 mg/gVSS, with an average of 6.5 mg/gVSS. The carbohydrate content ranged from 0.5 to 5.9 mg/gVSS, with an average of 2.2 mg/gVSS. These results were lower than the previously detected concentrations of EPS and its components in the biofilm of the membrane bio-reactor (Bales et al., 2013; Wu et al., 2018). This indicates that although it was found that microorganisms in sewer sediments have strong biological activity (Hvitved-Jacobsen et al., 2002b; Shrestha et al., 2017), EPS secretion by microorganisms in sewer sediment was less than the secretion from a biofilm in a membrane bioreactor (Hvitved-Jacobsen et al., 2002a; Wang et al., 2010). Furthermore, the concentration of EPS and its components detected in this study were higher than those extracted from dewatered sludge (Wu et al., 2018). In their study, the concentration of EPS was 12.3–15.1 mg/gVSS, which was explained in their report that dewatering altered the structure of EPS of sludge and the majority became soluble. As shown in Fig. 2(a) and (b), EPS content was higher in sewers with a large diameter, but the EPS content in smaller sewers was higher than that in the medium diameter sewers, which suggested that there was no clear relationship between the diameter and the concentration of EPS in sediments. The alteration in the trend of protein with diameter was also not apparent for combined sewers. However, in each sewer type, as the depth of sediment increased, there was an increase in the concentration of EPS and protein. In addition, Fig. 2(c) shows that there appeared to be more carbohydrate in sewers with a large diameter and this trend was more obvious than the variation of EPS and protein along the diameter of sewer. In each sewer type, the carbohydrate content increased with the increasing depth of the sediment; this was not evident in all layers of the samples, but still more evident than the regulation of the distribution of protein and EPS. An explanation for the distribution pattern of EPS may be the presence of more nutrients and a low-intensity current (Möderl et al., 2012) that are suitable for the growth of microorganism. Therefore, microbial communities on the surface or living near the nutrients from sewage grow faster than those in deeper layers (Wu et al., 2018; Yin et al., 2019). Thus, the microorganisms living near the surface turn into a stationary phase more quickly. With the growth of

Fig. 1. The anti-scouribility of each layer of each sample.

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Fig. 2. (a) is the concentration of EPS in each layer of each sample; (b) is the concentration of protein in each layer of each sample; (c) is the concentration of carbohydrate in each layer of each sample.

microorganism during the stationary phase, less EPS would be produced by the microbial community (Das and Mathew, 2011; Sheng and Yu, 2006; Sheng et al., 2006), so less EPS is secreted in the surface layers. Protein is the main component of EPS, and both enzymes and structural proteins are present in EPS, indicating that the secretion of protein is related to the secretion of EPS (Flemming and Wingender, 2010; Horan and Eccles, 1986). As a result, the protein distribution is consistent with the distribution of EPS in sewer sediment. For the combined sewers, with the mature and stable biofilms are attached to sediments, more carbohydrate lyase is present, which in turn reduces the carbohydrate content of EPS (Aquino and Stuckey, 2004; Laspidou and Rittmann, 2002; Padman et al., 2014), so it appears that there will be more carbohydrate lyase in surface layer, resulting in less carbohydrate content compared with the deeper layers.

3.2.2. The distribution of EPS and its components in storm sewer sediment As shown in Fig. 2(a)–(c), for storm sewers, the EPS content of sediment in storm sewer was 3.0–42.4 mg/g VSS, with an average of 17.7 mg/g VSS. The range of protein was 1.6–41.8 mg/gVSS, with an average of 15.9 mg/gVSS. The range of the carbohydrate content of sediment was 0.5–2.5 mg/gVSS, with an average of 1.7 mg/gVSS. These results were similar to the detection of EPS in anaerobic sludge (Zhen et al., 2017). Xu et al. (2017b) reported that the oxygen content in storm sewers was lower than that in combined sewers owing to the fact that during the wet weather, rainwater fills the sewer, allowing less space for air. This can explain the similarity described above. Furthermore, the intensity of water flow in storm sewers is much higher than that in combined sewers and it is accepted that adverse conditions increase the secretion of EPS. This can explain the higher content of EPS in storm sewers than combined sewers (Fang et al., 2018; Xavier and Foster, 2007). As shown in Fig. 2(a) and (b), a higher content of EPS and protein was generally found in sediments from sewers with a large diameter, except for RL-01 and RL-02, with fewer layers compared with the other samples. In addition, for each sewer, there was typically more EPS in the surface layers, although this was not obvious in RL-06 and RX-10. However, for RL-06 and RX-10, although there was more EPS in deeper layers, EPS tended to decrease from the first layer to the second layer, the third layer to the fifth layer, and several other sequenced layers. In addition, as shown in Fig. 2(b), in each sewer, the carbohydrate content decreased with an increase in the depth of the sediment; although some of the carbohydrate content in the deeper layers are a little higher than the previous layer, a regular distribution of carbohydrate is still more evident than for EPS and protein. Furthermore, there was more carbohydrate in sewers with a larger diameter, instead of RL-01 and RL-02, in which there were fewer layers compared with other samples.

In storm sewers, there is a higher-intensity water scour (Defilippi and Shih, 1971; Möderl et al., 2012), and continuous high-intensity water scour leads to more EPS because microorganisms secrete more EPS to protect cell membranes and cells (Adav et al., 2008; Shin et al., 2000). Thus, the microbial community living near the surface of sewer sediment influenced by scouring of rainwater will secrete more EPS. Moreover, it is reported that in adverse conditions, there will be more structural proteins secreted by microorganisms and it has been demonstrated that this protein helps to maintain the stability of EPS, which is necessary to improve the anti-scouribility of sewer sediment (Neu et al., 2010; Neu and Lawrence, 2014; Tawakoli et al., 2017). In addition, carbohydrates are able to enhance the adhesiveness of viscous EPS and for the storm sewer, there is research to indicate that high-intensity current scouring increases the secretion of carbohydrates and improves the adherence of EPS (Ramasamy and Zhang, 2005; Wang et al., 2013). These factors appear to support the distribution of EPS in storm sewer found in this study. 3.2.3. 3-DEEM analysis EEM spectroscopy is a sensitive technique that can selectively characterise dissolved organic matter, especially fluorescence substances.

Fig. 3. the represent example of three-dimensional fluorescence pattern of EPS in sewer sediment of combined sewer. Peak A: Ex/Em = 275 nm/310 nm, tyrosine peak; peak B: Ex/Em = 275 nm/340 nm, tryptophan peak; peak C: Ex/Em = 200–250 nm/380–440 nm, fulvic acid peak; Peak D: Ex/Em = 310–340 nm/350–450 nm, humic acid peak; and peak E: Ex/Em = 340–370 nm/420–450 nm, hydrophobic acid.

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For all samples from both sewer types, similar peaks were found, as shown in Fig. 3, which contains five peaks. These results were different from the detection of EPS in activated sludge (Wei et al., 2017; Yang et al., 2018). In these studies, peaks for humic acid and fulvic acid, considered as soluble EPS and loosely bound EPS (LB-EPS), respectively, were high intensity. This implied that soluble EPS and loosely bound EPS in sewer sediment were at a low concentration. However, the concentrations of fulvic acid and humic acid were similar to those found in the EPS of activated sludge. This indicated that soluble EPS and loosely bound EPS have similar concentrations and this was consistent with the research of Zhang (2014). Moreover, the fluorescence intensity of peak A (tyrosine) and peak B (tryptophan) were significantly higher

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than the other peaks, suggesting that the concentration of tyrosine and tryptophan in EPS was relatively high in both sewer types. It has been reported that tyrosine and tryptophan can promote cell aggregation and enhance the stability of small particles in sediment (D'Abzac et al., 2010), indicating that they are main substances in EPS that positively affect sediment anti-scouribility. 3.3. The relationship between EPS, protein, carbohydrate, and the antiscouribility of sewer sediment As shown in Fig. 4(a)–(f), for both storm and combined sewers, respectively, anti-scouribility was positively correlated with EPS (R2 =

Fig. 4. (a) The relationship between the concentration of EPS and anti-scouribility (expressed as shear stress) of sewer sediment from combined sewer. (b) The relationship between the concentration of EPS and anti-scouribility (expressed as shear stress) of sewer sediment from storm sewer. (c) The relationship between the concentration of protein and anti-scouribility (expressed as shear stress) of sewer sediment from combined sewer. (d) The relationship between the concentration of protein and anti-scouribility (expressed as shear stress) of sewer sediment from storm sewer. (e) The relationship between the concentration of carbohydrate and anti-scouribility (expressed as shear stress) of sewer sediment from combined sewer. (f) The relationship between the concentration of carbohydrate and anti-scouribility (expressed as shear stress) of sewer sediment from storm sewer.

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0.67, 0.51), protein (R2 = 0.68, 0.53), and carbohydrate (R2 = 0.82, 0.67). The correlation analysis among two systems shown in Table S3 indicates that there was moderate correlation (Pearson Corr. = 0.604, sig. = 0.219) between anti-scouribility and EPS, moderate correlation (Pearson Corr. = 0.623, sig. = 0.234) between anti-scouribility and protein, and strong correlation (Pearson Corr. = 0.727, sig. = 0.359) between anti-scouribility and carbohydrate. Furthermore, according to Fig. 5(a) and (b), the variation in antiscouribility was significantly influenced by carbohydrate, protein, and EPS and the relationship between depth, diameter, EPS, protein, carbohydrate, and anti-scouribility for the two systems supports the results presented in Figs. 1 and 2(a)–(c). These results were in agreement with the reports that EPS, as a viscous substance, has a key role in the aggregation of microorganisms and the protection of microbial membranes from adverse environmental conditions, including shear force (Rocher et al., 2003; Seco et al., 2014). Furthermore, the adsorption and deposition of EPS on solid surfaces are affected by the interaction energies between the constituents of EPS and a solid surface, which can be predicted by implementing Derjaguin-Landau-Verwey-Overbeek (DLVO) theory (Ying et al., 2010). This theory indicates that EPS can trap colloidal particles. It was reported that most of the small particles in sewer sediment are embedded by organic substances, and that their characters were similar to colloidal particles (Xu et al., 2017a). Therefore, if more small particles trapped by the EPS, the anti-scouribility of sewer sediments will be increased. In addition, Sweity et al. (2011) reported that a high solid retention time (SRT) renders the microbial community to produce more EPS as a viscous substance to trap particles and sludge in reactors, which indicates that in sewers, long term siltation results in more EPS, which enhances the anti-scouribility of sediment. This was consistent with Figs. 1 and 2, which show that the content of EPS and antiscouribility in deeper layers of combined sewer sediments was higher than the surface layers. Protein, as a component of EPS, is able to support the EPS structure and improve the anti-scouribility of sewer sediment (Neu and Lawrence, 2014). Apart from supporting the structure, there are other exoenzymes in EPS, which are proteins that promote cell aggregation and maintain the stability of cells (Flemming et al., 2007; Flemming and Wingender, 2010; Neu and Lawrence, 2014); thus, proteins are the main ingredient of EPS required to maintain the antiscouribility of sewer sediment. This was consistent with the results of

three-dimensional fluorescence spectroscopy. Furthermore, the structure of EPS is consolidated by neutral carbohydrates and hydrophobic carbohydrates have an important role in improving the adsorption capacity of EPS (Adav et al., 2008; Shin et al., 2000). In addition, it is reported that the presence of carbohydrates in EPS enhance the ionic strength, which is the main force causing the adhesiveness of EPS (Frank and Belfort, 2003; Sharma and Sarkar, 2013), which indicates that carbohydrates play a significant role in forming the viscidity of EPS and improving the anti-scouribility of sewer sediments.

3.4. Microbial community composition and diversity It is widely acknowledged that the microbial community is an important part of sewer sediments (Santo Domingo et al., 2011). To analyse the relationship between anti-scouribility and microbial community in sewer sediments, sequence abundance, microbial diversity, and microbial species composition were determined for each sample in this study, and the differences between each group were analysed.

3.4.1. Microbial community abundance and diversity A total of 1,647,373 effective sequences and 4964 OTUs were obtained after 16S RNA sequencing. The OTUs and bacterial diversity of the combined and storm sewer samples are shown in Table 1. Since the results of different layers of each sample are similar, 10 average results of the layers in 10 samples are presented. The Chao index and the Shannon-Wiener index indicate greater diversity and abundance in larger diameter sewers. It was reported that the presence of biofilm attached to sediments composed of a microbial community enhanced the anti-scouribility of sediments (Fish and Boxall, 2018; Lau and Droppo, 2000; Zhang et al., 2015b). This was supported by the moderate correlation (Pearson Corr. = 0.413, sig. = 0.361) between antiscouribility and diameter. Considering the similarity of diversity, the abundance of the microbial community among different layers, and the regulated distribution of anti-scouribility among layers of sediment, it appears that EPS, protein, and carbohydrate, are the most important substances regulating the distribution, instead of the microbial community.

Fig. 5. (a) Principal component analysis of the anti-scouribility (expressed as shear stress), the concentration of EPS, protein and carbohydrate, depth of sewer sediment from combined sewers and sewer diameter for combined sewers. (b) Principal component analysis of the anti-scouribility (expressed as shear stress), the concentration of EPS, protein and carbohydrate, depth of sewer sediment from storm sewers and sewer diameter of storm sewers.

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Table 1 Diversity index (average ± standard deviation). Sample

Read number

OTUs (97%)

CS-04 CM-05 CL-11 RS-08 RL-01 RL-02 RM-07 RM-09 RL-06 RX-10

27391 27391 27391 27391 27391 27391 27391 27391 27391 27391

4121 4223 4357 4774 4646 4430 4881 4649 4254 3947

Chao (97%) 2648.84 ± 79.48 2741.53 ± 76.47 2778.45 ± 81.26 2771.29 ± 104.84 2935.14 ± 101.79 2948.46 ± 96.74 2857.11 ± 93.42 2844.19 ± 87.56 2997.33 ± 86.43 2857.39 ± 115.75

3.4.2. Microbial community composition To specifically analyse the diversity of the microbial community, the composition of the microbial community was investigated and the top 20 major species in each sediment sample are shown in Fig. 6(a). Proteobacteria, Bacteroidetes, and Firmicutes were abundant in all samples, which was consistent with the findings of Santo Domingo et al. (2011). Furthermore, the results indicate that there were differences between different layers of each sample, but the differences did not follow a pattern. To show these differences more clearly, the Bray-Curtis method was used to analyse the differences in the microbial community of each layer of samples, as shown in Fig. 6(b). From this figure, it can be determined that the difference between layers of the same sample was not evident or uniform, which was consistent with the observations presented in Fig. 6(a). This implied that the microbial community was not the cause of the difference of anti-scouribility according to depth, which was consistent with conclusion stated in Section 3.4.1. However, as shown in Fig. 6(b), there was a clear difference between samples obtained from combined and storm sewers. Considering the difference in anti-scouribility between the sediments from combined and storm sewers shown in Fig. 1, and the moderate and positive correlation (Pearson Corr. = 0.537, sig. = 0.341) between anti-scouribility and the type of sewer, it was necessary to determine whether the difference and moderate correlation were related to the microbial community. Thus, a group difference analysis was conducted for sediment samples from combined sewers and storm sewers.

Shannon-Wiener (97%)

Coverage (97%)

5.84 ± 0.10 5.73 ± 0.11 5.97 ± 0.13 5.71 ± 0.12 5.91 ± 0.14 5.93 ± 0.19 5.73 ± 0.13 5.79 ± 0.15 5.95 ± 0.16 5.87 ± 0.12

0.981 ± 0.001 0.982 ± 0.001 0.984 ± 0.001 0.980 ± 0.001 0.979 ± 0.001 0.981 ± 0.001 0.978 ± 0.001 0.983 ± 0.001 0.977 ± 0.001 0.979 ± 0.001

than in storm sewers. It was reported that Saccharibacteria is dominant in the membrane bioreactor-treated medium age landfill leachate (Remmas et al., 2017) and aerobic SBRs (sequencing-batch reactors) fed with synthetic wastewater (Hanada et al., 2014). This appears to indicate that the conditions in combined sewers are similar, to a certain extent, to those in a bioreactor, which was corroborated by the fact that the pollutants in sewer sediment are from the deposition of contaminates containing in waste water and it is widely accepted that waste water influences the microbial community in a bioreactor (Mintenig et al., 2017). Furthermore, the results show obvious high richness and differences among Bacteroidetes, Firmicutes, and Caldiserica (Fig. 7). A summary of the different species is shown in Table S4. Interestingly, it indicates that the abundance of Bacteroidetes and Firmicutes, which are abundant in both combined and storm sewers, was significantly different in the combined and storm sewers (p-values of 0.008942 and 0.005059, respectively). Moreover, Bacteroidetes and Firmicutes are gram-positive bacteria, in which cellulose synthesis is common in bacterial metabolism (More et al., 2014). In particular, cellulose plays an important role in the microbial membrane structure, which can improve anti-scouribility (Kristensen et al., 2008). Based on the observation that carbohydrate concentration is high in combined sewers, as shown in Fig. 2(c), it appears that microbial community, through the secretion of carbohydrates, especially cellulose, is responsible for the higher anti-scouribility of sewer sediment in combined sewers than in storm sewers.

4. Conclusion 3.4.3. Group difference analysis of microbial species composition The Kruskal-Wallis method was used to determine the difference between that the species composition in the combined sewer and storm sewer sediments (ANOSIM p value is 0.001, Adonis Pr (NF) is 0.001). As shown in Fig. 7, Saccharibacteria was more abundant in combined sewers

This study has characterized the influence of carbohydrates, proteins, EPS, and the microbial community on the anti-scouribility of sewer sediments. The results showed that for the anti-scouribility of sewer sediments, the clearest pattern of distribution was that the antiscouribility of deeper sediment layers in combined sewers was higher

Fig. 6. (a) The heatmap of phyla composition from each layer of sewer sediment samples. X axis contains the name of each layer of each sample and Y axis contains the most abundant bacteria phyla. The intensity of color indicates the richness of each phylum and it is the average intensity of 3 replicates. The color intensity of each bacteria phylum is based on the relative abundance of it. (b) The heatmap of difference of species composition from each layer of sewer sediment samples. Red reflects evident difference between two layers, and green reflects unconspicuous difference between two layers. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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Fig. 7. Group difference of microbial species composition. Left histogram represents the mean percentage of species abundance of sewer sediment from two kinds sewers. The figure on the right shows the proportion of differences in function abundance within the confidence interval set. “*” means 0.01 b p ≤ 0.05, “**” means 0.001 b p ≤ 0.01, “***” means p b 0.001.

than that of the surface layers, and that this was the opposite in storm sewers. The regular distribution of anti-scouribility of sewer sediment appears to be attributable to the distribution of EPS, proteins, and carbohydrates. The diversity and abundance of the microbial community have a positive influence on the anti-scouribility distribution with respect to sewer diameter. Moreover, the composition of the microbial community contributes to the difference in anti-scouribility for each type of sewer. Specifically, the abundance of the gram-positive bacteria from the phyla Bacteroidetes and Firmicutes is clearly different in combined and storm sewers, which, owing to their production of cellulose, appear to be the cause of the difference in anti-scouribility between combined and storm sewers. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2019.05.387. References Adav, S.S., Lee, D.J., Tay, J.H., 2008. Extracellular polymeric substances and structural stability of aerobic granule. Water Res. 42, 1644–1650. Adessi, A., de Carvalho, R.C., De Philippis, R., Branquinho, C., da Silva, J.M., 2018. Microbial extracellular polymeric substances improve water retention in dryland biological soil crusts. Soil Biol. Biochem. 116, 67–69.

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