In this study, a fixed-bed biofilm membrane bioreactor was used to assess denitrification and carbon removal performance, membrane fouling, composition, and the dynamics of microbial communities across 10 salinity levels. As salinity levels increased (from 0 to 30 g/L), the removal efficiency of total nitrogen and chemical oxygen demand decreased from 98 and 86% in Phase I to 25 and 45% in Phase X, respectively. Beyond a salinity level of 10 g/L, membrane fouling accelerated considerably. The analysis of fouling resistance distribution suggested that soluble microbial products (SMPs) were the primary cause of this phenomenon. The irregularity in microbial community succession reflected the varying adaptability of different bacteria to different salinity levels. The relative abundance of Sulfuritalea, Lentimircobium, Thauera, and Pseudomonas increased from 20.2 to 47.7% as the experiments progressed. Extracellular polymeric substances-related analysis suggested that Azospirillum plays a positive role in preserving the structural integrity of the biofilm carrier. The SMP-related analysis showed a positive correlation between Lentimircobium, Thauera, Pseudomonas, and the SMP content. These results suggested that these three bacterial genera significantly promoted the release of SMP under salt stress, which in turn led to severe membrane fouling.

  • Fixed-bed biofilm membrane bioreactor maintains good performance at low-salinity levels.

  • Soluble microbial products are the major cause for fixed-bed biofilm membrane bioreactor membrane fouling.

  • Azospirillum has a positive effect on carrier biofilms.

  • Lentimicrobium, Pseudomonas, and Thauera are highly correlated with soluble microbial product concentration.

Rapid industrialization and urbanization on a global scale have severely increased the problems of water scarcity and aggravation of water quality. Thus, efficient and sustainable wastewater treatment technologies need to be developed. The fixed-bed biofilm membrane bioreactor (FB-MBR) is an innovative wastewater treatment technique that has received much attention from researchers. The FB-MBR combines the advantages of the membrane bioreactor (MBR) and the fixed-bed biofilm (FB) (Asif et al. 2019). MBR can separate solid and liquid phases, thus increasing the biomass of microbial communities. These changes enhance the resistance to substantial shock loads. The FB utilizes the complex porous structure of sponge carriers to generate a rich gradient of dissolved oxygen (DO) (Khan et al. 2011), which favors an anaerobic environment that increases denitrification. This not only ensures efficient removal of pollutants and reduction of membrane fouling but also provides new methods to treat wastewater.

The increase in wastewater salinity and the generation of large quantities of saline wastewater have drawn widespread attention. Saline wastewater is mainly produced by activities such as petroleum production, seawater aquaculture, dyeing processes, paper production, and chemical manufacturing. Complex chemical use leads to the high-salinity characteristics of contaminated wastewater (Juel et al. 2017; Tamersit et al. 2018). The salinity of wastewater from the petrochemical industry is often greater than 85 g/L (Srivastava et al. 2021), as a branch of aquaculture in the marine environment, the salinity of saline wastewater produced by the rapid development of mariculture is about 31 g/L (Brown & Terwilliger 1999). The textile printing and dyeing industry consumes 200–500 cubic meters of water per ton of products processed (Munnaf et al. 2014; Oktem et al. 2019), resulting in the production of a large amount of Cl in the process of bleaching and dyeing, the salinity level range was 2.9–10 g/L (Srivastava et al. 2021). The salinity of wastewater produced by a paper mill in Jiangsu Province, China can reach 90 g/L (Qiu et al. 2021). Very high salinity is detrimental to microbial activity (Bassin et al. 2012). The increase in osmotic pressure caused by an increase in salt concentrations leads to cell lysis. The protoplasm moves away from the cell wall due to the loss of water, resulting in microbial death and a decrease in denitrification efficiency (Jang et al. 2013; Zhao et al. 2020). Salinity inhibits the kinetic degradation of nitrifying bacteria and heterotrophic bacteria in activated sludge, which decreases the removal efficiency of organic matter and nutrients (Liang et al. 2017).

Di Trapani et al. (2014) studied salt-adapted sludge in a moving-bed biofilm MBR and found that the biofilm significantly detached from the carrier, causing irreversible surface cake layer blockage. Similarly, Rinzema et al. (1988) found that granular sludge is susceptible to disintegration under high salt concentrations. The combined use of FB and MBR can effectively retain functional microorganisms in the reactor, thus maintaining the performance of the denitrification system under salt stress. However, information on the performance of FB-MBR in treating saline wastewater is limited.

Membrane fouling is inevitable in the MBR process; although it is mitigated by FB, it intensifies significantly under salt stress. High salinity can lead to the deterioration of sludge, causing changes in soluble microbial product (SMP). SMP contributes to the formation of a gel layer on the membrane surface (Ramesh et al. 2007) and plays a key role in membrane fouling (Jarusutthirak & Amy 2006; Meng et al. 2009); higher SMP is released under high salt stress. Many studies have investigated the membrane fouling characteristics of MBR. However, a detailed investigation into the membrane fouling characteristics of FB-MBR under salt stress is lacking. The extent of membrane fouling and its underlying causes in FB-MBR need to be experimentally determined.

Studies have found that the decrease in denitrification and carbon removal performance, as well as the exacerbation of membrane fouling (Hong et al. 2013; Qiu & Ting 2013) are caused mainly due to the changes in the microbial community structure. High-salinity environments cause a huge effect on microbial community structure, and the change of microbial community structure in turn affects the efficiencies of nitrogen and carbon removal and the performance of the MBRs (Lay et al. 2010; Jang et al. 2013). Previous studies also reached the same conclusion, attributing the decline in biological performance primarily to alterations in the bacterial community structure in saline environments (García-Ruiz et al. 2018).

Microorganisms have specific optimal growth requirements for salinity. When salinity changes, microorganisms that are unable to withstand the salinity shock lose their activity (Shen et al. 2015). The presence of a large number of halophilic microorganisms aggravated the membrane fouling and reduced the removal efficiency of pollutants. The transmembrane pressure (TMP) reached the critical flux (27 kPa) after 132 h without the addition of salt. However, TMP reached the critical flux within 60 h of operation with a salt concentration of 20 g/L (Jang et al. 2013). Salinity below 2.0 wt% yields good performance, but higher salinity levels have a strong adverse effect on acclimated denitrifying sludge (Miao et al. 2015). Researchers have also found significant changes in the denitrifying microbial community structure following exposure to high salinity (Ng et al. 2015; Chen et al. 2016). These findings indicate that salinity is one of the crucial factors influencing MBR performance and sludge characteristics. Studies on salinity-induced microbial community succession have not comprehensively investigated the community succession process based on the FB-MBR. Whether FB-MBR can adapt to saline wastewater and be used for efficient denitrification and carbon removal needs to be evaluated.

In this study, a 92-day experiment was conducted on FB-MBR using 10 salinity levels. The evaluation criteria included denitrification and carbon removal performance, membrane fouling characteristics, and microbial community succession. A comprehensive investigation was conducted to assess the efficiency of FB-MBR in treating urban sewage rich in inorganic salts. Correlation was specifically examined between the composition and variation of membrane fouling substances and microbial community succession. We also analyzed microbial community succession and the worsening of membrane fouling at the phylum and genus levels. These findings provided theoretical support for the treatment of saline wastewater using FB-MBR in the future.

Experimental setup

A flowchart of the FB-MBR process is presented in Figure 1. The FB-MBR system is primarily composed of organic glass. The reactor is divided into two main sections, including the FB tank with an effective volume of 42 L and the MBR tank with an effective volume of 21.6 L. Raw water is introduced into the system through a high-level water tank and then is sequentially passed through the FB tank and the MBR tank. Finally, it is pumped into the product water tank via the membrane module.
Figure 1

FB-MBR process flow chart. (1) Into the water tank; (2) high water tank; (3) FB biological filter; (4) membrane component pool; (5) production water tank; (6) stationary carrier; (7) hollow fiber membrane; (8) float ball valve; (9) stirrer; (10) heating rod; (11) WTW water quality detector; (12) temperature/pH/DO/ORP probe; (13) vacuum pressure gauge; (14) intake pump; (15) aeration pump; (16) gas flowmeter; (17) perforated aerator; (18) water production/backwash pump; (19) PLC; and (20) computer.

Figure 1

FB-MBR process flow chart. (1) Into the water tank; (2) high water tank; (3) FB biological filter; (4) membrane component pool; (5) production water tank; (6) stationary carrier; (7) hollow fiber membrane; (8) float ball valve; (9) stirrer; (10) heating rod; (11) WTW water quality detector; (12) temperature/pH/DO/ORP probe; (13) vacuum pressure gauge; (14) intake pump; (15) aeration pump; (16) gas flowmeter; (17) perforated aerator; (18) water production/backwash pump; (19) PLC; and (20) computer.

Close modal

The FB-MBR process is equipped with a programmable logic controller (PLC) and a data acquisition system to control system operations. Throughout the process, the membrane module maintains a constant flux, cycling between 9 min of effluent collecting and 1 min of hydraulic flushing. Perforated aeration pipes are installed beneath the membrane module for intermittent air scouring of surface contaminants (30 s on/30 s off). The FB-MBR process stops when it reaches the end of a phase or when the TMP gauge reads approximately 50 kPa. At this point, the fouled membrane modules are removed for offline cleaning.

Pre-cultivation of biofilm

In the laboratory, activated sludge was used as the seed sludge for biofilm development. Activated sludge was obtained from an oxidation ditch with good nitrogen and carbon removal performance in a wastewater treatment plant in north China. The process started with rapid sludge discharge to initiate carrier pre-coating. Then, the influent carbon and the nitrogen load were increased to further enrich and cultivate the biofilm on the carriers.

After 36 days of enrichment and cultivation, a dynamic equilibrium was attained in the growth and detachment of the biofilm. The biomass stabilized at 1.525 gSS/g of the carrier and the VSS/SS ratio reached 0.81. The microbial activity was high, demonstrating excellent denitrification and carbon removal efficiency. The efficiencies of the removal of -N, chemical oxygen demand (COD) reached 99.44 and 84.60%, respectively.

Synthetic wastewater and operating conditions

In the experimental setup, artificial water was used, which contained nitrate nitrogen, organic matter, and inorganic salts obtained from potassium nitrate, sodium acetate, and sodium chloride, respectively. These components were mixed in specific proportions to create the desired composition. The concentrations of nitrate nitrogen and COD were 31 ± 2 and 113.7 ± 2 mg/L, which ensure all nitrate nitrogen can be reduced to N2, the average C/N ratio was 3.67. Trace elements were prepared with (mg/L): KHCO3(1.25); KHPO4(0.025); CaCl·2H2O(0.3); MgSO4·7H2O(0.2); FeSO4(0.00625); EDTA(15); ZnSO4·7H2O(0.43), CoCl2·6H2O(0.24); MnCl·4H2O(0.99); CuSO4·5H2O(0.25); NaMoO4·2H2O(0.22); NiCl2·6H2O(0.19); NaSeO4·10H2O(0.21); H3BO4(0.014); and NaWO4·2H2O(0.05).

The experimental procedure included 10 phases conducted over 92 days. The phases were divided into two categories based on salinity; in Phases I–VI, each phase duration was 7 days, the salinity range was 0–10 g/L, representing low salinity, whereas, in phases VII to X, each phase duration was 10 days, 10 days, 14 days, and 14 days, the salinity range was 15–30 g/L, representing high salinity. The salinity concentration increase in Phase I–X was 0.5, 0,5, 1.5, 2.5, 2.5, 5, 5, 5, and 5 g/L, respectively. The hydraulic retention time (HRT) was maintained at 12 h. Details on substrate concentration parameters are presented in Table 1. Throughout the operation, the temperature, pH, and DO within the reactor were maintained at 25 ± 2 °C, 7.5–8.5, and 0.2–0.5 mg/L, respectively. A stirrer and an aeration pump were used to maintain the DO level.

Table 1

Operational conditions of FB-MBR

PhaseTime/dNaCl/g/LHRT/hCOD/mg/LNO3-N/mg/L
Ⅰ 1–7 0.0 12 115.14 31.06 
Ⅱ 8–14 0.5 117.23 32.15 
Ⅲ 15–21 1.0 111.61 31.21 
Ⅳ 22–28 2.5 115.46 29.38 
Ⅴ 29–35 5.0 111.51 31.35 
Ⅵ 36–42 10.0 115.71 30.94 
Ⅶ 43–52 15.0 113.69 31.15 
Ⅷ 53–62 20.0 111.22 32.70 
Ⅸ 63–77 25.0 112.51 31.15 
Ⅹ 78–92 30.0 113.51 30.31 
PhaseTime/dNaCl/g/LHRT/hCOD/mg/LNO3-N/mg/L
Ⅰ 1–7 0.0 12 115.14 31.06 
Ⅱ 8–14 0.5 117.23 32.15 
Ⅲ 15–21 1.0 111.61 31.21 
Ⅳ 22–28 2.5 115.46 29.38 
Ⅴ 29–35 5.0 111.51 31.35 
Ⅵ 36–42 10.0 115.71 30.94 
Ⅶ 43–52 15.0 113.69 31.15 
Ⅷ 53–62 20.0 111.22 32.70 
Ⅸ 63–77 25.0 112.51 31.15 
Ⅹ 78–92 30.0 113.51 30.31 

Analytical method

Conventional index analysis

The COD, -N, -N, -N, and mixed liquid suspensions were determined according to standard methods (American Public Health Association et al. 2005).

Determination of carrier biomass

The carrier biomass was extracted and measured following the method described by Douterelo et al. (2014). Briefly, a specific quantity of carrier material was randomly selected from the reactor and added to a 50 mL solution of 1 mol/L NaOH. The mixture was then heated in a water bath at 80°C for 30 min. After heating the mixture, ultrasonication was performed for 1 min at 100 W to facilitate the detachment of biomass from the carrier. The treated samples were filtered through a 0.45 μm membrane filter. The resulting biomass was divided into two parts. One part was placed in a constant-temperature oven, and the other part was placed in a muffle furnace; both parts were dried and weighed separately. The measured values of carrier-attached biomass (suspended solids (SS)) and volatile suspended solids (VSS) were used to calculate the quantity of biomass as gSS/g carrier and gVSS/g carrier, respectively. Using this method, the biomass attached to the carrier material could be accurately determined (Liang et al. 2010).

Extraction and measurement of extracellular polymeric substances and SMP

During the late phases of each operational phase, a specific quantity of carrier material was randomly selected from the reactor. The biofilm was detached from the carrier and dissolved in 50 mL of deionized water. Ultrasonication was performed at 40 W for 1 min to create a homogeneous mixture. To remove residual substances from the sludge surface, the mixture was washed thrice with deionized water.

For extracting SMP, the homogenized mixture was placed in a 50 mL centrifuge tube and centrifuged at 4 °C and 4,000 × g for 5 min. The supernatant obtained after centrifugation was filtered through a 0.45 μm membrane filter to collect the SMP. For extracting extracellular polymeric substances (EPS), deionized water was added to the centrifugation residue to restore the original volume and the mixture was thoroughly mixed. Then, the mixture was subjected to heat extraction at 105 °C for 2 h. After heat extraction, the mixture was centrifuged at 4 °C and 8,000 × g for 10 min. The supernatant obtained after centrifugation was filtered through a 0.45 μm membrane filter to collect EPS.

SMP and EPS were standardized based on the total content of polysaccharides (PS) and proteins (PN). Their concentrations were determined by the phenol–sulfuric acid method, with glucose as the standard for PS, and the modified Bradford method, with bovine serum albumin as the standard for PN. The PS and PN components of SMP and EPS were labeled as SMPPs, SMPPN (expressed in mg/L), EPSPs, and EPSPN (expressed in mg/g) (Adav & Lee 2008).

Membrane cleaning and analysis of membrane fouling resistance and rate

The offline membrane cleaning process involves several key steps to rejuvenate the performance of the membrane. First, air flushing for 2 h to eliminate the filter cake layer. Then, backwash with distilled water in the membrane and remove the gel layer by air flushing for 2 h. In the next phase, the membrane was immersed in a solution of 1 g/L NaClO for 22 h (air flushing for the last 11 h) to remove organic pollutants. Finally, the membrane was immersed in a 3 g/L citric acid solution, and then, flushed with air for 2 h, which effectively eliminated inorganic pollutants (Xiao et al. 2023).

Darcy's law was applied to calculate filtration resistance using the following equation (Lin et al. 2009):
formula
(1)

In the equation, R represents the total filtration resistance, ΔP represents the TMP difference, J represents the permeate flux, μ represents the dynamic viscosity, and Rc, Rp, and Rm, respectively, represent the resistance of the filter cake layer, the membrane pore resistance, and the inherent resistance of the membrane. R was calculated from the data at the end of the phase. Rm was obtained by measuring the permeability of the virgin membrane with distilled water. The total resistance of Rm and Rp were measured by the permeability test of the fouled membrane after cleaning, and then the value of Rp and Rc could be successively calculated (Lin et al. 2009).

The membrane fouling rate (MFR (kPa/h)) was calculated using the following equation:
formula
(2)

Here, ΔP represents the TMP difference and ΔT represents the duration of each run of the cycle.

Three-dimensional fluorescence spectrum analysis

In Section 2.4.3, the extracted biofilm SMP and EPS supernatant were diluted to a certain concentration and directly analyzed using a fluorescence spectrophotometer (Hitachi, F7100, Japan). Ultrapure water was used as a blank sample for control. The interval of excitation wavelength (Ex) was 10 nm and the wavelength range was 200–450 nm. The interval of emission spectrum (Em) was 10 nm, the wavelength range was 250–500 nm, and the scanning speed was 60,000 nm/min.

Analysis of the microbial community structure

Carrier biofilm samples were collected at the end of the 10 phases. The biofilm attached to the carrier was rinsed with deionized water to peel it off. Then, it was centrifuged at 4 °C and 13,000 × g for 10 min. All samples were stored in an ultra-low temperature refrigerator at −80 °C (MDF-U33v, Sanyo Company, Japan). In total, 10 samples were collected and labeled S1–S10. DNA was extracted using the EZNA soil DNA Kit (Ommi Biotechnology, USA). Primers 515F (5′-GTGCCAGCMGCCGCGG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) were used to amplify the V4 region of the 16S rRNA gene.

Sequencing was performed using the Illumina-MiSeg-PE300 platform (Shanghai Megi Biopharmaceutical Technology Co., Ltd) operational taxonomic unit (OTU) with 97% similarity were clustered using the UPARSE method. The Origin 2021 software was used for determining microbial diversity via map analysis.

Effect analysis of nitrogen and carbon removal

The treatment performance of FB-MBR under different conditions of salinity is shown in Figure 2. In Phase I, where no NaCl was added to the system, the nitrogen loading rate was maintained at 0.063 kg/(m3·d). The removal efficiencies for -N and total nitrogen (TN) were 99.18 and 98.23%, respectively. The nitrogen removal rate was 0.062 kg/(m3·d). The COD removal efficiency was 86%, which indicated that denitrification and carbon removal during this phase were efficient and stable.
Figure 2

Effect of FB-MBR on nitrogen and carbon removal under different salinity conditions.

Figure 2

Effect of FB-MBR on nitrogen and carbon removal under different salinity conditions.

Close modal

From Phases II to V, salinity increased from 0.5 to 5 g/L and the removal efficiencies of -N and TN decreased from 98.8 and 95.766% in Phase II to 78.64 and 72.339% in Phase V, respectively. The proportion of -N in the effluent was 1.16, 12.83, 12.68, and 21.9%, and the proportion of nitrite (NO2-N) in the effluent was 1.3, 1.8, 2.59, and 2.58%. The contribution rate of nitrogen removal through denitrification decreased from 95.8 to 71.7%. However, the effluent concentrations of -N and TN remained below 8.4 mg/L and the COD removal efficiency decreased from 81.76 to 71.33%. The C/N consumed by the carrier biofilm was 3.02, 3.24, 3.46, and 3.32, respectively, which meant that the biofilm needed to synthesize and secrete more substances to maintain the balance of osmotic pressure. At the beginning of each phase, the removal efficiencies decreased, but they recovered to normal levels after the system adapted to the salinity shock. This indicated that at low-salinity levels, the system adapted to environmental changes without altering its high denitrification efficiency. The adaptability of biofilms to low-salinity environments was also demonstrated in Zhai's experiment. When the salinity reaches 10 g/L, the denitrification efficiency of biofilm will fluctuate greatly, but it can still recover high nitrogen removal efficiency after the system adapts to the environment (Zhai et al. 2018).

From Phases VI to X, the denitrification performance and carbon removal efficiency significantly decreased. The removal efficiencies of -N and TN decreased from 71.72 and 65.74% to 43.3 and 25.23%, respectively. The proportion of -N in the effluent was 27.7, 36.5, 40.0, 48.0, and 53.7% and the proportion of NO2-N in the effluent was 2.9, 4.3, 5.7, 9, and 12.7%. The contribution rate of nitrogen removal through denitrification decreased from 95.8 to 71.7%. The COD removal efficiency also decreased from 66.1 to 41.9%. The C/N consumed by the carrier biofilm was 3.02, 3.24, 3.46, and 3.32, respectively. The high-salinity shock exceeded the load-bearing capacity of the system, which greatly decreased denitrification and carbon removal efficiencies. This was similar to the experimental results for Zhai et al. (2019), which showed that after the salinity level was greater than 25 g/L, the denitrification and nitrogen removal efficiencies of the biofilm showed drastic fluctuations and the time required to adapt to high salinity gradually increased. When the salinity level was greater than 35 g/L, even if the system was given sufficient time to adapt to the environment, the biofilm failed to show adaptability to high salinity, resulting in a sharp decline in nitrogen removal efficiency (Zhai et al. 2019). The efficiency of TN removal decreased significantly partly due to the accumulation of nitrite (-N) after Phase VIII. The system could not adapt to the high-salinity shock. This indicated that microorganisms capable of thriving and reproducing in highly saline conditions were not present in the system, which led to a continuous decline in removal efficiency.

Carrier-attached biomass and apparent morphology

The changes in carrier-attached biomass and biofilm surface morphology under different salinity conditions are shown in Figure 3 and Figure S1. The evolution of the biofilm could be categorized into two periods: Phases I–V represented the growth phase and Phases VI–X represented the decline phase.
Figure 3

Changes in carrier attachment biomass and VSS/SS ratio under different salinity conditions.

Figure 3

Changes in carrier attachment biomass and VSS/SS ratio under different salinity conditions.

Close modal

At the end of Phase I, the carrier-attached biomass was 1.450 gSS/g carrier and the VSS/SS ratio was 0.850. At this phase, the biofilm was firmly attached to the carrier and appeared dark brown. Biomass increased as salinity increased from 0.5 to 5 g/L. This increase occurred due to the introduction of inorganic salts, which imposed stress on the carrier-attached biofilm. In response to this stress, microorganisms secreted more carbohydrates and PN, which increased carrier-attached biomass (Wang et al. 2015). By the end of Phase V, the carrier-attached biomass reached 1.545 gSS/g carrier and the VSS/SS ratio increased to 0.871. At this phase, a viscous flocculent substance coated the surface of the carrier-attached biofilm, which increased the thickness of the biofilm and changed its color from dark brown to light brown. A higher VSS/SS ratio indicated that the microbes within the carrier-attached biofilm were more active. These results indicated that moderate levels of salinity can facilitate the rapid formation of biofilm.

In Phase VI, the NaCl concentration increased to 10 g/L, which led to the detachment of some of the biofilm material from the carrier. Consequently, the carrier-attached biomass decreased to 1.472 gSS/g carrier by the end of this phase. The VSS/SS ratio also decreased to 0.812. However, the morphology of the carrier-attached biofilm in this phase did not undergo significant changes compared to that recorded in Phase I. Also, the biofilm could still maintain the overall structural integrity. During Phases VII–X, in the high salinity environment, the biomass decreased. It significantly decreased from 1.302 gSS/g carrier in Phase VII to 0.689 gSS/g carrier in Phase X. The VSS/SS ratio also decreased from 0.741 to 0.435. The morphology of the carrier-attached biofilm underwent noticeable changes. By the end of Phase VIII, the biofilm structure on the carrier surface became loose, and most of the biofilm was detached. In Phase X, the biofilm was almost completely detached from the carrier surface. At this phase, the biofilm struggled to resist the impact of high salinity (Wang et al. 2019). These results suggested that when salinity was low, the carrier-attached biofilm relied on functional microorganisms to secrete substances such as PS and PN to maintain the osmotic pressure within and outside the cells. However, when salinity was high, the rapid decrease in VSS/SS indicated a significant decrease in the activity of functional microorganisms within the carrier-attached biofilm. Inactive microorganisms cannot maintain the structure of the biofilm, and their attachment to the carrier surface decreases. This leads to a reduction in the denitrification and decarbonization performance of the FB-MBR process.

Analysis of the content and composition of SMP and EPS

The variation in the content and composition of SMP and EPS in the biofilm of carrier media under different conditions of salinity is shown in Figure 4. When no NaCl was added, the SMP content in the system was the lowest, only 22.75 mg/L, and the EPS content was 30.21 mg/g. As the influent inorganic salt concentration increased from 0.5 to 5 g/L, the content of EPS and SMP gradually increased and reached values of 35.24 and 29.89 mg/L, respectively. This increase occurred due to the self-protective behavior of microorganisms under salt stress. EPS can bind to cells to form an extensive network structure with a high water content, thus protecting cells from dehydration. This, in turn, helps maintain the osmotic balance within and outside cells, ensuring that the environment of the microbial community is conducive to survival. EPS is a complex high-molecular-weight polymer mixture composed of PS, PN, humic acids, sugar alcohols, nucleic acids, lipids, and other components. EPS can envelop microbial aggregates and create a protective matrix that can resist external stress. In wastewater biological treatment, microorganisms exist as microbial aggregates, such as biofilms, floc structures, and granules (Leng et al. 2015). EPS is a primary component of the biofilm, constituting 50–80% (w/w) of the total biofilm weight. EPS has multiple functions, including surface adhesion, bacterial cell aggregation, biofilm cohesion, structural stability, protection against microbial threats, and nutrient absorption (Flemming 2011; Flemming et al. 2016).
Figure 4

Changes in EPS and SMP contents and the composition of carrier biofilm under different salinity conditions.

Figure 4

Changes in EPS and SMP contents and the composition of carrier biofilm under different salinity conditions.

Close modal

As the salinity further increased from 10 to 20 g/L, along with the detachment of the carrier biofilm, the EPS content also decreased from 35.24 mg/g in Phase V to 32.02, 28.65, and 25.07 mg/g in Phases Ⅵ–Ⅷ. This finding indicated that when the salinity level was between 10 and 20 g/L, microorganisms lost their ability to withstand salinity stress, leading to a decrease in metabolic activities and an inability to secrete EPS to balance the osmotic pressure difference on either side of the cell. In contrast, the SMP content increased continuously from 24.94 mg/L in Phase V to 26.98, 31.59, and 37.77 mg/L in Phases Ⅵ–Ⅷ. The rate of increase in the SMP content accelerated with the advancement of the phases of the experiment.

When the salinity level increased to 25 and 30 g/L, the carrier biofilm was completely detached. The EPS content decreased to 19.79 and 12.82 g/L, respectively, whereas the SMP content increased to 45.98 and 56.66 mg/g. At the end of the experiment, the EPS content was only about one-third of the maximum content recorded in Phase V. This finding indicated that under high-salinity stress, FB-MBR could no longer sustain microbial life, which resulted in a significant decrease in denitrification and decarburization efficiency. The SMP content increased throughout the experiment, and the rate of increase in Phases V–X was considerably higher than that recorded in Phases I–V. This occurred due to the hydrolysis of EPS and cell lysis, both of which increased the SMP content. SMP primarily originates from EPS and cell lysis. EPS production increases under salt stress to protect cells (Li et al. 2013). The hydrolysis of EPS can increase the production of SMP (Aquino & Stuckey 2004). Salinity-induced high osmotic conditions may promote and exacerbate cell lysis. The intracellular components released from lysed cells may increase the SMP content (Aquino & Stuckey 2004; Yogalakshmi & Joseph 2010).

Analysis of membrane fouling

The variation in TMP and membrane fouling under different conditions of salinity are shown in Figure 5 and Figure S2. The system maintained a consistent membrane flux of 10.6 L/(m2·h) throughout the process. In Phase I, where no inorganic salts were introduced, the TMP was 15.5 kPa by the end of the phase, with a corresponding MFR of 0.083 kPa/h. From Phases II to VI, salinity increased from 0.5 to 10 g/L. The increase in salinity affected the physicochemical properties of the biofilm in the low-salinity environment. In response to salinity stress, microorganisms increased the secretion of EPS and SMP. These changes increased the TMP to 27.0 kPa and the MFR from 0.086 to 0.146 kPa/h.
Figure 5

TMP and membrane flux curves of systems with different salinity conditions.

Figure 5

TMP and membrane flux curves of systems with different salinity conditions.

Close modal

Phases VII–X were conducted under high-salinity conditions (15–30 g/L), which made the system more vulnerable to salinity shock, resulting in the detachment of the carrier biofilm to a greater extent. The high osmotic pressure led to a significant increase in the rate of cell death, which led to the release of intracellular components. These changes rapidly increased the SMP content and promoted membrane fouling. By the end of this phase, the MFR increased significantly from 0.172 to 0.396 kPa/h and the operational cycle was shortened to 5 days.

At Phase I of system operation (c(NaCl) = 0 g/L), membrane fouling was relatively mild. Only a small amount of viscous substances were found to adhere to the surface of the membrane filaments. In Phases II–VII (c(NaCl) = 0.5–15 g/L), in response to salinity stress, microorganisms secreted more SMP, which caused denser membranous substances to adhere to the surface of the filaments as the salinity of the system increased. In Phases VIII–X (c(NaCl) = 15–30 g/L), the carrier biofilm started to detach and enter the membrane tank, while the retention and adsorption of the components of the membrane formed a cake layer on the surface of the filaments. These observations suggested that the factors leading to an increase in membrane fouling may vary under different conditions of salinity.

The distribution of membrane fouling resistance under different conditions of salinity is shown in Table 2. In Phase I (no NaCl), Rt was 2.072 × 1012 m−1, Rp/Rt was 81.08%, and Rc/Rt was 5.07%. Rp was the primary factor that contributed to membrane fouling. In Phases V–VI (low-salinity conditions), Rt increased to 3.101 × 1012 and 3.609 × 1012 m−1, Rp/Rt increased to 84.36 and 85.73%, and Rc/Rt increased to 6.39 and 6.32%, respectively. Rp was the predominant contributor to membrane fouling.

Table 2

Distribution of membrane fouling resistance under different salinity conditions

PhaseRm (×1012 m−1)Rp (×1012 m−1)Rc (×1012 m−1)Rt (×1012 m−1)Rp/Rt (%)Rc/Rt (%)
Ⅰ 0.287 1.680 0.105 2.072 81.08 5.07 
Ⅱ 0.287 1.864 0.121 2.272 82.04 5.33 
Ⅲ 0.287 2.005 0,154 2.446 81.97 6.30 
Ⅳ 0.287 2.240 0.186 2.713 82.57 6.86 
Ⅴ 0.287 2.616 0.198 3.101 84.36 6.39 
Ⅵ 0.287 3.094 0.228 3.609 85.73 6.32 
Ⅶ 0.287 5.348 0.278 5.913 90.44 4.70 
Ⅷ 0.287 5.765 0.698 6.750 85.41 10.34 
Ⅸ 0.287 5.945 0.518 6.750 88.07 7.67 
Ⅹ 0.287 5.297 1.166 6.750 78.47 17.27 
PhaseRm (×1012 m−1)Rp (×1012 m−1)Rc (×1012 m−1)Rt (×1012 m−1)Rp/Rt (%)Rc/Rt (%)
Ⅰ 0.287 1.680 0.105 2.072 81.08 5.07 
Ⅱ 0.287 1.864 0.121 2.272 82.04 5.33 
Ⅲ 0.287 2.005 0,154 2.446 81.97 6.30 
Ⅳ 0.287 2.240 0.186 2.713 82.57 6.86 
Ⅴ 0.287 2.616 0.198 3.101 84.36 6.39 
Ⅵ 0.287 3.094 0.228 3.609 85.73 6.32 
Ⅶ 0.287 5.348 0.278 5.913 90.44 4.70 
Ⅷ 0.287 5.765 0.698 6.750 85.41 10.34 
Ⅸ 0.287 5.945 0.518 6.750 88.07 7.67 
Ⅹ 0.287 5.297 1.166 6.750 78.47 17.27 

The Rt values were 6.750 × 1012 m−1 in Phases VIII and X (high-salinity conditions). The retention of some parts of the detached biofilm by the membrane components led to an increase in the Rc/Rt ratio to 10.34 and 17.27%, respectively. However, the Rp/Rt ratios remained relatively high at 85.41 and 78.47%. The membrane pore resistance was identified as the primary source of membrane fouling under these high-salinity conditions.

The passive adsorption of SMP occurs even under zero-flux conditions (Zhang et al. 2006). The rapid increase in TMP and MFR might be attributed to the gradual alteration of the effective surface energy of the membrane due to SMP fouling, which affects the interaction between the membrane and pollutants. This makes it more susceptible for solutes and particles to adhere, especially those (e.g., other polymer substances and flocs) that are not easily adsorbed on the active layer of the clean membrane. Additionally, SMP is adsorbed not only on the surface but also within the membrane pores, which often leads to irreversible fouling (Ognier et al. 2002). These findings matched the conclusions of this study, in which SMP was identified as the primary contributor to membrane pore resistance.

Fluorescence spectroscopy analysis of SMP and EPS

The changes in fluorescence characteristics of SMP and EPS in the biofilm under different salinity conditions are presented in Figure 6. In Phases I–IV, the carrier biofilm maintained good structural integrity and high denitrification and carbon removal efficiency. The analysis of salinity on the components of the carrier biofilm was conducted in five phases, i.e., in Phases I, V, VI, VIII, and X, by conducting three-dimension excitation emission matrix (3D-EEM) analysis. In the SMP three-dimensional fluorescence spectrum of Phase I, Ex/Em = 220 nm/330 nm and Ex/Em = 280 nm/340 nm were the two major characteristic peaks representing soluble microbial byproducts, mainly tyrosine and tryptophan; the fluorescence peak intensities recorded were 1,014 and 807.9, respectively. A weaker peak of humic acid-like substances (Ex/Em = 360 nm/410 nm) was also detected, with a fluorescence peak intensity of only 55.6 (Zheng et al. 2018). In the SMP EEM spectra of the other four phases (i.e., Phases V, VI, VIII, and X), the fluorescence peak intensities of tyrosine and tryptophan increased, reaching peaks of 2,146 and 1,469 in Phase X, while the fluorescence peak of humic acid-like substances showed negligible changes.
Figure 6

Fluorescence spectra of SMP (left) and EPS (right) of carrier biofilm at different phases (I, V, VI, VIII, X).

Figure 6

Fluorescence spectra of SMP (left) and EPS (right) of carrier biofilm at different phases (I, V, VI, VIII, X).

Close modal

In the EPS three-dimensional fluorescence spectra were obtained for four of the Phases (I, V, VI, and VIII), three types of characteristic peaks were identified, which included the aromatic protein I characteristic peak at Ex/Em = 220–230 nm/300–310 nm, the aromatic protein II characteristic peak at Ex/Em = 220–230 nm/340–350 nm (with a slight difference in peak intensity), and the tryptophan characteristic peak at Ex/Em = 280 nm/350 nm (Zheng et al. 2018). In Phase X, the aromatic protein I characteristic peak disappeared, but the other two types of characteristic peaks were detectable. The fluorescence intensity in Phase V reached its peak value, aligning with the highest EPS content mentioned in the previous section.

Some studies have shown that PN play a greater role in the decrease in membrane flux compared to PS. This is because PN have a propensity to obstruct membrane pores and adhere to the membrane surface (Ni et al. 2011). The influence of low-molecular-weight humic substances on membrane fouling may be disregarded due to their small molecular size as compared with that of PN and PS (Li et al. 2015). Therefore, under saline conditions, the pronounced membrane fouling in FB-MBR is chiefly ascribed to SMP, with an emphasis on the greater release and retention of proteinaceous compounds.

Impact on the microbial community structure

Microbial diversity

The microbial communities under different conditions of salinity were characterized by conducting Illumina high-throughput sequencing (Table 3). The alpha diversity of the microbial community structure was evaluated. Abundance-based coverage estimator (ACE) and the Chao index represent community richness. The Sobs index represents the actual observed number of OTUs, and a larger index indicates a greater diversity in the microbial species present. The Shannon and Simpson indices reflect community diversity. High coverage estimation values (i.e., >0.99) indicate high accuracy of sequencing and robust diversity results. Sobs, ACE, and Chao indices all decreased after the inorganic salts were introduced into the system, but the values recovered. This indicated that the microbial communities probably underwent succession due to salt shock, with salt-tolerant microorganisms gradually dominating the microbial community. As the salinity level increased, these three indices exhibited an overall decreasing trend but still showed temporary increases, suggesting that different salt-tolerant microorganisms can thrive at specific salinity levels. This trend matched the values of the Shannon index. The Simpson index is calculated by randomly selecting two OTUs from a sample dataset, representing the probability that they belong to different species; a higher probability indicates greater species diversity. After inorganic salts were introduced into the system, the Simpson index reached its maximum value, indicating that microbial species were most abundant at the low-salinity level (Phase II). The value of the Simpson index in Phases III–VI fluctuated around 0.046–0.052, suggesting strong competition between salt-tolerant microorganisms and salt-intolerant microorganisms during this period. In Phases VII–IX, the Simpson index increased from 0.059 to 0.068, indicating that salt-tolerant microorganisms dominated these phases, but their adaptability to different levels of salinity led to continuous changes in the dominant species.

Table 3

Microbial community richness and diversity indices of different salinities

SamplesACEChaoShannonSimpsonSobsCoverage
S1 1570 1613 4.5626 0.0417 1290 0.9947 
S2 1387 1379 4.0002 0.0814 1096 0.996 
S3 1561 1549 4.6332 0.0503 1315 0.9958 
S4 1449 1447 4.3729 0.0463 1140 0.995 
S5 1435 1400 4.2567 0.0527 1122 0.9948 
S6 1469 1453 4.4770 0.0515 1223 0.9954 
S7 1490 1499 4.1918 0.0593 1162 0.995 
S8 1287 1299 4.1199 0.0606 1018 0.995 
S9 1446 1455 4.0708 0.0683 1104 0.9949 
S10 1147 1118 4.3311 0.0513 962 0.9960 
SamplesACEChaoShannonSimpsonSobsCoverage
S1 1570 1613 4.5626 0.0417 1290 0.9947 
S2 1387 1379 4.0002 0.0814 1096 0.996 
S3 1561 1549 4.6332 0.0503 1315 0.9958 
S4 1449 1447 4.3729 0.0463 1140 0.995 
S5 1435 1400 4.2567 0.0527 1122 0.9948 
S6 1469 1453 4.4770 0.0515 1223 0.9954 
S7 1490 1499 4.1918 0.0593 1162 0.995 
S8 1287 1299 4.1199 0.0606 1018 0.995 
S9 1446 1455 4.0708 0.0683 1104 0.9949 
S10 1147 1118 4.3311 0.0513 962 0.9960 

Microbial community analysis in the genus level

Denitrifying functional genera were identified from the high-throughput sequencing data, and the genus-level changes in the structure of the microbial community were analyzed (Figure 7) to assess the effect of salinity. Across the 10 phases, the dominant genera were ranked as follows: Sulfuritalea (14.4–26.1%), Lentimicrobium (2.8–13.4%), Thauera (2.2–18.4%), Pseudomonas (2.7–6.8%), Dechloromonas (0.4–5%), Acinetobacter (0.5–9.6%), and Azospirillum (0.2–6.2%). Except for Lentimicrobium, all identified genera belonged to phylum Proteobacteria.
Figure 7

Horizontal abundance heat maps of bacteria genera with different salinities.

Figure 7

Horizontal abundance heat maps of bacteria genera with different salinities.

Close modal

Sulfuritalea showed high tolerance to salinity throughout the experiment. It rapidly proliferated in the second phase (II) following the introduction of inorganic salts and reached a genus-level relative abundance of 26.07%, which indicated its strong ability to adapt to saline environments. Its relative abundance was also high (14.4–20.2%) in the subsequent phases. Sulfuritalea are sulfur-oxidizing bacteria that are abundant in saline lakes (Kojima et al. 2014), which explains the trend observed in our study. Huang et al. (2020) suggested that Sulfuritalea possesses characteristics of autotrophic denitrifying bacteria. It showed a 14.3% correlation with the denitrification gene napa; a correlation with the denitrification gene nirs was also identified.

Yuan et al. (2015) found that Acinetobacter was optimally acclimated to a salinity of 0.5%, which matched the results of this study. In this study, the relative abundance of Acinetobacter significantly decreased after inorganic salts were added, and its relative abundance continued to decrease (9.6–0.6%) as the salinity level increased to 5 g/L. Yuan et al. acclimated Acinetobacter strains isolated from sediment in breeding ponds to a saline environment in the absence of other microbial species. This indirectly suggested that Acinetobacter may be weak competitors in the microbial community.

Wang et al. (2015) showed that Pseudomonas can occur within a salinity range of 0–7%, but disappear at 8% salinity; their findings matched the results of this study. Wang et al. conducted their study using an aerobic granular sludge sequencing batch reactor. The granulation of sludge and aerobic conditions probably helped Pseudomonas to tolerate higher levels of salinity. In this study, the relative abundance of Pseudomonas reached 6.8% in Phase V (salinity: 15 g/L), and then, it decreased as salinity increased.

Wang et al. (2023) showed that Lentimicrobium exhibits a highly significant positive correlation with the denitrification functional gene napA. Their findings suggested that Lentimicrobium may have the napA gene, which plays a key role in nitrate reduction. Thauera initially had a low relative abundance of only 2.2%, but in the final phase of the experiment, it increased to approximately 18.5%. It surpassed the relative abundance of Sulfuritalea during the same period and became the dominant genus. This finding was similar to that reported by Ji et al. (2018), who showed that the relative abundance of Thauera increased from 51.33 to 83.66% when the salt level increased from 0 to 30 g/L, establishing it as the dominant species in the community. The relative abundance of Azospirillum increased before Phase V, reached a peak value of 6.17% in Phase V, and decreased as the salinity levels increased further. Many important members of the alpha-Proteobacteria class of denitrifying bacteria, including Azospirillum and Hyphomicrobium, cannot tolerate high salt concentrations (Osaka et al. 2008).

The results of high-throughput sequencing in this study showed that the relative abundance of denitrifying bacteria increased from 33.7% in Phase I to 46.5% in Phase X, reaching its peak value of 55.9% in Phase VIII. As the salinity level increased, the relative abundance of denitrifying bacteria did not increase or decrease continuously but showed intermittent changes. Such a pattern occurred probably because of two main reasons. First, as salinity levels increased, the microbial community structure started changing. Initially, halophilic bacteria could not tolerate the initial low-salinity shock when inorganic salts were introduced into the system. For halotolerant bacteria, the environment was more favorable, and it increased their growth and reproduction. As salinity levels continued to increase, the relative abundance of bacteria that can exclude salt decreased, as the environment became unsuitable for their growth; in contrast, halophilic bacteria could thrive. Second, at moderately high levels of salinity, different halophilic bacteria prefer different levels of salinity, and their adaptability to the changing salinity range varies. In an environment in which salinity increases continuously, the community structure changes with the succession of dominant species.

Correlation analysis of bacteria with EPS and SMP

As found in the analysis of the EPS correlation chart (Figure 8), Azospirillum exhibited a strong positive correlation with TOTALEPS, EPSPS, and EPSPN, while Dechloromonas exhibited a moderate positive correlation with TOTALEPS, EPSPS, and EPSPN. Lentimircobium, Thauera, and Pseudomonas strains exhibited a general negative correlation with the aforementioned EPS components (Table S1). As EPS is a major component of the biofilm, the strong correlation between Azospirillum and EPS suggested that Azospirillum plays an important role in the formation of the carrier biofilm. It maintains the structural integrity of the biofilm against salinity shocks and regulates osmotic balance inside and outside cells. The negative correlation of Lentimircobium, Thauera, and Pseudomonas with EPS suggested that these three genera might be involved in the hydrolysis of EPS, which is detrimental to the formation and stability of the carrier biofilm.
Figure 8

Heat map of Spearman correlation coefficient between bacteria and EPS and SMP.

Figure 8

Heat map of Spearman correlation coefficient between bacteria and EPS and SMP.

Close modal

As found in the analysis of the SMP correlation chart (Figure 8), TOTALSMP, SMPPS, and SMPPN exhibited a strong positive correlation with Lentimircobium, Thauera, and Pseudomonas. They exhibited a strong negative correlation with Acinetobacter and a moderate negative correlation with the Azospirillum strains (Table S2). The results of the membrane fouling resistance analysis showed that the blockage of pores by SMP was the main reason for the significant increase in the rate of membrane fouling after Phase V. The strong correlation between some genera (Lentimircobium, Thauera, and Pseudomonas) and SMP, TMP, and MFR indicated the fundamental cause of the increase in the MFR.

In this study, we found that changes in salinity significantly affected the denitrification and carbon removal efficiencies, membrane fouling characteristics, and microbial community succession of the FB-MBR process. The process showed high denitrification and carbon removal efficiencies at low salinity (0–10 g/L) but lower efficiencies at high salinity (10–30 g/L). The biofilm on the carriers maintained structural integrity by increasing the EPS content at the phases in which salinity was low, thus protecting the microbial living environment. Sponge filters kept the MFR at manageable levels when salinity was low. The increase in the SMP content due to high salinity was the main reason for an increase in the MFR. Changes in salinity resulted in frequent succession of the microbial community. This occurred because salt-sensitive, salt-tolerant, and halophilic microorganisms have different optimal salinity ranges, and their sensitivity to changes in salinity varies, which results in the continuous replacement of the dominant species. At the genus level, Lentimicrobium, Pseudomonas, and Thauera exhibited halotolerance to some extent. Azospirillum protected the carrier biofilm in this study. The strong correlation of Lentimicrobium, Pseudomonas, and Thauera with SMP indicated that they could induce an increase in the SMP content, thus promoting membrane fouling. Therefore, it is suggested that enrichment culture of Azospirillum and other potential bacteria that are beneficial to the structural integrity of biofilms in low-salinity environments, or the pretreatment of wastewater to reduce the salinity level, is expected to effectively alleviate membrane fouling caused by SMP. Our results showed that the microbial community succession at the high-salinity level is the main reason for the decrease in nitrogen and carbon removal efficiencies and the acceleration of MFR in the FB-MBR process. We examined the correlations behind these three phenomena and obtained valuable information that might contribute to enhancing the efficacy of the FB-MBR system in treating saline wastewater.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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Supplementary data