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Effect of Salinity on Performance and Microbial Community during Granulation Process in a Sequencing Batch Reactor

School of Environment, Harbin Institute of Technology, Harbin 150090, China
State Key Laboratory of Urban Water Resources and Environment, Harbin Institute of Technology, Harbin 150090, China
School of Civil Engineering, Guangzhou University, Guangzhou 510006, China
National Marine Environmental Monitoring Center, Dalian 116023, China
Author to whom correspondence should be addressed.
Water 2023, 15(22), 3961;
Submission received: 7 October 2023 / Revised: 31 October 2023 / Accepted: 9 November 2023 / Published: 14 November 2023


This study focused on the secretion of extracellular polymeric substances (EPSs), reactor nutrient removal performance and the microbial community under varying concentrations of NaCl (0, 10, 20, 30 and 40 g/L) during a granulation process in a sequencing batch reactor (SBR). The microorganisms tended to secrete higher levels of protein (PN) and polysaccharide (PS) as a protective mechanism under saline conditions, with tightly bound EPS (TB-EPS) playing a crucial role in stabilizing granules. An overall high removal rate of chemical oxygen demand (COD) throughout operation was observed. However, the removal rate of total nitrogen (TN) progressively decreased with the stepwise increase in salinity from 85.59% at 10 g/L to 64.18% at 40 g/L. The low total phosphorus (TP) removal efficiency during the operation process is due to the loss of sludge biomass and inhibition of phosphorus-accumulating bacteria activity. Moreover, salinity caused the changes in microbial community structure. Paracoccus, Thauera and unclassified_f_Rhodobacteraceae were dominant genera at 10 g, 20 g/L and 30 g/L salinity, respectively, while Azoarcus, Halomonas, unclassified_f_Flavobacteriaceaeand Vibrio replaced them at 40 g/L salinity.

1. Introduction

The increasing discharge of industry saline wastewater produced from petroleum exploitation, leather making, food processing, chemical manufacturing, et al., imposes a certain negative impact on the environment [1,2]. In addition, seawater, an inexhaustible water resource, has been used extensively instead of fresh water in some places [3], including industrial cooling water and large domestic water (mainly flushing water). The increased consumption of seawater has directly resulted in a rise in saline wastewater emission and produced a shock to the traditional sewage treatment process. There were mainly two methods of saline wastewater treatment: non-biological methods and biological methods. Non-biological methods mainly refer to physico-chemical processes and have a high cost because of chemical usage and energy consumption, and thus cannot be widely used [4,5]. Moreover that, the high osmotic pressure caused by a high salinity environment can lead to plasmolysis or the loss of cell activity, and it can also influence the flocculation ability of microorganisms and reduce the settling properties of activated sludge in biological treatment processes [6,7]. So far, many studies have proved that inhibition takes place while the salinity is above 1 wt% [7,8,9]. Therefore, it is urgent and significant to find a more effective measure of wastewater treatment with high salinity.
At present, aerobic granular sludge (AGS) technology as a new wastewater treatment approach has aroused general concern. AGS is a special case of biofilm with self-immobilization [10]. Compared with the conventional activated sludge, it has the advantages of a stable structure, good sedimentation property, ability to withstand shock and toxic loadings, and capability of simultaneous COD, nitrogen, and phosphorus removal [11,12]. It is these unique advantages that render AGS a small footprint, lower cost, and simplicity of operation. After years of development, the applied field of AGS has not been confined to wastewater aerobic treatment, but to treating high-density organic wastewater, phenolic acid wastewater, heavy metal wastewater, and so on [13,14,15]. Naturally, there is increasing interest in the use of AGS for saline wastewater treatment.
A lot of research results have indicated that the AGS system is effective for wastewater with high inorganic salts, including NaCl [16,17]. Although the presence of salt created a greater resistance to precipitation through higher buoyant forces, it contributed to screening out sludge particles with better settling performance. Due to the different sensitivities of microbial flora to salinity stress, the removal efficiency and metabolic mechanism of pollutants are quite different. Pronk et al. [18] found that ammonia oxidation remained unaffected at a salinity level of 20 g/L, whereas nitrite oxidation and phosphate removal were significantly inhibited. The study of He et al. [19] suggested that nitrogen removal efficiency was not affected by salinity levels up to 20 g/L, while the phosphorus removal process experienced complete degradation at a salinity level up to 20 g/L. Wang et al. [20] investigated the response mechanism of an AGS system under different salinities in a sequencing batch reactor, and the results showed that the removal efficiencies of COD, TN and TP decreased with increasing salt stress in an AGS system. These studies were based on mature granular sludge, while few works have been conducted to demonstrate the effects of salt on performance in COD, nitrogen and phosphorus removal during the granulation process. In addition, the strategy of gradually increasing salinity could gradually adapt microorganisms to changes in osmotic pressure caused by salinity and weaken the adverse effects of salinity on microorganisms. This strategy has effectively been implemented in a flocculent sludge system to mitigate the negative impact of salinity on nitrification [21]. Furthermore, it is necessary to study the granulation process under the strategy of gradual increasing salinity.
Thus, this study aimed to evaluate the effect of a gradual increase in salt on the performance and microbial community structure of an AGS reactor. A sequencing batch reactor (SBR) fed with stepwise increasing salinity was started up and operated. And the focus was put on examining the impact of salt stress, including the secretion of extracellular polymeric substances (EPS), reactor nutrient performance and the microbial community under varying concentrations of NaCl (0, 10, 20, 30 and 40 g/L). The results obtained from this study will be helpful in enriching the existing theoretical knowledge of AGS and will provide a scientific basis to both process designers and decision makers about the application of AGS to treat salinity wastewater in the future.

2. Materials and Methods

2.1. Reactor Start-Up and Operation

A sequencing batch reactor (SBR) with an effective working volume of 2.0 L (H/D = 11.67) was used in this experiment. Aeration was supplied with an airflow rate of 1.6 L/min to produce an up-flow air velocity of 1.6 cm/s. The programable logic controller (PLC) was utilized to operate the peristaltic pumps and aeration pump, ensuring the continuous and automated functioning of the reactors. The rector was operated in 4 h sequential cycles comprising four stages, filling (60 min), reaction (170 min), settling (5 min) and drawing (5 min), which were automated through time switches. Effluent was discharged at the middle of reactor to ensure the volumetric exchange ratio of each reactor at 50%, corresponding to a hydraulic retention time (HRT) of 8 h. The operation process (total 95 d) divided into five stages with different NaCl concentrations (0, 10, 20, 30 and 40 g/L) was conducted to investigate the effects of salt stress on the performance of an aerobic SBR. The duration of each stage was 14 d, 20 d, 20 d, 20 d and 21 d, respectively.

2.2. Inoculated Sludge and Synthetic Wastewater

A certain amount of activated sludge taken from a local sewage treatment plant in Harbin was inoculated to guarantee that the approximate concentration of mixed liquor volatile suspended solid (MLVSS) was 0.91 g/L. The composition and concentrations of synthetic saline wastewater used through the experimental period were as follows (g/L): 0.78 NaAc, 0.43 glucose, 0.20 NH4Cl, 0.02 K2HPO4, 0.037 KH2PO4·3H2O, 0.05 MgSO4·7H2O and 0.025 CaCl2·2H2O. Moreover, 1 mL/L trace element solution consisted of 0.02 g/L FeSO4·7H2O, 0.05 g/L CuSO4·5H2O, 0.05 g/L H3BO4, 0.05 g/L MnCl2·4H2O, 0.01 g/L NaMoO4·2H2O, 0.01 g/L ZnSO4·7H2O and 0.05 g/L CoCl2·6H2O was also added in the saline wastewater. The pH of the influent was maintained within a range of 7.0 ± 0.2 through the addition of NaHCO3.

2.3. Analytical Methods

The reactor was consistently sampled for effluent and mixed liquor at specific intervals during the entire duration of the experiment. Parameters including chemical oxygen demand (COD), ammonia nitrogen (NH4+-N), nitrite (NO2-N), nitrate (NO3-N) and total phosphorus (TP), MLVSS and the sludge volume index after 5 min (SVI5) were measured according to the standard methods [22]. The laser particle size analyzer (MASTERSIZER 2000, Malvern, UK) was employed to measure the sludge size. The microscopic morphology of granules at the final stage was observed via scanning electron microscopy (SEM) (SU8010, Hitachi, Japan). The pretreatment method of the granular sample before the SEM observation was based on that used by Wang et al. [20]. A heating technique was employed to extract the EPS including the loosely bound EPS (LB-EPS) and the tightly bound EPS (TB-EPS) from sludge samples [23]. The protein (PN) and polysaccharide (PS) content were determined using the modified Lowry method [24] and the phenol-sulfuric acid method [25], respectively. The qualitative analysis of the extracted EPS components was conducted using a fluorescence spectrophotometer (FP-6500, JASCO, Tokyo, Japan). All the experiments were carried out in triplicate, and all the calculated results were shown as the mean. One-way analysis of variance (ANOVA) was performed to compare the mean sludge size at different salinities.
Sludges at the end of each salinity phase (R10, R20, R30 and R40) were sampled, except inoculated sludge (SEED), to identify the microbial community dynamics. The DNA extraction of samples was performed using the E.Z.N.ATM Mag-Bind Soil DNA Kit (M5635-02, OMEGA, USA) in accordance with the instructions provided by the manufacturer. The distinct regions (V3-V4) of the 16S rRNA gene were amplified with PCR using the bacterial universal primers 338F (5′-ACTCCT ACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). The microbial community analysis of all samples was outsourced and conducted by Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China).

3. Results and Discussion

3.1. Effect on Granulation Process

The reactor was run for a total of 95 d and AGS was successfully cultured. As shown in Figure 1a–c, the inoculation sludge was loose overall, while the sludge obviously agglomerated and the initial granules formed at day 14. Clearer and more regular edge profiles and denser structures in granules at day 34 were observed. This granular morphology was maintained and was visible to the naked eye. The SEM image of the granular sludge at the final stage is shown in Figure 1d,e. The saline granular sludge had good roundness and a dense structure, and there were many fine microparticles on the surface. The granules exhibited a high abundance of the microbial phase, characterized by the presence of both cocci and bacilli. At the same time, there were obvious films which encased the microorganisms on the surface of granules, possibly due to the secretion of EPS [26].
The evaluation of the granulation process under salinity conditions was conducted by considering several features such as MLVSS, SVI5 and sludge size, as presented in Table 1. The biomass of the reactor exhibited an initial increase followed by a decrease, reaching its maximum at day 34. Compared to the biomass growth during the 0–14-day stage, there was greater growth observed during the 14–34 day period, which could be attributed to a gradual adaptation of microorganisms to their environment. However, the biomass of the system gradually decreased from 3.52 g/L at 10 g/L salinity to 2.72 g/L at 40 g/L salinity thereafter. This change in MLVSS was similar to that observed in other studies [27]. On the one hand, high salinity as a hydraulic selective pressure led to an increase in fluid density, which enhanced the intensity of hydraulic scour and caused significant biomass loss; on the other hand, salinity retarded biomass growth [28]. According to the results of SVI5, the formation of granular sludge led to a gradual decrease in the SVI5 values and the sedimentation performance was obviously improved. The SVI5 of the sludge remained consistently below 60 mL/g after day 34, indicating that the sedimentation performance of granules was not easily influenced by salinity. The higher salt concentration resulted in the increased buoyancy of wastewater and facilitated the separation of light flocculent sludge out of the reactor. Consequently, sludge aggregations with superior settling performance could be retained in the reactor. Moreover, the high concentration of Na+ resulted in the compression of the double electric layer on the surface of granules, which enhanced the agglomeration ability of sludge. The mean size of sludge initially increased and subsequently decreased and the particle size at day 14–54 increased more slowly compared with the non-salinity condition. Possible explanations for this outcome included (a) a reduction in biological yield; (b) compression of double electric layers; and (c) the weakening of the EPS structure [18]. The marks of ANOVA were d, c, b, c and a at different salinities, which showed that there was no significant difference at 10 g/L and 30 g/L salinity.

3.2. Effect on EPS Secretion

EPS containing PN and PS played a crucial role in facilitating microbial aggregation and maintaining the stability of aerobic granules, while also providing protection against harsh environmental conditions [29]. Figure 2 illustrates the variations in PN and PS concentrations in LB-EPS and TB-EPS during reactor operation. The altered living environment stimulated significant EPS secretion by microorganisms initially, leading to substantial increases in both LB-PN and TB-PN. The concentrations of LB-PN and TB-PN were 121.94 mg/g VSS and 130.63 mg/g VSS, respectively. The PN/PS ratio simultaneously increased from the initial value of 4.32 to 7.19, leading to an improvement in hydrophobicity and enhanced sludge aggregation performance, thereby ensuring the formation and stability of AGS. The decrease in EPS concentration at day 34 indicated the adaptation of microorganisms to high shear force and a salinity of 10 g/L. However, the subsequent increase in salinity resulted in a simultaneous increase in PN and PS. Microorganisms could enhance ion transport by secreting a higher quantity of extracellular enzymes, predominantly PN, to mitigate the disparity in intracellular and extracellular ion concentrations induced by elevated salinity levels and to maintain osmotic pressure balance [30]. Furthermore, microorganisms tended to increase the secretion of PS containing numerous polar groups when confronted with salinity stress to prevent cellular dehydration [31]. The change in PS is more significant compared to that in PN, resulting in a gradual decrease in the PN/PS ratio to 1.53 at day 54. Li et al. [31] also observed that the abundance of polar groups in PS rendered its content more sensitive than that of PN. In the final stage, PN and PS contents decreased from 173.92 mg/g VSS and 94.21 mg/g VSS to 134.79 mg/g VSS and 76.46 mg/g VSS, respectively, indicating that the microorganisms gradually adapted to the salinity stress and the system tended to be stable. Moreover, LB-EPS consistently exhibited significantly smaller concentrations than TB-EPS under saline conditions, regardless of PN or PS. TB-EPS seemed to play a more important role in the stability of granules because it could enhance the zeta potential and hydrophobicity of the sludge cells’ surface and contribute to cell attachment [32].
To further investigate the components of EPS in the granulation process, 3D-EEM was conducted at day 34 and 95, as shown in Figure 3. It was important to note that the peak fluorescence intensity detected in LB-EPS at day 34 exhibited a significantly low level due to its extremely low concentration. On the contrary, Peak A (Ex/Em = 275/340) with high fluorescence intensity attributed to protein-like fluorescence peaks was found in TB-EPS at day 34. Moreover, Peak B (Ex/Em = 225/335), another protein-like fluorescence peaks, was also observed in TB-EPS. Peak A was linked to soluble microbial by-products such as tryptophan and protein-like, while peak B was associated with simple aromatic amino acids like tyrosine [33]. Peak C (Ex/Em = 270/440) and Peak D (Ex/Em = 355/440) associated with humic acids were observed in TB-EPS on day 34. This may originate from the decomposition of deceased cells and macromolecular organic compounds (PN and PS) caused by salinity [34]. With the granulation process and the increase in salinity, the fluorescence components in EPS were not significant, while the fluorescence intensity of each substance was different. Peak A appeared in LB-EPS on day 95 and the fluorescence intensity of Peak A in TB-EPS increased from 223.32 to 297.04. Obviously, PN played an important role in promoting the formation and stability of saline granular sludge. In addition, Peak C and Peak D were still present because of salinity.

3.3. Effect on Performance of Reactor

The performance in COD, and the nitrogen and phosphorus removal of the reactor were detected and analyzed, as shown in Figure 4. Each increase in salinity induced fluctuations of COD concentration in the effluent. The COD removal rate decreased to 80.67% after the initial addition of salt, while subsequent additions of salt did not result in a reduction in the COD removal rate below 90%. This phenomenon may be attributed to enhanced granule maturity and stability with the operation of the reactor. Furthermore, every reduction in COD removal rate can be promptly restored, resulting in an overall high removal rate throughout operation. These results indicated that heterotrophic bacteria, a very wide group of different bacteria, could use carbon sources in different salinities, aligning with previous studies by Kim et al. [35].
The changes in nitrogen composition during operation are illustrated in Figure 4b. The presence of a salinity level of 10 g/L also led to the short-term deterioration and gradual recovery of the TN removal rate, while higher salinity levels caused a progressive decrease in the overall nitrogen removal rate from 85.59% at 10 g/L to 64.18% at 40 g/L. Obviously, the increase in effluent NH4+-N concentration was an important reason for the decrease in TN removal rate. The abrupt salinity change induced an elevation of effluent NH4+-N concentration, which correlated with reduced nitrification rates resulting from increased salinity levels. In addition, the sudden change in salinity brought about the loss of sludge, leading to a decrease in the nitrifying bacteria population and consequently an increase in effluent NH4+-N concentration. The ammonia-oxidizing bacteria gradually acclimated to the salinity conditions and the removal rate of NH4+-N partially recovered. However, the effluent NH4+-N concentration under the conditions of 30 g/L and 40 g/L was still high with 9.28 mg/L and 16.18 mg/L, respectively. The initiation of salt addition at day 14 resulted in both a decrease in NO3-N and an increase in NO2-N in the effluent, indicating that the activity of nitrite-oxidizing bacteria was inhibited. However, the subsequent observation of reduced NO2-N and no-detected NO3-N indicated the enhancement of denitrification in the system. Due to the restriction of mass transfer, the anoxic layer formed inside the granules provided favorable conditions for the growth of denitrifying functional bacteria. After that, the subsequent accumulation of NO2-N was observed, which may be due to the fact that nitrite reductase is more sensitive to salinity than nitrate reductase. A subsequent sudden change in salinity led to a dramatic decrease in effluent NO2-N and then a slight accumulation of nitrite was observed. This phenomenon has been observed at 20 g/L and 30 g/L salinity, which indicated the gradual adaptation of ammoxidation bacteria and the inhibiting effect of nitrite-oxidizing bacteria to salinity. While NO2-N in effluent could not be detected at 40 g/L salinity, NO3-N in effluent was never detected at any salinity level. This suggested that ammonia-oxidizing bacteria exhibited a higher tolerance to salinity compared to nitrite-oxidizing bacteria [36]. Additionally, partial nitrification and denitrification may nitrogen removal pathway under salinity conditions. Figure 4c shows the change in phosphorus removal efficiency. The low TP removal efficiency in the initial stage of operation was due to the low sludge concentration of the reactor. Since then, the metabolic activity of polyphosphate accumulators was inhibited by salinity [20], leading to consistently low TP removal efficiency. In addition, the presence of salinity may inhibit oxygen penetration, limiting oxygen availability within the inner layer of granules and affecting microbial activity and metabolism adversely, thereby compromising phosphorus removal [19].

3.4. Effect on Microbial Community Structure

As shown in Table 2, high coverage (>0.99) was found in all samples, indicating that sequencing results can effectively characterize microbial communities and ensure the robustness of diversity analysis results. SEED has the highest bacterial diversity because the granulation process primarily selects species with strong self-aggregation or coaggregation capabilities [37]. Moreover, microbial diversity gradually decreased with the increase in salinity, as evidenced by the decrease in the Shannon index and the increase in the Simpson index. Ace and Chao1 values also followed the decreasing trend of R10 > R20 > R30 > R40, indicating that sludge granulation and salinity stress reduced bacterial abundance. The decline in microbial diversity and abundance may stem from the inhibition of salinity in the reproduction of non-adapted microorganisms, which has been similarly concluded in other studies [38].
The microbial community structure at the phylum and class levels was depicted in Figure 5, representing SEED, R10, R20, R30 and R40 from innermost to outermost. Proteobacteria emerged as the predominant phylum across all samples. Except for SEED which ranked second in relative abundance, Proteobacteria had the highest relative abundance in other samples. Previous studies have confirmed that the majority of heterotrophic bacteria capable of organic matter degradation belong to Proteobacteria [39], and several types of denitrification bacteria have also been classified within this phylum [40]. The relative abundance of Proteobacteria in R40 even reached 90.96%, potentially attributed to the proliferation of halophilic heterotrophic bacteria induced by salinity [41]. Simultaneously, the consistent presence of Bacteroidota across all samples ensured efficient nitrogen removal under saline conditions, as it has been proved to have high capability for the oxidation of ammonium [37] and is associated with salt-tolerant denitrifying bacteria [41]. In addition, Proteobacteria tended to secrete EPS in unfavorable environments that promoted granulation [42]. Actinobacteriota was believed to have a positive impact in promoting sludge flocculation and was also highly abundant in all samples apart from R40. Patescibacteria was also exclusively found in samples other than R40, exhibiting an abundance of 28.67% in R30, suggesting some degree of salt tolerance. In addition, Chloroflexi with a high relative abundance (13.60%) in the inoculated sludge was not found in salinity samples, indicating its sensitivity to salinity changes [43].
At the class level, Acidimicrobiia which had the highest relative abundance (22.21%) in SEED was not detected in the remaining salinity samples, indicating that it was difficult to grow and accumulate during the granulation process with salinity. The predominant classes in R10, R20 and R30 were Alphaproteobacteria (35.05%, 39.72%, 31.95%) and Actinobacteria (25.46%, 39.38%, 26.96%), while Gammaproteobacteria (89.58) constituted the absolute dominant bacteria group present in R40. Alphaproteobacteria and Gammaproteobacteria encompassed a variety of bacteria capable of secreting EPS that contributed to granules stability maintenance [31,44]. In addition, the salt tolerance of Actinobacteria, which could promote flocculation, has been demonstrated. Moreover, Gammaproteobacteria was believed to play a crucial role in denitrification during saline wastewater treatment [38], which may explain the low levels of NO2-N and NO3-N observed in the system at 40 g/L salinity. Sphingobacteriia which was considered to be the main microorganism for organic matter removal and nitrogen removal [45] also has a high relative abundance in R10, R20 and R30.
The evolution of microbial community structure at the genus level was further investigated to gain insights into the population dynamics during the granulation process under salinity changes, as depicted in Figure 6. Candidatus_Microthrix (17.06%), norank_f_Saprospiraceae (6.14%) and norank_f_norank_o_Saccharimonadales (4.81%) were found to be dominant genera in the inoculated sludge. However, with the start-up of the granular sludge reactor, alterations in operating conditions and water quality environment led to the significant disappearance of these genera, and only a 3% abundance of norank_f_norank_o_Saccharimonadales remained in R10. The disappearance of Candidatus_Microthrix (Guo et al., 2012) and norank_f_Saprospiraceae may be associated with high shear condition because they were proved to undergo filamentous expansion [46,47]. At the same time, there were some novel genera appearing in R10, such as Lactococcus (5.94%), Paracoccus (7.50%), Propioniciclava (13.54%), Thauera (7.05%), TM7a (5.35%) and unclassified_f_Rhodobacteraceae (14.74%). Among these genera, Paracoccus and Thauera could secrete EPS [48] and played an important role in promoting sludge granulation. Meanwhile, Paracoccus, Thauera and unclassified_f_Rhodobacteraceae were also identified as denitrifying bacteria, and were involved in the removal of organic matter and nitrogen [47,49]. Propioniciclava belonging to the genus Actinobacteria could utilize various carbohydrates and has been found to degrade petrochemicals [50].
The microbial population structure would continue to change with the increase in salinity. However, Paracoccus (18.36%, 20.92%), Propioniciclava (25.17%, 14.54%), Thauera (7.15%, 1.96%) and unclassified_f_Rhodobacteraceae (11.43%, 4.42%) were still the dominant genera in R20 and R30. TM7a (28.51%) was a black horse and has the highest population abundance in R3. Its relative abundances were 5.35% and 3.79% in R10 and R20, respectively. The study by Zhang et al. [51] also showed that TM7a was a biomarker detected in an ammonium assimilation biological system with 3% salinity. Compared with the afore-mentioned samples, the microbial community structure of R40 showed significant changes. The above genera were eliminated due to salinity stress, while Azoarcus (75.89%), Halomonas (3.61%), unclassified_f_Flavobacteriaceae (8.28%) and Vibrio (9.58%) became the absolute dominant genera. These findings indicated that these genera had strong resistance and could adapt to high-saline conditions. Azoarcus was known for the formation of biofilms through the secretion of EPS [52] and has been reported to play an important role in the efficient removal of nitrate in high salinity [53]. Halomonas was one of the most advantageous genera in the biological treatment system for heterotrophic saline wastewater, closely associated with organic matter and nitrogen removal processes [54], and it could survive and maintain activity even in the presence of 5% NaCl concentration [55]. In addition, Vibrio has also been linked to denitrification processes and EPS production [42].

4. Conclusions

Salinity caused the loss of sludge biomass and had no effect on sedimentation performance. The microorganisms tended to secrete more PN and PS to protect themselves under saline conditions, and TB-EPS played a more important role in granule stabilization. The decrease in the COD values was not greatly affected by salinity, but led to a decrease in the removal rates of TN and NH4+-N. Phosphorus-accumulating bacteria are greatly affected by salinity, which made phosphorus removal efficiency low. Salinity caused the changes in microbial community structure. Candidatus_Microthrix, norank_f_Saprospiraceae and nor-ank_f_norank_o_Saccharimonadales were found to be dominant genera in the inoculated sludge. Paracoccus, Thauera and unclassified_f_Rhodobacteraceae were the common dominant genera at 10, 20 and 30 g/L salinity and were replaced by Azoarcus, Halomonas, unclassified_f_Flavobacteriaceae and Vibrio at 40 g/L salinity.

Author Contributions

Conceptualization, M.W. and J.H.; methodology, M.W.; software, M.W.; validation, M.W., J.H., and X.D.; formal analysis, M.W.; investigation, M.W.; resources, M.W.; data curation, M.W.; writing—original draft preparation, M.W.; writing—review and editing, M.W. and X.D.; visualization, M.W.; supervision, J.H., X.D. and J.Z.; project administration, J.H.; funding acquisition, J.H. All authors have read and agreed to the published version of the manuscript.


This research was funded by the National Natural Science Foundation of China (No. 52070048) and the Research and Development Project in Key Areas of Guangdong Province (No. 2019B110209002).

Data Availability Statement

Due to the nature of this research, participants in this study did not agree for their data to be shared publicly, so supporting data are not available.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Lefebvre, O.; Moletta, R. Treatment of organic pollution in industrial saline wastewater: A literature review. Water Res. 2006, 40, 3671–3682. [Google Scholar] [CrossRef] [PubMed]
  2. Castillo-Carvajal, L.C.; Sanz-Martin, J.L.; Barragan-Huerta, B.E. Biodegradation of organic pollutants in saline wastewater by halophilic microorganisms: A review. Environ. Sci. Pollut. Res. Int. 2014, 21, 9578–9588. [Google Scholar] [CrossRef] [PubMed]
  3. Sun, X.; Sun, Y.; Wang, H.; Yu, D. Experimental Study on Shortcut Nitrification of Sewage from Flushing Toilet with Seawater. In Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology, Wuhan, China, 4–5 July 2009; pp. 273–276. [Google Scholar]
  4. Kim, K.H.; Ihm, S.K. Heterogeneous catalytic wet air oxidation of refractory organic pollutants in industrial wastewaters: A review. J. Hazard. Mater. 2011, 186, 16–34. [Google Scholar] [CrossRef] [PubMed]
  5. Fakhru’l-Razi, A.; Pendashteh, A.; Abdullah, L.C.; Biak, D.R.; Madaeni, S.S.; Abidin, Z.Z. Review of technologies for oil and gas produced water treatment. J. Hazard. Mater. 2009, 170, 530–551. [Google Scholar] [CrossRef]
  6. Chen, Y.; He, H.; Liu, H.; Li, H.; Zeng, G.; Xia, X.; Yang, C. Effect of salinity on removal performance and activated sludge characteristics in sequencing batch reactors. Bioresour. Technol. 2018, 249, 890–899. [Google Scholar] [CrossRef]
  7. Uygur, A. Specific nutrient removal rates in saline wastewater treatment using sequencing batch reactor. Process Biochem. 2006, 41, 61–66. [Google Scholar] [CrossRef]
  8. Zhao, Y.; Park, H.D.; Park, J.H.; Zhang, F.; Chen, C.; Li, X.; Zhao, D.; Zhao, F. Effect of different salinity adaptation on the performance and microbial community in a sequencing batch reactor. Bioresour. Technol. 2016, 216, 808–816. [Google Scholar] [CrossRef]
  9. Amin, M.M.; Khiadani, M.H.; Fatehizadeh, A.; Taheri, E. Validation of linear and non-linear kinetic modeling of saline wastewater treatment by sequencing batch reactor with adapted and non-adapted consortiums. Desalination 2014, 344, 228–235. [Google Scholar] [CrossRef]
  10. Xia, J.; Ye, L.; Ren, H.; Zhang, X.X. Microbial community structure and function in aerobic granular sludge. Appl. Microbiol. Biotechnol. 2018, 102, 3967–3979. [Google Scholar] [CrossRef]
  11. de Kreuk, M.K.; Heijnen, J.J.; van Loosdrecht, M.C. Simultaneous COD, nitrogen, and phosphate removal by aerobic granular sludge. Biotechnol. Bioeng. 2005, 90, 761–769. [Google Scholar] [CrossRef]
  12. Gao, D.; Liu, L.; Liang, H.; Wu, W.M. Aerobic granular sludge: Characterization, mechanism of granulation and application to wastewater treatment. Crit. Rev. Biotechnol. 2011, 31, 137–152. [Google Scholar] [CrossRef] [PubMed]
  13. Corsino, S.F.; Campo, R.; Di Bella, G.; Torregrossa, M.; Viviani, G. Cultivation of granular sludge with hypersaline oily wastewater. Int. Biodeterior. Biodegrad. 2015, 105, 192–202. [Google Scholar] [CrossRef]
  14. Wang, J.; Gong, B.; Huang, W.; Wang, Y.; Zhou, J. Bacterial community structure in simultaneous nitrification, denitrification and organic matter removal process treating saline mustard tuber wastewater as revealed by 16s rRNA sequencing. Bioresour. Technol. 2017, 228, 31–38. [Google Scholar] [CrossRef] [PubMed]
  15. Xie, Y.R.W.; Zhang, X.H.; Xie, Q.L.; Bai, S.Y. A review on aerobic granular sludge for heavy metal wastewater treatment. Appl. Mech. Mater. 2014, 535, 213–216. [Google Scholar] [CrossRef]
  16. Corsino, S.F.; Capodici, M.; Morici, C.; Torregrossa, M.; Viviani, G. Simultaneous nitritation-denitritation for the treatment of high-strength nitrogen in hypersaline wastewater by aerobic granular sludge. Water Res. 2016, 88, 329–336. [Google Scholar] [CrossRef]
  17. Eom, H.; Kim, J.; Kim, S.; Lee, S.-S. Treatment of saline wastewater containing a high concentration of salt using marine bacteria and aerobic granule sludge. J. Environ. Eng. 2018, 144, 04018026. [Google Scholar] [CrossRef]
  18. Pronk, M.; Bassin, J.P.; de Kreuk, M.K.; Kleerebezem, R.; van Loosdrecht, M.C. Evaluating the main and side effects of high salinity on aerobic granular sludge. Appl. Microbiol. Biotechnol. 2014, 98, 1339–1348. [Google Scholar] [CrossRef]
  19. He, Q.; Wang, H.; Chen, L.; Gao, S.; Zhang, W.; Song, J.; Yu, J. Elevated salinity deteriorated enhanced biological phosphorus removal in an aerobic granular sludge sequencing batch reactor performing simultaneous nitrification, denitrification and phosphorus removal. J. Hazard. Mater. 2020, 390, 121782. [Google Scholar] [CrossRef]
  20. Wang, X.; Yang, T.; Lin, B.; Tang, Y. Effects of salinity on the performance, microbial community, and functional proteins in an aerobic granular sludge system. Chemosphere 2017, 184, 1241–1249. [Google Scholar] [CrossRef]
  21. Bassin, J.P.; Kleerebezem, R.; Muyzer, G.; Rosado, A.S.; van Loosdrecht, M.C.; Dezotti, M. Effect of different salt adaptation strategies on the microbial diversity, activity, and settling of nitrifying sludge in sequencing batch reactors. Appl. Microbiol. Biotechnol. 2012, 93, 1281–1294. [Google Scholar] [CrossRef]
  22. APHA. Standard Methods for the Examination of Water and Wastewater; American Public Health Association (APHA): Washington, DC, USA, 2005. [Google Scholar]
  23. Li, X.Y.; Yang, S.F. Influence of loosely bound extracellular polymeric substances (EPS) on the flocculation, sedimentation and dewaterability of activated sludge. Water Res. 2007, 41, 1022–1030. [Google Scholar] [CrossRef] [PubMed]
  24. Frølund, B.; Palmgren, R.; Keiding, K.; Nielsen, P.H. Extraction of extracellular polymers from activated sludge using a cation exchange resin. Water Res. 1996, 30, 1749–1758. [Google Scholar] [CrossRef]
  25. Dubois, M.; Gilles, K.; Hamilton, J.K.; Rebers, P.A.; Smith, F. Colorimetric method for determination of sugars and related substances. Anal. Chem. 1956, 28, 350–356. [Google Scholar] [CrossRef]
  26. Geng, M.; Ma, F.; Guo, H.; Su, D. Enhanced aerobic sludge granulation in a sequencing batch reactor (SBR) by applying mycelial pellets. J. Clean. Prod. 2020, 274, 123037. [Google Scholar] [CrossRef]
  27. Ou, D.; Li, W.; Li, H.; Wu, X.; Li, C.; Zhuge, Y.; Liu, Y.D. Enhancement of the removal and settling performance for aerobic granular sludge under hypersaline stress. Chemosphere 2018, 212, 400–407. [Google Scholar] [CrossRef]
  28. He, H.J.; Chen, Y.J.; Li, X.; Cheng, Y.; Yang, C.P.; Zeng, G.M. Influence of salinity on microorganisms in activated sludge processes: A review. Int. Biodeterior. Biodegrad. 2017, 119, 520–527. [Google Scholar] [CrossRef]
  29. He, Q.; Song, Q.; Zhang, S.; Zhang, W.; Wang, H. Simultaneous nitrification, denitrification and phosphorus removal in an aerobic granular sequencing batch reactor with mixed carbon sources: Reactor performance, extracellular polymeric substances and microbial successions. Chem. Eng. J. 2018, 331, 841–849. [Google Scholar] [CrossRef]
  30. Wang, Z.C.; Gao, M.C.; Wei, J.F.; Ma, K.D.; Pei, J.; Zhang, J.; Zhou, Y.; Yang, Y.S.; Yu, S.P. Long-term effects of salinity on extracellular polymeric substances, microbial activity and microbial community from biofilm and suspended sludge in an anoxic-aerobic sequencing batch biofilm reactor. J. Taiwan Inst. Chem. Eng. 2016, 68, 275–280. [Google Scholar] [CrossRef]
  31. Li, J.; Ye, W.; Wei, D.; Ngo, H.H.; Guo, W.; Qiao, Y.; Xu, W.; Du, B.; Wei, Q. System performance and microbial community succession in a partial nitrification biofilm reactor in response to salinity stress. Bioresour. Technol. 2018, 270, 512–518. [Google Scholar] [CrossRef]
  32. Wang, Y.; Wang, J.; Liu, Z.; Huang, X.; Fang, F.; Guo, J.; Yan, P. Effect of EPS and its forms of aerobic granular sludge on sludge aggregation performance during granulation process based on xdlvo theory. Sci. Total Environ. 2021, 795, 148682. [Google Scholar] [CrossRef]
  33. Zhao, L.; She, Z.; Jin, C.; Yang, S.; Guo, L.; Zhao, Y.; Gao, M. Characteristics of extracellular polymeric substances from sludge and biofilm in a simultaneous nitrification and denitrification system under high salinity stress. Bioprocess. Biosyst. Eng. 2016, 39, 1375–1389. [Google Scholar] [CrossRef] [PubMed]
  34. Qu, F.; Liang, H.; He, J.; Ma, J.; Wang, Z.; Yu, H.; Li, G. Characterization of dissolved extracellular organic matter (dEOM) and bound extracellular organic matter (bEOM) of microcystis aeruginosa and their impacts on uf membrane fouling. Water Res. 2012, 46, 2881–2890. [Google Scholar] [CrossRef] [PubMed]
  35. Kim, H.; Ahn, D. The effects of high salinity on nitrogen removal and the formation characteristics of aerobic granular sludge. Environ. Eng. Res. 2019, 25, 659–667. [Google Scholar] [CrossRef]
  36. Ghafari, S.; Hasan, M.; Aroua, M.K. Improvement of autohydrogenotrophic nitrite reduction rate through optimization of ph and sodium bicarbonate dose in batch experiments. J. Biosci. Bioeng. 2009, 107, 275–280. [Google Scholar] [CrossRef] [PubMed]
  37. Zhang, X.; Liu, Y.; Li, J.; Wei, Z.; Duan, W.; Chen, F. Enhancing effects of sludge biochar on aerobic granular sludge for wastewater treatment. Processes 2022, 10, 2385. [Google Scholar] [CrossRef]
  38. Xia, Z.; Wang, Q.; She, Z.; Gao, M.; Zhao, Y.; Guo, L.; Jin, C. Nitrogen removal pathway and dynamics of microbial community with the increase of salinity in simultaneous nitrification and denitrification process. Sci. Total Environ. 2019, 697, 134047. [Google Scholar] [CrossRef]
  39. Qin, Y.; Cao, Y.; Ren, J.; Wang, T.; Han, B. Effect of glucose on nitrogen removal and microbial community in anammox-denitrification system. Bioresour. Technol. 2017, 244, 33–39. [Google Scholar] [CrossRef]
  40. Ji, J.; Peng, Y.; Wang, B.; Mai, W.; Li, X.; Zhang, Q.; Wang, S. Effects of salinity build-up on the performance and microbial community of partial-denitrification granular sludge with high nitrite accumulation. Chemosphere 2018, 209, 53–60. [Google Scholar] [CrossRef]
  41. Wang, Z.; Gao, P.; Ji, Y.; Zhang, H.; Wu, X.; Ma, J.; Li, S. Effects of salinity on the simultaneous anammox and denitrification process: Performance, sludge morphology and shifts in microbial communities. R. Soc. Open Sci. 2021, 8, 202099. [Google Scholar] [CrossRef]
  42. Tang, R.; Han, X.; Jin, Y.; Yu, J. Do increased organic loading rates accelerate aerobic granulation in hypersaline environment? J. Environ. Chem. Eng. 2022, 10, 108775. [Google Scholar] [CrossRef]
  43. Zeng, D.F.; Liang, K.; Guo, F.; Wu, Y.H.; Wu, G.X. Denitrification performance and microbial community under salinity and mit stresses for reverse osmosis concentrate treatment. Sep. Purif. Technol. 2020, 242, 116799. [Google Scholar] [CrossRef]
  44. Wang, X.; Chen, Z.; Shen, J.; Zhao, X.; Kang, J. Impact of carbon to nitrogen ratio on the performance of aerobic granular reactor and microbial population dynamics during aerobic sludge granulation. Bioresour. Technol. 2019, 271, 258–265. [Google Scholar] [CrossRef] [PubMed]
  45. Tang, B.; Chen, Q.; Bin, L.; Huang, S.; Zhang, W.; Fu, F.; Li, P. Insight into the microbial community and its succession of a coupling anaerobic-aerobic biofilm on semi-suspended bio-carriers. Bioresour. Technol. 2018, 247, 591–598. [Google Scholar] [CrossRef] [PubMed]
  46. Guo, J.; Peng, Y.; Wang, S.; Yang, X.; Wang, Z.; Zhu, A. Stable limited filamentous bulking through keeping the competition between floc-formers and filaments in balance. Bioresour. Technol. 2012, 103, 7–15. [Google Scholar] [CrossRef] [PubMed]
  47. He, Q.; Zhang, J.; Gao, S.; Chen, L.; Lyu, W.; Zhang, W.; Song, J.; Hu, X.; Chen, R.; Wang, H.; et al. A comprehensive comparison between non-bulking and bulking aerobic granular sludge in microbial communities. Bioresour. Technol. 2019, 294, 122151. [Google Scholar] [CrossRef]
  48. Paulo, A.M.S.; Amorim, C.L.; Costa, J.; Mesquita, D.P.; Ferreira, E.C.; Castro, P.M.L. Long-term stability of a non-adapted aerobic granular sludge process treating fish canning wastewater associated to EPS producers in the core microbiome. Sci. Total Environ. 2021, 756, 144007. [Google Scholar] [CrossRef]
  49. He, Q.; Chen, L.; Zhang, S.; Chen, R.; Wang, H. Hydrodynamic shear force shaped the microbial community and function in the aerobic granular sequencing batch reactors for low carbon to nitrogen (C/N) municipal wastewater treatment. Bioresour. Technol. 2019, 271, 48–58. [Google Scholar] [CrossRef]
  50. Chen, C.; Ming, J.; Yoza, B.A.; Liang, J.; Li, Q.X.; Guo, H.; Liu, Z.; Deng, J.; Wang, Q. Characterization of aerobic granular sludge used for the treatment of petroleum wastewater. Bioresour. Technol. 2019, 271, 353–359. [Google Scholar] [CrossRef]
  51. Zhang, M.; Han, F.; Chen, H.; Yao, J.; Li, Q.; Li, Z.; Zhou, W. The effect of salinity on ammonium-assimilating biosystems in hypersaline wastewater treatment. Sci. Total Environ. 2022, 829, 154622. [Google Scholar] [CrossRef]
  52. Li, J.; Ma, Z.; Gao, M.; Wang, Y.; Yang, Z.; Xu, H.; Wang, X.-H. Enhanced aerobic granulation at low temperature by stepwise increasing of salinity. Sci. Total Environ. 2020, 722, 137660. [Google Scholar] [CrossRef]
  53. Ruan, Y.J.; Deng, Y.L.; Guo, X.S.; Timmons, M.B.; Lu, H.F.; Han, Z.Y.; Ye, Z.Y.; Shi, M.M.; Zhu, S.M. Simultaneous ammonia and nitrate removal in an airlift reactor using poly(butylene succinate) as carbon source and biofilm carrier. Bioresour. Technol. 2016, 216, 1004–1013. [Google Scholar] [CrossRef] [PubMed]
  54. Miao, S.; Jin, C.; Liu, R.; Bai, Y.; Liu, H.; Hu, C.; Qu, J. Microbial community structures and functions of hypersaline heterotrophic denitrifying process: Lab-scale and pilot-scale studies. Bioresour. Technol. 2020, 310, 123244. [Google Scholar] [CrossRef] [PubMed]
  55. Garcia, M.T.; Ventosa, A.; Mellado, E. Catabolic versatility of aromatic compound-degrading halophilic bacteria. FEMS Microbiol. Ecol. 2005, 54, 97–109. [Google Scholar] [CrossRef] [PubMed]
Figure 1. The micro morphological images of granular sludge at day 0 (a), 14 (b), 34 (c) and 95 (d,e).
Figure 1. The micro morphological images of granular sludge at day 0 (a), 14 (b), 34 (c) and 95 (d,e).
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Figure 2. Variation in EPS content (PN and PS) during operation process.
Figure 2. Variation in EPS content (PN and PS) during operation process.
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Figure 3. 3D-EEM characteristics of LB-EPS and TB-EPS of AGS at day 34 (a,b) and 95 (c,d).
Figure 3. 3D-EEM characteristics of LB-EPS and TB-EPS of AGS at day 34 (a,b) and 95 (c,d).
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Figure 4. Variations in COD removal (a), nitrogen removal (b) and phosphorus removal (c).
Figure 4. Variations in COD removal (a), nitrogen removal (b) and phosphorus removal (c).
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Figure 5. Microbial community structure of sludge samples on phylum (a) and class (b) level, representing SEED, R10, R20, R30 and R40 from innermost to outermost.
Figure 5. Microbial community structure of sludge samples on phylum (a) and class (b) level, representing SEED, R10, R20, R30 and R40 from innermost to outermost.
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Figure 6. Heat map of the identified genus of sludge samples at different stages.
Figure 6. Heat map of the identified genus of sludge samples at different stages.
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Table 1. Variations in MLVSS, SVI5 and sludge size during operation process.
Table 1. Variations in MLVSS, SVI5 and sludge size during operation process.
Time (d)Salinity (g/L)MLVSS (g/L)SVI5 (mL/g)Size (μm)
00.91 ± 0.17257.66 ± 6.2189.08 ± 0.84
1401.37 ± 0.21102.99 ± 5.36333.71 ± 21.8
34103.52 ± 0.1358.47 ± 3.32396.07 ± 6.14
54203.43 ± 0.1846.34 ± 2.36443.39 ± 17.96
74303.15 ± 0.1750.68 ± 3.55406.47 ± 10.43
95402.72 ± 0.2252.28 ± 3.24373.09 ± 3.22
Table 2. Richness and diversity indices of sludge samples.
Table 2. Richness and diversity indices of sludge samples.
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Wang, M.; He, J.; Dong, X.; Zhang, J. Effect of Salinity on Performance and Microbial Community during Granulation Process in a Sequencing Batch Reactor. Water 2023, 15, 3961.

AMA Style

Wang M, He J, Dong X, Zhang J. Effect of Salinity on Performance and Microbial Community during Granulation Process in a Sequencing Batch Reactor. Water. 2023; 15(22):3961.

Chicago/Turabian Style

Wang, Mengfei, Junguo He, Xiangke Dong, and Jie Zhang. 2023. "Effect of Salinity on Performance and Microbial Community during Granulation Process in a Sequencing Batch Reactor" Water 15, no. 22: 3961.

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