Quantitative study of biofilm yield and biomass distribution of a multi-stage moving-bed biofilm system

Moving-bed biofilm reactors (MBBRs) consist of free-suspended carrier elements, the surface of which provides attachment sites for biofilm growth (Leyva-Díaz et al. 2013). The compact design, simple operation, no requirement for sludge recycling, high microbial activity, and stable nitrification make MBBRs highly effective for nitrogen removal from wastewater (Morgan-Sagastume 2018; Ooi et al. 2018; Du et al. 2022). The MBBR process has a higher biomass residence time compared to the activated sludge method (Avcioglu et al. 1998), which provides favorable conditions for the enrichment of nitrifying bacteria with low specific growth rates (Gu et al. 2014; Li et al. 2020) while ensuring the biomass number. According to the main mode of microbial presence, MBBR systems can be divided into hybrid MBBR (i.e., IFAS) or pure MBBR technology. Due to China's wastewater treatment issues, such as small land area, high standards, and poor stability, IFAS has been successfully used in upgrading Chinese wastewater treatment plants with its unique advantages. However, there are fewer studies investigating the microbial growth and application of pure MBBR, especially for the multi-stage pure MBBR process.

Based on the reaction kinetics principle to optimize the removal process of pollutants, staging biological reactors has been proposed (Joss et al. 2006). Due to the advantages of the original MBBR process, the multi-stage MBBR process has become a novel process preference in recent years due to its ability to control the concentration and nature of the growth substrate in contact with the biomass and the ability to grow different types of active microbial systems in a targeted manner (Polesel et al. 2017; Torresi et al. 2017). Additionally, it was shown that significant differences in microbial communities for nitrogen removal and pollutants biotransformation in the multi-stage MBBR were determined by the different gradients of organic loading and mass concentrations (Polesel et al. 2017). Furthermore, the special operating mode of multiple reactors in series is more conducive to screening and enrichment of dominant nitrifying bacteria (Zhang et al. 2019; Fan et al. 2022). At present, the research on the multi-stage pure membrane A/O-MBBR system mostly focuses on the conversion relationship of carbon and nitrogen removal, while the complex biomass distribution and activity that play a key role in this relationship are less studied.

The biological treatment process of wastewater is completed through a series of complex microbial metabolic processes. Low temperature can directly affect the growth and metabolism of biomass and inhibit microbial activity, especially the inhibition of autotrophic nitrifying bacteria (Antoniou et al. 1990). Although MBBR is considered an option to ensure the effective removal of pollutants under low-temperature conditions, the weakening effect of low temperature on pollutant removal efficiency during winter is not negligible.

Delatolla et al. (2010) discovered that when the temperature dropped from 14 to 3 °C, the ammonium nitrogen removal rate decreased by 73% (from 0.60 to 0.16 kg-N/(m³·d)). Ashkanani et al. (2019) noticed a reduction of 54.7, 62.3, and 89%, respectively, in the surface ammonia removal rate of MBBR systems using different bio-carriers as the temperature decreased from 35 to 4 °C. Regarding the effect of temperature on denitrification, it has been shown that low temperatures directly affect the hydrolysis rate of substrates involved in denitrification and the activity of denitrifying reductases (Fu et al. 2022). While denitrification will be abolished at temperatures below 3 °C (Ghafari et al. 2008), Young et al. (2017a) showed that a temperature dropping to 5 °C led to a decrease in denitrification rates by 50%. Whereas studies reflecting the effect of temperature on nitrification and denitrification in terms of ammonia removal rates are adequate, it remains to be considered how temperature directly affects biomass distribution and activity which influences nitrification and denitrification from a microbiological perspective. Young et al. (2017a) showed that the increase in biofilm thickness of the MBBR system at low temperatures can compensate for the increase in the ammonia removal efficiency of single cells to improve the nitrification performance. Therefore, the number of active biomass and the cells’ activity per unit surface area largely determine the final treatment effect of the system. Studies investigating the inhibition effect of low-temperature conditions focused on the influence on nitrification efficiency, while the effect of low temperature on heterotrophic denitrification remains to be elucidated. Moreover, it has been previously shown that the microbial activity of pure MBBR occurs only in the biofilm, even when the wastewater contains exfoliated biofilms and free-growing microbial suspension carriers (Piculell et al. 2014; di Biase et al. 2021). In that case, it is particularly important to consider biomass composition, activity, and diversity when assessing its function (Helbling et al. 2015; Johnson et al. 2015; Torresi et al. 2018).

Therefore, the use of respirometry combined with the Activated Sludge Model No 1 (AMS1) equation (Henze et al. 2000; Ferrai et al. 2010), which consists of biofilm growth and decay, would represent a tool to measure microbial activity and composition to obtain the number and kinetic parameters of active biomass in the reactor while reflecting the activity of different types of biomass (Bina et al. 2018). The oxygen uptake rate (OUR, ⁠) is an important parameter in respirometric techniques for assessing biomass viability. Different specific respiration rates (SOUR, ⁠) indicate the respiration rate per unit mass of biofilm. Current respirometry techniques have been used to assess various aspects such as the kinetics of bacteria and activated sludge (Sánchez-Zurano et al. 2022); the biodegradability of municipal and industrial wastewater (Hayet et al. 2016); biomass activity and wastewater characterization in UCT-MBR pilot plants (Di Trapani et al. 2011); the toxicity of pharmaceutical compounds in activated sludge (Vasiliadou et al. 2018); and the effect of alkyl phenolic compounds on kinetic coefficients and biomass activity in MBBR (Bina et al. 2018). Respirometry has become a common technique for assessing microbial activity and characterizing microbial performance. Considering that the type of substrate in the reactor affects the kinetic parameters (Amin et al. 2013; Mansouri 2014), it is necessary and beneficial to determine the kinetic parameters of the more sensitive microorganisms under different conditions to develop a suitable design for simulating biological processes. Among them, the accurate quantification of the yield coefficient of heterotrophic biomass (Y_H) will promote the reasonable control of source dosage under low-temperature conditions in winter.

Here, we evaluated the effect of temperature changes on the distribution and activity of active biomass in a multi-stage MBBR system. With the help of respirometric techniques and the ASM1 equation, we characterized biomass viability. A method for reflecting the nitrification and denitrification capacity per unit mass of biomass in terms of SOUR was described and the effect of temperature variation on this as well as on Y_H was reported. High-throughput techniques aid in analyzing the correlation between microbial communities and active biomass. We provided a simple and rapid method to measure and compare the microbial performance in each reactor of the multi-stage MBBR system.

The system inlet water was pumped from the effluent primary sedimentation tank of the wastewater treatment plant, and an air floatation tank was applied as additional pretreatment for particle separation before the raw wastewater entered the pilot system (inlet wastewater characteristics are shown in Table 1). The water quality parameters for each reactor stage are shown in Table 2. Due to variation of the actual sewage, the above water quality parameters are within the normal range of variation.

The good fluidization state of the suspended bio-carrier was ensured by a wavemaker, which allows full contact with the nutrients in the water. An aeration system with a 6 cm bread bubble tray was connected to an 8 L/min aeration pump via an oxygen pipe and operating at a constant airflow. A portable DO meter, the Hash HQ40d (HACH, Loveland, CO, USA), was used in connection with the data collection system for real-time monitoring of the DO concentration in the reactor at a frequency of 1 min. A wireless temperature measurement device was used to obtain the reactor's internal temperature in real-time to facilitate the timely treatment of temperature abnormalities.

During the first step, the suspended bio-carriers were rinsed 3–5 times with tap water to remove the attached organic matter, allowing them to enter the endogenous respiration phase, which can be verified by continuous monitoring of the DO curves. Full aeration was carried out to make the DO concentration in the reactor reach the saturated DO (10–12 mg O₂/L) before entering the next stage. During the second stage, when the DO concentration in the batch set-up reached 10–12 mg O₂/L, a prepared ammonium chloride solution of a certain concentration was measured with a pipette and injected into the reaction device to ensure the initial concentration of 20 mg N/L. While during the third stage, 20 mg N/L allylthiourea was added to inhibit nitrification, and sodium acetate at a dose of 250 mg COD/L was used for heterotrophic biomass respiration. The batch set-up was sealed at all stages to avoid interference from the outside air and the DO profiles were monitored. The DO profiles for the three stages of the test procedure are shown in Figure 2(b).

During the operating period, eight carriers were randomly selected from each reactor. Subsequently, biofilms were immediately scraped from the carriers and stored at −80 °C. Samples were named A1_1, A1_2, and A1_3 (A1_1, A1_2, and A1_3 represent the A1 reactor at T1, T2, and T3 respectively). Both microbial community genomic DNA extraction and DNA sequencing were performed according to the standard protocols by Majorbio Bio-Pharm Technology Co., Ltd (Shanghai, China) and the detailed steps were previously described (Zhang et al. 2020). The hypervariable region V3–V4 of bacterial 16S rRNA gene was amplified with the primer pairs 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′).

The correlation analysis in this study was performed on origin 2021 Pro using the Principal Component Analysis plug-in, and the experimental data were statistically analyzed and pre-processed using Microsoft Excel 2019.

The above analysis showed that the multi-stage A/O-MBBR system was favorable to the formation of different proportions of active biomass and different functional zones met the treatment needs of different pollutants. Furthermore, the proportion of autotrophic biomass in the MBBR system was much higher than that in the activated sludge system (Fernandes et al. 2014), which was more favorable to nitrification.

Temperature is one of the most important factors that determines the MBBR performance. While nitrification is particularly sensitive to temperature and stops below 8 °C (Hurse & Connor 1999), MBBR's unique structure can reduce the wear of biofilm and outperforms other biological treatment technologies even in harsh low-temperature environments (Young et al. 2017a).

Figure 3(b) illustrates the active biomass variation in each reactor at different temperatures for a multi-stage A/O-MBBR. Overall, it can be seen that the effect of temperature on the active biomass was still relatively large. With the decrease in temperature, the total active biomass showed an upward trend. In particular, a larger increase in total active biomass can be seen when the temperature was reduced from T1 to T2, with an increase of approximately 25–87%. In contrast, the maximum increase in total active biomass was only 24% when the temperature was reduced from T2 to T3; thus indicating that low temperatures limited biomass growth. Interestingly, the total active biomass of each reactor in the first A/O-MBBR subsystem decreased during this process, while MLSS (Supplementary material, Table A1) did not; this indicated that the proportion of active material within the biofilm decreased with lower temperatures, whereas the second A/O-MBBR subsystem was relatively unaffected. The decrease in total active biomass in the first A/O-MBBR subsystem during temperature change is mainly due to the drop in X_H. The maximum growth of X_H in the second A/O-MBBR subsystem was only 24%, a decrease of 62% compared to the maximum growth of X_H from T1 to T3. Furthermore, during the whole temperature change, the X_A in the aerobic reactor maintained a high growth rate, which was more obvious between T1 and T2, increasing by 51–184%, with an increase of about 8–79% from T2 to T3 and a slight decrease in the relative growth, which showed that further decreases in temperature lead X_A growth inhibition. Overall, the X_A growth is more tolerant of low temperatures than X_H and is closely linked to changes in water conditions.

The variation in the respective ratios of X_A and X_H in each reactor at different temperatures for the multi-stage A/O-MBBR is shown in Figure 3(b). Firstly, the X_H ratios in each reactor decreased with dropping temperature, while the corresponding X_A proportion increased. This indicates that the competitive advantage of autotrophic biomass growth was enhanced at low temperatures. Furthermore, we demonstrated that the growth of autotrophic biomass was more tolerant to low temperatures compared to heterotrophic biomass. The most significant increase in ratios of O3-MBBR and O7-MBBR in the aerobic reactor during the temperature decrease (T1 to T3) was from 10 to 24% and from 9 to 28%, respectively, which was equivalent to the decrease in heterotrophic biomass growth within the reactor. However, the increase in X_A ratios was 5 and 4% for O4-MBBR and O10-MBBR, respectively, with a decrease for the O8-MBBR, which may be related to the greater increase in active heterotrophic biomass. Due to the DO from reflux, the X_A ratios in A1-MBBR and A5-MBBR increased by 16 and 11%, respectively, with the nitrate recycling ratio in the first A/O-MBBR subsystem being higher than that in the second A/O-MBBR subsystem. Overall, the active biomass ratio characteristics indicate that autotrophic biomass had a greater growth advantage at low temperature.

The SOUR_E of aerobic reactors is generally higher than that of anoxic reactors (Figure 4(b)), which is in part related to their own large active biomass base. Furthermore, the aerobic reactor SOUR_E exhibited the same response following variation in temperature as the anoxic reactor, suggesting that the low temperature is more favorable to biomass cell accumulation, which to a certain extent compensates for the reduced rate of degradation of organic matter by individual cells (Young et al. 2017a). The SOUR_E of O3, O4, O7, and O8 had a maximum value of about 0.07 at T1, with approximately 0.02–0.04 at T3. Furthermore, the SOUR_E of O4 and O8 was less sensitive to the temperature drop than O3-MBBR and O7-MBBR. The SOUR_E of O10-MBBR was less affected by temperature and was always low (approximately 0.02 ⁠. It is worth considering that A9-MBBR and O10-MBBR, as the third stage of the A/O-MBBR, both had a lower SOUR_E than their counterparts, and the biomass on the biofilm was much less impacted by the substrate load, as the stable material conditions might have promoted microbial growth. The SOUR_E can be used as a parameter to determine the state of microbial cell death or the state of cell accumulation, thus reflecting the system section operational efficacy.

The autotrophic SOUR (SOUR_A) can indirectly represent nitrification activity. The SOUR_A declined with decreasing temperature (Figure 4(c)), indicating that low temperatures hindered the nitrification activity of autotrophic biomass. The SOUR_A of O4-MBBR, O8-MBBR, and O10-MBBR was significantly higher than that of O-MBBR 3 and O7-MBBR, indicating a relatively good nitrification performance, consistent with their higher X_A. Furthermore, SOUR_A was significantly influenced by temperature, with SOUR_A values for O4-MBBR, O7-MBBR, O8-MBBR, and O10-MBBR varying from 0.1313 to 0.0853, 0.1163 to 0.0748, 0.1817 to 0.1161, and 0.1765 to 0.1083 ⁠, respectively (Supplementary material, Table A2), as the temperature decreased from T1 to T3, producing a decrease of 35, 36, 36, and 39%, respectively. Additionally, the SOUR_A of O3-MBBR indicates a low nitrification activity, fluctuating around 0.050 ⁠. Although the total active biomass of the O3-MBBR was consistently high, it was limited by the large proportion of X_H, which led to intense competition between biomass and thus decreased the nitrification activity.

Biological nitrogen removal is carried out through denitrification, which can be divided into autotrophic and heterotrophic denitrification, depending on the carbon source required for biological growth (Karanasios et al. 2010). Of these, heterotrophic denitrification has been shown to be the most common and cost-effective process (Wang & Chu 2016). The amount and activity of heterotrophic biomass together determine the effectiveness of biological heterotrophic denitrification. The heterotrophic SOUR (SOUR_H) can indirectly represent the denitrification activity per unit mass of biofilm. Temperature had the same effect on SOUR_H as it did on SOUR_A (Figure 4(d)); this suggested that low temperatures have a negative effect on both the nitrification and denitrification activity per unit mass of biofilm. For the five anoxic reactors, SOUR_H was A9 > A6 > A2 > A5 > A1. The substrate of A9-MBBR's microbial contact was superior to that of other anoxic reactors, thus allowing its unit mass biofilm to have a higher active biomass and activity per mass of biofilm and better denitrification, which corresponded to its analytical results for X_H. The SOUR_H values for A1-MBBR, A2-MBBR, A5-MBBR, A6-MBBR, and A9-MBBR varied from 0.0375 to 0.0274, 0.1439 to 0.111, 0.0535 to 0.0403, 0.1879 to 0.1484, and 0.2395 to 0.1745 (Supplementary material, Table A2) as the temperature decreased from T1 to T3, producing a decrease of 27, 23, 25, 21, and 27%, respectively, which was 10% lower than the decline efficiency of SOUR_A. This suggests that the nitrification effect was more heavily influenced by low temperatures than the denitrification (the above is only for a unit mass of biofilm). This it also related to the proportion of active biomass type contained per unit mass of biofilm. The result was in contrast to the positive effect of low temperatures on active biomass growth. Although the increase in active biomass per unit mass of biofilm cannot counteract the effect of low temperature on its activity, the SOUR_H of A6-MBBR was greater at T1 than at T2, which could be due to the large increase in the amount of active heterotrophic biomass during the process (Figure 3(a)), thus offsetting the effect of the weakened activity. The SOUR_H of A1-MBBR and A5-MBBR was significantly lower than in other anoxic reactors. The high redox potential of the nitrifying liquid was generated by the high amount of DO carried by the nitrate recycling, which allowed heterotrophic biomass to use DO for respiratory metabolism and inhibit enzyme activity. Consequently, the anaerobic/anoxic biomass activity was inhibited and can lead to ineffective denitrification (Li et al. 2021; Fu et al. 2022), which is corroborated by the high proportion of X_A observed.

The yield coefficient of Y_H is an important parameter in the field of wastewater degradation kinetics and in determining the degradation kinetics of specific chemical substances (Strotmann et al. 1999). Supplementary material, Table A3 indicates the Y_H values for each reactor at T3. The higher active heterotrophic biomass at low temperatures were further supported by the fact that more than 80% of the organic matter in the aerobic reactor was used for the growth of heterotrophic biomass during winter low-temperature conditions. As a consequence of nitrate recycling, the A1-MBBR and A5-MBBR were not anoxic in the traditional sense, with approximately 83% of the organic matter playing a role in the material metabolic processes of the heterotrophic biomass. Such high Y_H values were also related to the substrate overdose during the test. Under normal conditions, the biomass in the aerobic reactor was always at low substrate concentrations, and A1-MBBR as well as A2-MBBR were not inlet points with low levels of substrate. Faced with a sudden abundance of organic matter, a large amount was rapidly consumed by heterotrophic biomass for material metabolism, resulting in generally high Y_H values. For the A2-MBBR, A6-MBBR, and A9-MBBR denitrification reactors, which were strictly dominated by heterotrophic biomass, the Y_H values were 0.6068, 0.6231, and 0.6876, respectively, at T3. The Y_H values for A9-MBBR were higher than those for the other two reactors, indicating that the easily biodegradable organic matter was more readily available to the biomass.

Further, the functional genus of aerobic reactors was analyzed and discussed (Figure 6(b)). Nitrosomonas was the dominant AOB genus and Nitrospira, Nitrolancea, and Candidatus_Nitrotoga were the dominant NOB genera in the aerobic reactor. Nitrospira and Nitrosomonas were the main AOB and NOB identified in wastewater treatment plants. Nitrospira abundance reached 7% (T1) in the O10-MBBR. The abundance of Nitrosomonas with autotrophic ammonia oxidation capacity was significantly higher at T3 than at T1. Candidatus_Nitrotoga, a cold-tolerant genus of nitrifying bacteria, showed optimum growth at T3 and was detected in each reactor at T3, and the abundance in both O4-MBBR and O8-MBBR was about 1%, making it the dominant nitrifying genus after Nitrospira in the aerobic reactor.

For anoxic reactors, Denitratisoma, Flavobacterium, Simplicispira, Thiothrix, and Hydrogenophaga were the main functional genera of denitrifying bacteria. Overall, the abundance of denitrifying genera in the system increased significantly with decreasing temperature, with increased abundance in the post-anoxic reactors (A2 and A6) compared to that in the pre-anoxic reactors (A1 and A5). These findings are consistent with the X_H data and the respiration rate tests, indicating that they were closely related to each other. Conversely, Thauera, Rhodobacter, Acinetobacter, Flavobacterium, Thiothrix, Lautropia, and Acidovorax were more abundant in the post-anoxic denitrification reactors, which was different from Zhou et al. (2022), who reported that Rhodobacter, Acinetobacter, and Acidovorax were significantly more abundant in the pre-anoxic reactors. This disparity may be related to the inlet point of the system. Thauera and Flavobacterium were reported to have the ability of aerobic denitrification and heterotrophic nitrification (Hong et al. 2020), with little difference in abundance among reactors. In our study, the abundance of Azospira and Thauera declined with decreasing temperature. For instance, the relative abundance of Azospira and Thauera decreased from 4 to 1% and 1 to 0.3% in A6-MBBR, respectively, when the temperature dropped from T1 to T3. Dechloromonas has been shown to play an important role in simultaneous nitrification denitrification (SND) (Fan et al. 2022), with its levels increasing with decreasing temperature (T3: 0.6% (A2), 0.8% (A6), 4% (A9)), indicating that SND was more likely to occur under low temperature. Furthermore, the Dechloromonas were much higher in A9-MBBR than other anoxic reactors, echoing a previous report (Jia et al. 2020) indicating that its levels decreased under inadequate carbon sources. Additionally, a higher abundance of Nitrospira was observed in the A1-MBBR and A5-MBBR (A1: 1–3%; A5: 1–3%), which corresponded to the more X_A in them. Nitrospira was also discovered in A2, A6, and A9 (T1), while being almost absent from A2 and A6 (T2 and T3). This might be explained by the fact that saturated DO was elevated at low temperatures, which was more conducive to the growth of heterotrophic biomass.

Nitrospira in the aerobic reactor showed a significant positive correlation with SOUR_A at all temperatures, with a maximum positive correlation coefficient of 0.8216(p < 0.01). The correlation coefficient between Nitrosomonas and SOUR_A declined with decreasing temperature (ρ = 0.8884 (T1); ρ = 0.4542 (T2); ρ = −0.1982 (T3)) (p < 0.05). Alternatively, there was a negative correlation between Nitrolancea and SOUR_A, with a maximum negative correlation coefficient of −0.972; however, the correlation fluctuated considerably due to low temperatures. Candidatus_Nitrotoga showed a weaker correlation with SOUR_A, probably related to the genus occurring only at low temperatures and being less representative in terms of reactive nitrification performance. Among the dominant genus, JG30-KF-CM45, Rhizobiales_Incertae_Sedis, and Romboutsia had a significant positive correlation with SOUR_A (p < 0.001), with correlation coefficients above 0.5. Gemmatimonadaceae had a significant negative correlation with SOUR_A (ρ = −0.6776– − 0.9893) (p < 0.001), and the correlation was further strengthened with decreasing temperature. Except for Dokdonella (p < 0.01) and Trichococcus (p < 0.001), which showed significant positive correlations with X_A (ρ > 0.7), the correlations between other genera and X_A were weak, while most genera in aerobic and anoxic reactors showed significant correlations with X_H, which may have a certain relationship with the base of the active biomass type. Additionally, the correlation between the genus and X_H as well as SOUR_E showed a strong consistency in the aerobic reactor, indicating that the biomass decay in the system was mainly dominated by heterotrophic biomass.

Except Hyphomicrobium and Thiobacillus, all other denitrifying genera showed a positive relationship with SOUR_H and X_H, and a negative relationship with X_A in anoxic reactors. Thiothrix and Hydrogenophaga showed enhanced positive correlations with SOUR_H with decreasing temperature (ρ = 0.51 and 0.63 (T1); ρ = 0.99 and 1.00 (T2); ρ = 0.98 and 0.97 (T3), respectively) (p < 0.05). The SND-related Dechloromonas showed a positive correlation with X_H (p < 0.01) and SOUR_H (p < 0.05) and a negative correlation with X_A (p < 0.05) (T1). Its correlation with active biomass weakened with decreasing temperature, while its correlation with the respiration rate was slightly increased. Flavobacterium (aerobic denitrification capacity) showed a significant positive correlation with X_H (ρ > 0.97) (p < 0.01) and SOUR_H (p < 0.05). The correlation between Thauera and X_H was more significant (ρ = 0.83–0.86) (p < 0.05). As a typical genus of endogenous denitrifying bacteria using an internal carbon source (Salehi et al. 2019), Dechloromonas showed a negative correlation with SOUR_E (ρ = 0.48–0.67), while Defluviicoccus showed a significant positive correlation with SOUR_E (ρ = 0.48–0.98) (p < 0.001), with more significant correlations at low temperatures. Finally, the most dominant genera in the anoxic reactor showed significant correlations with X_A, X_H, and SOUR_H, and were less influenced by overall temperature.

In summary, the correlation between the observed microbial community, the active biomass, and the specific respiration rate reflects the reliability of the respirometric method for characterizing the microbial performance of the multi-stage A/O-MBBR. As the first study to propose a correlation between microbial community, active biomass, and respiration rate, the method is yet to be validated by similar studies.

In this study, the active biomass distribution, Y_H of a multi-stage MBBR with nitrogen removal were measured in different conditions. The correlation between SOUR and nitrification as well as denitrification activity was also investigated. The following conclusions were drawn:

• The total active biomass in the multi-stage A/O-MBBR system was 0.71–1.68 g COD/m² for the aerobic reactor and 0.39–1.44 g COD/m² for the anoxic reactor.

• The increased active biomass at low temperatures can to some extent compensate for the reduced biofilm activity per unit mass.

• The Y_H values for the aerobic reactors were 0.82–0.89 at 10–13 °C, which were significantly higher than the recommended value of the activated sludge model (Y_H = 0.67). However, the anoxic reactors had Y_H value of 0.61–0.69, which were comparable to Y_H = 0.67.

• The correlation coefficient between Nitrospira and SOUR_A was 0.82. Thiothrix, Hydrogenophaga, Dechloromonas, Flavobacterium and other denitrifying genera showed significant correlation with SOUR_H and X_H.

The results of the correlation analysis between the community and SOUR also concluded that the respiration tests applied in this study can function as a simple-to-apply and reliable method for nitrification and denitrification trouble shooting at WWTPs.

This work was funded by the National Natural Science Foundation of China (grant number: 51908303) and the Research Council of Norway (grant number: 310074/G10).

N.C. investigated the study, did data curation, wrote the original draft, did formal analysis and prepared the methodology. X.W. conceptualized the study, investigated and prepared the methodology, wrote the draft and acquired funds. M.H. investigated the study and did data curation. Z.M. wrote the original draft, revised, and editing the article. H.R. validated the study. X.B. investigated and supervised the study.

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

The authors declare there is no conflict.