This study focused on using pH as a single indicator to evaluate/control the performance of the nitritation system under the influence of three major operational parameters, and a total of fifteen batch tests were conducted. Results indicated that there were important interactions among different operational parameters and pH in the nitritation system; it was possible to propose the optimal nitritation operation scheme to compensate for negative changes in operational parameters. The optimal carbon to nitrogen (C/N) ratio was kept at 2.0 to ensure efficient removal of ammonium. The reaction time was the lowest (150 min) with the temperature = 20 °C, C/N = 0, and sludge/water ratio = 1:1. However, the C/N ratio could be adjusted to close to zero by reducing the temperature to about 10 °C, weakening the heterotrophic bacteria, and supplying sufficient biomass. The C/N ratio and sludge/water ratio could also be set at 4.0 and 1:3 respectively to deal with the impact of low temperature and organic matter. Results of this study might be useful to explain the optimal conditions and process control schemes with pH as a single indicator.

  • The pH as a single representative factor could be affected by temperature, C/N ratio and sludge concentration, respectively.

  • The optimal control conditions were explained among adjustment of different environmental parameters of a partial nitritation (PN) system.

  • Using sufficient substrate and appropriate amount of sludge could be conducive to dealing with the impact of low temperature and organic matter.

Nitritation is the oxidation of ammonium (NH4+-N) to nitrite (NO2-N) only; that is, NH4+ + 1.5O2 → NO2 + 2H+ without the continual oxidation to nitrate (NO3-N). Compared with traditional nitrification, nitritation is reported to be capable of saving approximately 25% of oxygen demand and reducing 30% of reaction time, respectively (Ruiz et al. 2003). It is a prerequisite reaction for the nitritation-denitritation process, but it can also be coupled with anaerobic ammonia oxidation (anammox) to form an efficient nitrogen removal system. Currently, more than one hundred combined nitritation-anammox systems are being operated in the world (Lackner et al. 2015a; Adams et al. 2020). As a fast process, the real-time control of nitritation could be performed by using the change curve between reaction time and parameters such as pH, dissolved oxygen (DO), and oxidation-reduction potential (ORP). For example, the pH control strategy has been widely studied to start up nitritation in different circumstances (Gu et al. 2012), to explain the effect on simultaneous nitritation (He et al. 2012) or to monitor/control the formation of autotrophic nitritation granules (Rathnayake et al. 2015). In addition, the pH control strategy had been carried out with respect to N2O production under aerobic conditions in the nitritation system (Law et al. 2011) or other biochemical reactions by changing the activities of functional bacteria (van Hulle et al. 2007; Ahn et al. 2008; Okabe et al. 2011; Rathnayake et al. 2015; Soliman & Eldyasti 2016).

Considerable research has been devoted to realizing or controlling the nitritation process and improving nitrogen removal efficiency. pH is one of the main driving factors that determine the dominant ammonia-oxidizing bacteria (AOB) species in a nitritation bioreactor (Kinh et al. 2017). Most of the literature about bioreactors suggests that pH in a range of 7.5 − 8.5 is most suitable to inhibit nitrite-oxidizing bacteria (NOB) (He et al. 2012). Furthermore, pH of 8.0 had been proved to be the optimal value for nitrite accumulation in batch reactors (Bae et al. 2001). The pH control has been reported as a constructive strategy for the nitritation process (Magrí et al. 2007).

In spite of these aforementioned studies, sufficient information is not available on the relationships between pH change, the evolution of ammonium concentration and nitritation reaction as well as some key process parameters (e.g. temperature, organic matter and biomass concentrations). Our preliminary studies analyzed the pH change during the nitritation process, including ΔpH, time to pH peak [t(max)], and pH valley (see Figure 1 for their definitions). It was found that the trend of ammonium in the system (including its lowest point) and the end point of the nitritation reaction under the influence of different sludge concentrations and carbon to nitrogen (C/N) ratios were closely related to the pH change. The whole reaction process in the system could be divided into Phase I and Phase II by the characteristic of pH during the reaction (Figure 1). Phase I is the active phase of heterotrophic bacteria (HeB), which consume a large amount of organic matter to provide substrate for the nitritation reaction. In this process of catabolism and anabolism, the produced CO2 could raise the pH to its peak. In Phase II, however, pH is reduced as H+ is released due to the simultaneous nitritation reaction in the system. pH could not only regulate the chemical oxygen demand (COD) removal, but also indicate the end of the nitritation and denitritation (NO3 → NO2) reaction. Therefore, determining ΔpH, t(max), and pH valley are the key points for this regulation and/or indication.

Figure 1

Definitions of related terms. ΔpH = the difference between the initial and peak pH; t(max) = the time needed to reach peak pH; and pH valley = the pH associated with the ‘lowest ammonia concentration’ within the system. Phase I = testing period between the initial and peak pH; and Phase II = testing period between the peak and valley pH.

Figure 1

Definitions of related terms. ΔpH = the difference between the initial and peak pH; t(max) = the time needed to reach peak pH; and pH valley = the pH associated with the ‘lowest ammonia concentration’ within the system. Phase I = testing period between the initial and peak pH; and Phase II = testing period between the peak and valley pH.

The closer the temperature was to the optimal range of AOB, the higher the activity of AOB in the system and the better degradation of ammonium and the production of nitrite achieved. It was noticed that the temperature of 30 °C was suitable for microbial growth, and the pH of the reaction was positively correlated with the C/N ratio. The positive correlation was also not reversed at this temperature when the sludge concentration of the system was changed. Low temperature was one of the main challenges for applying nitritation-anammox to treat real wastewater. A study used pyrosequencing to analyze the granular sludge community/structure, and found that some psychrotolerant microorganisms produced cryoprotective extracellular polymeric substances, which could explain the better survival of the whole consortia at cold temperatures (Reino et al. 2016). However, the AOB could remove more than 90% of the incoming nitrogen at 12 °C (Hu et al. 2013). The nitritation process kept stable with an average nitrite accumulation efficiency above 95% at temperatures ranging from 11.9 to 26.5 °C (Yang et al. 2007).

Controlling the organic matter of the influent is also an important step in the nitritation and anammox system. With more organic matter, the HeB in the reactor could grow fast and compete for nitrite and living space with anammox and for DO with AOB (Chamchoi et al. 2008; Molinuevo et al. 2009; Jenni et al. 2014). The HeB's overgrowth would shift the process from nitritation/anammox to traditional nitritation/denitritation. Moreover, the sludge concentration is a core factor that affects pH, nitritation efficiency and effluent quality, and keeping the sludge concentration within the optimal level is important for the system to be stable.

In light of the above analyses, it is imperative to understand how to use pH as a single indicator to evaluate/control the performance of a nitritation system under the influence of different operational parameters. The objectives of this study were to use pH as a single indicator to: (1) determine the optimal conditions for nitritation under the influences of different temperatures, C/N ratios and sludge concentrations; (2) analyze the nitrogen and carbon removal efficiency of the nitritation system; and (3) evaluate the relationship among different operational parameters and the nitritation efficiency. It was anticipated that results of this study might be useful to explain the optimal conditions and process control schemes with pH as a single indicator/factor.

Experimental setup and operation mode

The nitritation sludge activity was tested by batch experiments with a 250-ml conical flask (Shuniu, Shubo Co., Ltd, Sichuan, China) as the batch reactor. The granular sludge used in the experiment was sampled from the nitrosated sludge in a sequencing batch reactor (SBR, as a nitritation reactor) The nitrosated sludge was washed 3 times with distilled water and soaked in distilled water for 24 h before use. The ammonium concentration in the batch reactor was always kept constant at 150 mg L−1. The main environmental factors in this research were: temperature (30 °C, 20 °C, 10 °C), C/N ratio (0, 1, 2, 3, 4), sludge concentration [sludge/water (v/v) = 1:6, 1:3, 1:1], respectively. To control the C/N ratio, solutions with different ratios of NH3Cl and CH3COONa were added to the batch reactor. To control the sludge/water ratio, the prewashed sludge with a concentration of total suspended solids (TSS) of 1,900, 3,100 and 4,000 mg L−1 respectively was added into the batch reactor, followed by adding the desired amount of the solutions (215, 185, 125 mL) to make the sludge/water ratios of 1:6, 1:3 and 1:1. The initial pH of the batch reactor was adjusted to 7.7 using NaHCO3. Table 1 summarizes the designed test conditions in this study.

Table 1

Experimental scheme

Test #Test conditions*
C/N = 0, COD = 0 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 30 °C 
C/N = 1, COD = 150 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 30 °C 
C/N = 2, COD = 300 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 30 °C 
C/N = 3, COD = 450 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 30 °C 
C/N = 4, COD = 600 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 30 °C 
C/N = 0, COD = 0 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 20 °C 
C/N = 1, COD = 150 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 20 °C 
C/N = 2, COD = 300 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 20 °C 
C/N = 3, COD = 450 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 20 °C 
10 C/N = 4, COD = 600 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 20 °C 
11 C/N = 0, COD = 0 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 10 °C 
12 C/N = 1, COD = 150 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 10 °C 
13 C/N = 2, COD = 300 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 10 °C 
14 C/N = 3, COD = 450 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 10 °C 
15 C/N = 4, COD = 600 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 10 °C 
Test #Test conditions*
C/N = 0, COD = 0 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 30 °C 
C/N = 1, COD = 150 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 30 °C 
C/N = 2, COD = 300 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 30 °C 
C/N = 3, COD = 450 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 30 °C 
C/N = 4, COD = 600 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 30 °C 
C/N = 0, COD = 0 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 20 °C 
C/N = 1, COD = 150 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 20 °C 
C/N = 2, COD = 300 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 20 °C 
C/N = 3, COD = 450 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 20 °C 
10 C/N = 4, COD = 600 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 20 °C 
11 C/N = 0, COD = 0 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 10 °C 
12 C/N = 1, COD = 150 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 10 °C 
13 C/N = 2, COD = 300 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 10 °C 
14 C/N = 3, COD = 450 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 10 °C 
15 C/N = 4, COD = 600 mg L−1, sludge/water = 1:6, 1:3 & 1:1, 10 °C 

*Each test was conducted in triplicated batch reactors, and each time two parallel samples were taken from each reactor (n = 6 in total).

To conduct the batch tests, the batch reactors were fixed in a shaker (LSHW-500D, Yataikelong Co., Ltd, Beijing, China) with a temperature control chamber, and the solution was uniformly mixed by controlling the shaker at a speed of 170 rpm/min. The DO concentration was set to a low value of about 0.5 mg L−1. To find the values corresponding to the starting, turning and ending points (as shown in Figure 1), samples (about 10 ml each) were taken from the batch reactor every 10 (or 20, 30, 50, 70, 90…) min and were used to monitor the changes of COD, ammonium, nitrite, nitrate and pH in each batch reactor until the minimum ammonium concentration was identified (then the test was terminated). In all tests, the remaining mixed liquid volumes were more than 50 mL after sampling of the batch experiment.

Analytical method and calculations

All the samples were analyzed for COD, mixed liquor suspended solids (MLSS), ammonium, nitrate, and nitrite according to the standard methods (APHA et al. 2012). The pH value was detected by pH meter (HQ40D, HACH). The specific ammonia oxidation rate (SAOR, mgN mgMLSS−1 d−1), specific COD removal rate (mgCOD mgMLSS−1 d−1), nitritation accumulation rate (NAR, %), and sludge volume index (SVI, mL g−1) were calculated according to the following formulae:
formula
(1)
where C[NH4+-N]0 is the initial concentration of ammonium (mg L−1); C[NH4+-N]t is the concentration of ammonium at time t (mg L−1); MLSS is the sludge concentration (mg L−1); is the time of reaction (d).
formula
(2)
where C(COD)0 is the initial concentration of COD (mg L−1); C(COD)t is the concentration of COD at time t (mg L−1); MLSS is the sludge concentration (mg L−1); t is the time of reaction (d).
formula
(3)
where NO2-N is the concentration of nitrite-nitrogen at the end of reaction (mg NO2-N L−1); NO3-N is the nitrate-nitrogen concentration at the end of reaction (mg NO3-N L−1).
formula
(4)
where SV% is the volume of sludge after sedimentation for 30 min/the volume of sludge-water (mL L−1); MLSS is the dry sludge weight (g L−1).
formula
(5)
where n(ΔpH change) is the value of ΔpH change (increase or decrease) with a single environment factor; n(Total) is the number of total ΔpH change value.
formula
(6)
where n(t(max)) is the value of t(max) change (increase or decrease) with a single environment factor; n(Total) is total t(max) change value.

Statistical methods

The relationship between minimum pH and environmental factors was analyzed by the correlation analysis with SPSS v.22.0.

The special value of pH under influence of different parameters

When the sludge/water was adjusted from 1:6 to 1:3, the ΔpH increased by 58.3%, and t(max) decreased by 75%. However, no significant increase in ΔpH was observed when the sludge/water ratio was changed from 1:1 to 1:3. Due to the selective utilization of carbon sources by microorganisms, the variations of carbon source in the influent significantly affect the pH tendency (Wu et al. 2016). The HeB could not perform the reaction of releasing CO2 without an external carbon source, leaving the pH unchanged instead of reaching the pH peak. The ΔpH was increased in all the testing reactors when the C/N was increased from 1 to 2. However, increasing the C/N from 2 to 4 resulted in an increase of 88.9% of ΔpH. In addition, the probability of increasing t(max) by elevated C/N from 1 to 2, 2 to 3, and 3 to 4 was 100%, 100% and 88.9%, respectively. It was thus confirmed that the C/N in the influent was closely related to the pH change in Phase I, where carbon removal was performed. Therefore, the C/N significantly affected the COD removal efficiency.

Correlation Analysis (CA) was used to explore the relationship between different environmental factors and pH valley, as shown in Table 2. The correlation coefficients of sludge concentration, C/N, temperature and pH were all greater than 0.5, indicating that these three environmental factors have a significant impact on the pH valley. Such a relationship was confirmed by the results shown in Figure 2. Figure 2(a) shows the pH valley was positively correlated with C/N at different sludge/water ratios at 30 °C. When C/N increased from 2 to 3, the correlation coefficient was highest, at 0.823, between pH minimum and the C/N value (Table 2). In Figure 2(b), three curves show an increase in pH valley with an increase in sludge/water ratio. The curve of pH valley was increased first and then decreased at C/N = 1, while at C/N = 0, it was decreased first and then increased slightly. For the sludge/water ratio = 1:3, the pH valley increased almost linearly. However, the relationship between pH and sludge concentration was not clear and needs further study. Figure 2(c) shows that temperature increase significantly affected the pH valley. The correlation coefficient was 0.410 for temperatures between 10 °C and 20 °C, and 0.731 between 20 °C and 30 °C (Table 2(c)). In addition, an increasing temperature caused a significant drop in pH valley (Figure 2).

Table 2

Correlation analysis between pH minimum and environmental factors (* indicates p < 0.05, ** indicates p < 0.005)

 
 
Figure 2

Trend of pH valley (the pH associated with the ‘lowest ammonia concentration’ within the reactor) with respect to different environmental parameters. Test temperature = 30 °C for panels (a) and (b); and the sludge/water ratio = 1:3 for panel (c).

Figure 2

Trend of pH valley (the pH associated with the ‘lowest ammonia concentration’ within the reactor) with respect to different environmental parameters. Test temperature = 30 °C for panels (a) and (b); and the sludge/water ratio = 1:3 for panel (c).

Water quality under influence of different parameters

As shown in Figure 3, pH had a direct downward trend at C/N = 0; thus, the system involved Phase II only. However, for systems with C/N ratios of 1 to 4, the pH increased first, followed by a decrease; thus, the systems had both Phase I and II. Figure 3 shows that COD declined rapidly in Phase I and slowed down in Phase II under different conditions. The correlations between the pH and ammonium concentration as a function of time, which also indicated how to find the pH valley associated with the lowest ammonia concentration (= ‘ammonia valley point’). Figure 3 also shows that the system with the highest sludge concentration (=1:1 sludge/water ratio) always had the lowest pH minimum, which was further confirmed by the change in the correlation value from 0.950 (p = 0) to 0.685 (p = 0.005) in (Table 2(a)). Again, results shown in Figure 3 probably demonstrate the feasibility of using pH as a single indicator to monitor a nitritation system.

Figure 3

Changes of pH, ammonium concentration and COD as a function of different sludge/water ratios at different C/N ratios at 10 °C. Inserts are time course of COD in the testing reactors under different conditions.

Figure 3

Changes of pH, ammonium concentration and COD as a function of different sludge/water ratios at different C/N ratios at 10 °C. Inserts are time course of COD in the testing reactors under different conditions.

When other variables were controlled as the same, the more ammonium was removed, and the shorter the residence time required when the sludge concentration was higher under normal conditions. Figure 4 shows that sludge/water ratios at 1:3 and 1:1 have a much higher ammonium removal than that of 1:6, and the nitrite concentration had a sudden drop at sludge/water ratio of 1:1 at 300 min, while the ammonium concentration had a small fluctuation between 260 and 290 min with the nitrate concentration being stable. For C/N = 4, during the reaction period of 200 − 300 min, the COD concentration at sludge/water = 1:3 was higher than that at sludge/water = 1:1.

Figure 4

Changes of nitrite and nitrate nitrogen concentration as a function of different sludge/water ratios at different C/N ratios at 10 °C.

Figure 4

Changes of nitrite and nitrate nitrogen concentration as a function of different sludge/water ratios at different C/N ratios at 10 °C.

Figure 4 shows that reaction in the system could be divided into a gentle phase (Phase I) and a rapid phase (Phase II), which is consistent with Figure 1. Phase II is associated with the nitritation reaction, which, in general, is relatively fast for most of the time but becomes gentle toward the end of the reaction. The nitrite accumulation efficiency increased with an increase in sludge concentration: the higher the sludge concentration, the shorter the time in which the system reached the nitritation end point. Adding a certain amount of organic matter to the nitritation system could contribute to the nitrite accumulation. The nitritation-anammox process was reported not to be obstructed with a ratio COD/N in the influent between 0.18 and 1.14 g g−1 (Pichel et al. 2019). However, a pilot-scale study illustrated that application of the proposed online aeration control was helpful to washout NOB without carbon, while keeping relatively high nitrogen removal (Regmi et al. 2014). The observation in this particular study was a bit different. Even if the influent COD = 600 mg L−1, C/N = 6, temperature = 10 °C, sludge concentration = only 1,900 mg L−1, the final ammonium and nitrite concentration still reached 44.44 mg L−1 and 60.02 mg L−1 in the reaction system, respectively. Only changing a single environmental condition (non-exposure, etc.) was not sufficient to completely replace the dominant population in the system in a short period of time, although the ecological structure of the environment was changed (Hirahara et al. 2003; Cai et al. 2020).

The nitrite accumulation at 30 °C and 20 °C was similar to that at 10 °C, but the difference in nitrite concentration between different sludge concentrations was smaller than that at 10 °C. The nitrite accumulation rate had obvious regularity with the reaction time, implying the system was in stable operation. When the temperature was higher than 15 °C, the growth rate of AOB was greater than NOB. When the temperature was higher than 25 °C, this advantage would be further enhanced (Paredes et al. 2007).

Figure 5(a) shows that the ammonium concentration in the effluent at 20 °C was lower than that at 10 or 30 °C; an increase in sludge/water enhanced the ammonium degradation; an increase in C/N also reduced the ammonium concentration in the effluent, but the reaction time would be prolonged at the same time. As an interesting incident, Figure 5(b) shows that, as the temperature was raised to 30 °C, the activity of the nitritation bacteria in the system might have been enhanced as the reaction efficiency was increased together with a reduced reaction time. In this case, the residence time of the HeB in contact with the organic matter was reduced, which would reduce the COD removal efficiency. Under the same sludge concentration condition, the total reaction time only fluctuated slightly at different C/N ratios when the temperature was higher than 20 °C but changed significantly at 10 °C, indicating that a suitable temperature could be critical to the stability of the nitritation system. These results suggest that it is possible to obtain a combination of operational conditions (e.g. sludge/water, C/N and temperature) to keep the system stable.

Figure 5

Effluent ammonium concentration and COD under the influence of different environmental parameters. The bubble color shows different classifications and the size represents the values of the ammonium concentration or COD. The full color version of this figure is available in the online version of this paper, at http://dx.doi.org/10.2166/wst.2020.371.

Figure 5

Effluent ammonium concentration and COD under the influence of different environmental parameters. The bubble color shows different classifications and the size represents the values of the ammonium concentration or COD. The full color version of this figure is available in the online version of this paper, at http://dx.doi.org/10.2166/wst.2020.371.

Figure 6 shows that the highest nitrite accumulation occurred at 20 °C, sludge/water = 1:6, and C/N = 4, and lowest at 10 °C, sludge/water = 1:1, and C/N = 1. In addition, nitrite accumulation could also reach higher levels by changing the environmental conditions at 10 °C (e.g. changing the C/N to 1:3), which indicates that it is possible to override the other factors by manipulating the C/N ratio to alleviate the fluctuation of effluent nitrite concentration. Moreover, maintaining a higher sludge/water ratio of the system would make a smaller difference in nitrite concentration in the effluent at different temperatures and C/N conditions.

Figure 6

Effluent nitrite nitrogen concentration under the influence of different environmental parameters.

Figure 6

Effluent nitrite nitrogen concentration under the influence of different environmental parameters.

The nitrate concentrations in each sludge system with different C/N temperatures were all lower than 10 mg L−1, and the NAR in the system was kept above 85%. In other words, the nitrite nitrogen in the system was well accumulated, presumably due to the low DO and the pH valley point. Therefore, when the pH valley was known in the stable nitritation reaction, using pH as a single indicator for real-time monitoring of the nitritation reaction process would be beneficial to the cultivation of mature nitritation sludge.

Nitrogen and carbon removal under influence of different parameters

In the nitritation system, there are intricate interactions among environmental factors and microorganisms. Since the reaction time of different tests was diverse under each condition, this study analyzed the SAOR and the specific COD removal rate by controlling a single variable to reflect the change in microbial activity in each of the batch reactors. Among them, SAOR was used to characterize the activity of AOB. The maximum SAOR of 0.25 mg mg−1 d−1 appeared at 20 °C, sludge/water = 1:6, C/N = 2 (Figure 7(b)), while the minimum SAOR of only 0.03 mg mg−1 d−1 appeared at 30 °C, sludge/water = 1:6, C/N = 1 (Figure 7(c)). These results are a bit different from the previous observations, which indicated that AOB with higher energy grew faster than NOB at 25 °C or higher (Hellinga et al. 1998).

Figure 7

The SAOR and specific COD removal efficiency under influence of different environmental parameters.

Figure 7

The SAOR and specific COD removal efficiency under influence of different environmental parameters.

Low temperature is one of the main challenges for applying nitritation-anammox to treat real wastewater. In order to compensate for the impact of temperature drop or sludge loss on the effluent quality, increasing the organic load rate in the system is generally adopted. At present, the anammox process with nitritation as the pre-reaction has been successfully applied to the treatment of high ammonium wastewater. Adding a certain amount of organic matter to the system could improve the activity of nitritation sludge and increase the removal rate of ammonium. This may result from the synergy and cooperation between HeB and other functional bacteria apart from competition (Chen et al. 2009). This control advantage was verified in this study. When the system temperature was 10 °C, C/N = 2 (COD = 300 mg L−1), the SAOR of the test with the lowest sludge concentration (sludge/water = 1:6) could reach 0.16 mg mg−1 d−1 (Figure 7(a)), which was lower than the other maximum sludge concentration without organic matter (sludge/water = 1:1 and C/N = 0) at the same temperature (Figure 7(a)). At 20 °C and C/N = 2, the system achieved 0.25 mg mg−1 d−1 of SAOR with the lowest sludge concentration (Figure 7(b)), which was the highest SAOR in all 15 tests. Since 30 °C was the optimum temperature for ammonium oxidation (Hellinga et al. 1998), the average SAOR of the tests at 30 °C was 0.11 mg mg−1 d−1. The higher SAOR could be reached when the higher organic concentration was carried at each sludge concentration level. A similar phenomenon also appeared in a previous study on anammox, where the presence of organic matter at low concentrations improved total nitrogen (TN) removal via heterotrophic denitritation, called a simultaneous nitritation, anammox and denitritation (SNAD) process (Lan et al. 2011). However, at the other two temperatures (10 and 20 °C), unlike the SAOR at 30 °C, the increase in C/N may reduce the SAOR. There were diverse threshold values at different temperatures, and when the C/N ratio of the influent was increased, the HeB had greater superiority in growth and competence for the matrix. In addition, increasing the influent organic matter would hinder the AOB activity in the one-stage nitritation/anammox process (Zhang et al. 2015).

In the sludge system, maintaining sufficient biomass was a core factor in ensuring the stability of the effluent. With an increase in C/N, the tests with a higher sludge concentration showed a greater SAOR and better sludge activity at the optimal temperature (30 °C). However, there are two reasons for the minimum SAOR at the optimum temperature. First, pH would affect the competition of AOB and NOB by controlling the concentration of free ammonia (FA) when pH was higher than 7.5 (Sinha & Annachhatre 2007). It was reported that the inhibitory concentration of FA on AOB and NOB was >10 mg L−1 (Hawkins et al. 2010) and <1 mg L−1 (Vadivelu et al. 2007). In this study, the FA was only 10.01 − 15.58 mg L−1 in Phase I. Thus, the inhibition of AOB by FA caused the SAOR of Phase I to be only 0.0059 mg mg−1 d−1. Second, the test with a condition of 30 °C, sludge/water = 1:6, and C/N = 1 needed a total residence time of 600 min. Small amounts of organic substrate added in the influent would positively affect the maximum nitrogen removal capacity because of heterotrophic denitritation of nitrate to nitrite (Mozumder et al. 2014). However, the amount of organic substrate in the influent should exceed a certain threshold; otherwise, the process would have limited nitritation. In Phase I, due to the low concentration of organic matter (150 mg L−1), heterotrophic filamentous bacteria with larger specific surface area were more advantageous than AOB in utilizing substrate. Thus, AOB could not recover even after long-term reaction of Phase I, resulting in SAOR of Phase II = 0.0987 mg mg−1 d−1. Therefore, controlling a reasonable influent matrix would be one important factor to improve the activity of nitritation sludge.

The organic carbon source was consumed by denitrifying bacteria. The HeB could reduce the COD in the system during the metabolic process, which resulted in a higher COD removal rate than SAOR from the entire reaction process. In the case of low temperature (10 °C), the sludge concentration was too high to adversely affect the COD removal (Figure 7(d)). Therefore, a certain amount of sludge should be discharged in practical applications with reduction in temperature. At temperatures of 10 °C and 20 °C, when C/N was 2, MLSS lower than 3,000 mg L−1 sludge was helpful to reach the highest COD removal rate. But the high organic loading (C/N = 4) in the sludge concentration would be disadvantageous to organic degradation. It was inferred from Figure 7(d)–7(f) that a small amount of organic carbon source (150 mg L−1) under non-ideal temperature and low oxygen conditions would cause insufficient COD removal, and such a problem did not occur at a suitable temperature of 30 °C. When temperature = 30 °C, sludge/water = 1:3, the special COD removal rate at C/N = 1 was higher than that at C/N = 4, C/N = 3 and C/N = 2 in turn. In this test, the maximum COD removal rate was 1.13 mg mg−1 d−1, which lay at 30 °C, C/N = 1, and sludge/water = 1:3. However, the COD removal rate was lowest at 20 °C, C/ N = 1, sludge/water = 1:1, and the value was only 0.12 mg mg−1 d−1. The proportion of functional microorganisms was different in the nitritation and denitritation coupling system, which resulted in a difference from the highest or lowest SAOR conditions. Besides the nitritation, it was necessary to judge the relationship between the synergy and competition of functional microorganisms to ensure the stability of the anammox system in practical applications (Li et al. 2018).

The reaction time under influence of different parameters

Figure 8 shows the total reaction time for different C/N ratios at different temperatures and sludge concentrations. The activity of microorganisms would be improved by increasing temperatures (10 to 30 °C); the time to reach the end point of nitritation would be reduced as well. In this study, the carbon and nitrogen removal and nitrite accumulation were maintained at 30 °C. The lowest reaction time at the same temperature (30 °C) was only 330 min, which was 23.49% less than the average reaction time (431 min over the three temperatures). The reduction of reaction time would play a role in saving manpower and material resources in practical applications. Of the 15 tests, the minimum reaction time was only 150 min, which occurred in the test at 20 °C, C/N = 0, and sludge/water = 1:1. At the end of the reaction, the ammonium removal efficiency reached 80%, and the NAR and COD removal efficiency were 91.85% and 89.51%. However, the NAR value was the highest (about 99.99%) at 30 °C, C/N = 4, sludge/water = 1:6, but the reaction time was 420 min. In addition, the COD removal performance was the best, and the ammonium removal efficiency was higher than 80%. The NAR was higher than 95% at 10 °C, C/N = 4, sludge/water = 1: 3, and 510 min of reaction time was needed. At low temperature (10 °C), the total reaction time was shortest, and the ammonium removal efficiency was greater than 80% at the fastest rate at C/N = 0 and sludge/water = 1:1. Under this condition, the NAR and final ammonium removal efficiency were 89.24% and 97.80%. The SBR showed a dramatic drop in activity at 10°C and did not return to normal even when the temperature was increased again under seasonal temperature fluctuations (Lackner et al. 2015b). Theoretically, a low temperature (10 − 15 °C) would have a negative impact on the growth of AOB and NOB, and the impact on AOB activity was greater than that on NOB (Yoo et al. 1999). Although the NOB abundance was up to 4% with the temperature decreased, AOB fractions were relatively constant over time, and the AOB activity did not even suffer any further losses between 20 and 10 °C (Gilbert et al. 2015). It is worth mentioning that the system still maintained a high NAR at the low temperature, presumably because (1) the early sludge activity recovery was good, (2) the competitive advantage of AOB was not lost even if a short temperature drop (maximum duration of 640 min) occurred. It means that instantaneous reaction changes in the conditions temporarily affect the system performance, but long-term reaction would change key functional microbial treatments (Li et al. 2018). In addition, it can be found that more time was needed to complete the reaction as the C/N increased, but the average ammonium removal efficiency also increased, and was 60.47%, 76.83%, 80.30%, 90.24% and 91.62%, respectively. The increase in substrate concentration enhanced the microbial oxidation of ammonia. The maximum average NAR was 97.63% at C/N = 2, when the minimum average NAR was at C/N = 1. The NAR at C/N = 3 or 4 was also lower than that at C/N = 2. The organic matter concentration addition caused the HeB to rapidly proliferate and wrap outside the nitrifying bacteria, or nitrite could be produced through HeB as an intermediate substance (Li et al. 2018). Most nitrogen was removed by the granules through the nitritation-anammox process, and the remaining nitrate was removed by the flocs through heterotrophic denitritation (Li et al. 2019).

Figure 8

Total reaction time under influence of different environmental parameters.

Figure 8

Total reaction time under influence of different environmental parameters.

Figure 9 shows the time distribution of 80% of ammonium removal under the influence of different parameters. The circle is divided into five sectors according to different C/N, where C/N = 0, 1, 2, 3 and 4 corresponds to the sections of 0° ≤ θ < 72°, 72° ≤ θ < 144°, 144° ≤ θ < 216°, 216° ≤ θ < 288° and 288° ≤ θ < 360°, respectively. Theoretically, there are nine points in one sector in Figure 9. From the C/N perspective, only two tests had an ammonium removal efficiency higher than 80% when C/N = 0. Other tests with a larger C/N had an ammonium removal efficiency higher than 80%. There were 8 points with ammonium removal efficiency higher than 80% in the sector of C/N = 4. Although AOB was autotrophic microorganisms, an appropriate amount of organic matter would stabilize and promote the effluent quality. Besides, a certain threshold organic substrate would contribute to a broader optimal oxygen range for easy control in practice (Mozumder et al. 2014).

Figure 9

Time distributions of more than 80% of ammonium removal under the influence of different environmental parameters.

Figure 9

Time distributions of more than 80% of ammonium removal under the influence of different environmental parameters.

From the temperature point of view, three types of shaded area of points symbolized three temperature conditions, and there were 15 points at each temperature. When the temperature was 10 °C, there were five points (15 points in total) with a reaction time of about 400–550 min. The efficiency for ammonia oxidation to reach 80% was a bit slow due to temperature restrictions. However, there were 11 points with 300–500 min of reaction time at 20 °C, while only nine points with 250–400 min of reaction time appeared at 30 °C. The finding suggests that higher temperature may not directly reduce the reaction time, though impacting on microbial activity. According to the sludge concentration, three different shapes of points signified three sludge/water ratios. For example, the square points were the symbol of sludge/water = 1:6. There were four points (15 points in total) with sludge/water = 1:6, nine points with sludge/water = 1:3, and ten points with sludge/water = 1:1, respectively. However, the tests at C/N = 3 took the longest time for ammonium removal efficiency to reach 80%, while it was shortest at C/N = 2, except for C/N = 0. The points in the ‘zone’ sector (C/N = 0) were obviously distributed within 200 seconds but the SAOR value fluctuated greatly. It can therefore be concluded that the optimum C/N was 2 for the high removal efficiency of ammonium. However, different factors in the system were related to others and affected each other mutually.

Figures 2, 8 and 9 confirm that the pH value varied with the environmental parameters and the reaction time. When the temperature was raised, the total reaction time and pH valley value were both lowered together with the increased degradation rate. Both the SAOR and pH valley swelled as the C/N increased to 30 °C. In the case of C/N = 2, 3, and 4, an increase in the sludge concentration would increase the pH valley and reduced the reaction time, respectively. Therefore, these results confirm that there is a regular relationship between pH and the performance of the nitritation system.

There were complicated interactions among different environmental parameters and pH in a nitritation system. pH, as a single indicator, was linked directly with the stable performance of the nitritation system. pH could be affected by three parameters: temperature, C/N ratio and sludge concentration. The optimal C/N was kept at 2.0 to ensure efficient oxidation of ammonium. The reaction time was lowest with the temperature = 20 °C, C/N = 0, and sludge/water = 1:1. However, the C/N ratio could be adjusted to close to zero by lowering the temperature to about 10 °C, weakening the HeB, and supplying sufficient biomass. The C/N ratio and sludge/water ratio could also be set at 4.0 and 1:3, respectively, to deal with the impact of low temperature and organic matter.

This work was financially supported by the China Postdoctoral Science Foundation (No. 2020M671400), Natural Science Foundation of Jiangsu Province (No. SBK2020022850),Jiangsu Qing Lan Project, Suzhou Science and Technology Planning Project (ss2019022), Opening Fund of Jiangsu Provincial Key Laboratory of Environmental Science and Engineering (No. Zd1804), and Pre-research Fund of Jiangsu Collaborative Innovation Center of Technology and Material of Water Treatment (XTCXSZ2019-3).

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

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Author notes

Contributed equally to this paper.