Next Article in Journal
Synthesis and Characterization of Visible-Light-Responsive TiO2/LDHs Heterostructures for Enhanced Photocatalytic Degradation Performance
Previous Article in Journal
Urban Pluvial Flood Resilience Evolution and Dynamic Assessment Based on the DPSIR Model: A Case Study of Kunming City, Southwest China
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Water
Volume 17
Issue 17
10.3390/w17172583
water-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Combined Effects of Carbon-to-Nitrogen (C/N) Ratio and Nitrate (NO3−-N) Concentration on Partial Denitrification (PD) Performance at Low Temperature: Substrate Variation, Nitrite Accumulation, and Microbial Transformation

by
Ying Cai
1,
Yujun Song
2,3,
Tangbing Yin
2,3,
Miao Zhang
2 and
Junjie Ji
2,3,*
1
Jiangsu Environmental Engineering Technology Co., Ltd., Nanjing 210036, China
2
College of Environmental Science and Engineering, Yangzhou University, Yangzhou 225127, China
3
Jiangsu Visionage Environmental Technology Co., Ltd., Yangzhou 225100, China
*
Author to whom correspondence should be addressed.
Water 2025, 17(17), 2583; https://doi.org/10.3390/w17172583
Submission received: 13 July 2025 / Revised: 13 August 2025 / Accepted: 27 August 2025 / Published: 1 September 2025
(This article belongs to the Section Wastewater Treatment and Reuse)
Browse Figures
Review Reports Versions Notes

Abstract

In this study, the combined effects of influent carbon-to-nitrogen ratio (C/N = 0.8, 1.5, 2.5, 3.5, 4.5) and nitrate (NO3−-N) concentration (40 and 80 mg/L, labeled as R40 and R80) on the partial denitrification (PD) performance were investigated using an intermittent sequencing batch reactor (SBR) process. With sodium acetate as an additional carbon source, the substrate variation, microbial diversity, and functional bacteria evolution were also explored to reveal the nitrite (NO2−-N) accumulation mechanism at low temperatures (3–12 °C). The results showed that the 3.5-R40 and 2.5-R80 systems both presented the optimal NO2−-N accumulation at a temperature of 10 °C, with the NO2−-N transformation rate (NTR) of 66.89% and 76.79%, respectively. In addition, as the temperature reduced from 10 °C to 5 °C, the NO2−-N accumulation performance was significantly suppressed, where the average effluent NO2−-N of 3.5-R40 (20.00 → 11.00 mg/L) and 2.5-R80 (43.00 → 18.90 mg/L) systems reduced by nearly half. It is worth noting that there was almost no NO2−-N accumulation at a C/N ratio of 0.8, although higher NO3−-N concentration promoted NTR under the same C/N ratio. The high-throughput sequencing showed that the minimum Shannon value of 3.81 and the maximum Simpson value of 0.095 both occurred at a C/N ratio of 2.5, suggesting the downshifted microbial richness. Proteobacteria and Bacteroides increased significantly from 35.31% and 18.34% to 51.69–60.35% and 18.08–35.21%, as compared with the seeding sludge. Thauera and Flavobacterium as the main contributors to NO2−-N accumulation accounted for 31.83% and 20.30% at the C/N ratio of 2.5 under a low temperature of 5 °C. The above discussion suggested that higher temperature (10 °C), lower C/N ratio (2.5–3.5), and higher NO3−-N concentration (80 mg/L) were more favorable for the stable PD formation.

1. Introduction

In recent years, environmental issues have garnered increasing attention from all sectors of society, among which water resources are closely related to human survival. As such, how to treat sewage productively and energy-efficiently has become a hot issue. Biological nitrogen removal (BNR) processes effectively degrade nitrogenous compounds from wastewater and facilitate compliance with the discharge standards outlined by national policy [1]. Particularly, the anaerobic ammonia oxidation (Anammox) process reacts ammonia (NH4+-N, electron donor) with nitrite (NO2−-N, electron acceptor) to generate nitrogen gas (N2) and nitrate (NO3−-N) [2,3], which manifests significant advantages such as reduced aeration, low sludge production, and reduced carbon source addition [4]. Consequently, partial denitrification (PD, NO3−-N → NO2−-N) has gained considerable attention due to its role in promoting stable nitrite accumulation, which is essential for enhancing the real application of the Anammox process. Studies have shown that many factors affect PD performance, including temperature, carbon-to-nitrogen (C/N) ratio, carbon source, dissolved oxygen (DO), and pH values [5,6,7], etc. In these studies, all the findings indicated that PD could be utilized to enhance traditional BNR efficiency in the upgrading and reconstruction of wastewater treatment plants (WWTPs).
Regarding the effects of temperature on PD, most scholars have focused on ambient temperatures ranging from 15 to 30 °C, revealing that this scope exerts a positive impact on the NO2−-N accumulation. According to Li et al. [8], the denitrification rate increased gradually with the elevation in temperature, and extending the hydraulic retention time (HRT) can also improve NO3−-N removal, although low temperatures may impede it. In particular, lower temperatures (15–17 °C) may result in oversaturated DO conditions and suppress the microbial activity associated with denitrification rates, thereby restricting the occurrence of anoxic denitrification throughout the operational period [9]. Extreme temperature variations can induce alterations in the structural integrity of cell membranes, including lipids and proteins [10]. However, few scholars have explored the NO2−-N accumulation characteristics of PD at lower temperatures [11]; therefore, this is a precious and special study to reveal the effect of decreasing temperature on nitrogen removal for stable operation of WWTPs under seasonal variations.
Additionally, many scholars have investigated the impact of the C/N ratio on PD performance. It was shown that for a given influent NO3−-N concentration, the peak NO2−-N productions increased with higher C/N ratios [12]. Moreover, the experimental data suggested an increase in both the maximum NO2−-N amount and the NO2−-N accumulation rate with rising NO3−-N concentrations [13]. In the combined partial denitrification-anammox (PD/A) process, the nitrate removal efficiency (NRE) was maintained around 89–90% with a mean nitrate-to-nitrite transformation ratio (NTR) of 84.43% at a C/N ratio of 2.5 [14]. However, the determination of the optimal C/N ratio was not an easy task, as different ratios have been reported for successful application [15,16]. Actually, a high C/N ratio may lead to unnecessary complete denitrification, while a lower C/N ratio was associated with the excessive residues of NO3−-N [17]. Returning to temperature, decreases or rises in temperature may influence the microbial activities and system dynamics [18], so how to protect functional bacteria in unfavorable conditions and achieve satisfactory NRE remains a huge challenge. Carbon sources as the source of energy and donor of electrons, facilitate bacteria’s metabolism during PD processes [19], but the competition between the C/N ratio and temperature to maintain the survival of denitrification bacteria needs to be further investigated. Hence, the factors of temperature, C/N ratio, and influent NO3−-N concentration are all critical for starting the PD process and maintaining stable operation, especially in cold regions.
A sequencing batch reactor (SBR) process was established with intermittent aeration by utilizing sodium acetate as the external carbon source, and the novelty of this study was to investigate the combined effects of the C/N ratio and NO3−-N concentration on NO2−-N accumulation and potential mechanism under lower temperature conditions (3–12 °C). Firstly, the nutrient transformation during both long-term operation and typical cycles was elucidated by analyzing substrate variations, offering an operating control strategy for technological advancement and process optimization. Secondly, the microbial community structure was assessed through high-throughput sequencing analysis to reveal the NO2−-N accumulation characteristics, proposing appropriate microbial dynamics for optimizing process performance and achieving efficient nitrogen removal under different operating conditions. Finally, the microscopic metabolic mechanism and macroscopic application feasibility were overviewed, with the aim of providing theoretical foundations for the popularization and application of the PD/A process.

2. Materials and Methods

2.1. Experimental Device and Operational Mode

As shown in Figure 1a, the cylindrical PD-SBR (working volume: 10 L, Yangzhou, China) was operated at room temperature, and the running time stretched across November to December with the ambient temperature changing from 10 ± 2 °C to 5 ± 2 °C. The reactor was fitted with a mechanical stirrer (IKA REO basic C type, Germany), while the microporous aeration was adopted at the bottom through a gas flow meter (LZB-4, Guangzhou, China) combined with an air pump (ACO-6603, Guangzhou, China). The experimental process, operated in an anoxic/aerobic alternating mode (Figure 1b), consisted of four cycles per day. Each operational cycle lasted 270 min, with the following duration for each stage: influent stage (15 min), anoxic stage (180 min), aerobic stage (30 min), sedimentation stage (30 min), and drainage stage (15 min). At the beginning of each cycle, 5 L of synthetic wastewater, along with appropriate amounts of NO3−-N and COD, were pumped into the reactor, followed by agitation under anoxic conditions for the production of NO2−-N accumulation. To effectively expel the N2 produced by denitrification for better sludge settling and higher biological activity [20], a brief aeration period of 30 min (DO: 2.0–3.0 mg/L) was conducted, and approximately 50 mL of sludge was discharged before sedimentation to ensure that the sludge retention time (SRT) was sustained around 25 days (Table 1).

2.2. Seeding Sludge and Synthetic Wastewater

The seeding sludge (SS) used in the test was obtained from the biological pond of Tangwang WWTP (Yangzhou, China), known for its effective denitrification performance. The initial mixed volatile suspended solids (VSS) of the PD-SBR was kept at about 2500 mg/L [21]. The test water was artificially simulated with the carbon and nitrogen sources provided by sodium acetate (CH3COONa) and sodium nitrate (NaNO3), respectively. The reactors were categorized into two groups based on the initial NO3−-N concentration: R40 (NO3−-N: ~40 mg/L) and R80 (NO3−-N: ~80 mg/L), and the COD concentration fluctuated within the range of 32 mg/L to 360 mg/L, giving initial C/N ratios of 0.8, 1.5, 2.5, 3.5, and 4.5, respectively.
Moving on to the C/N ratio, R40 and R80 were further subdivided into five types: 0.8-R40 and 0.8-R80 (C/N = 0.8), 1.5-R40 and 1.5-R80 (C/N = 1.5), 2.5-R40 and 2.5-R80 (C/N = 2.5), 3.5-R40 and 3.5-R80 (C/N = 3.5), 4.5-R40 and 4.5-R80 (C/N = 4.5), and each system was operated for 120 cycles (Table 1). Meanwhile, in order to maintain good microbial growth and metabolism, 1 mL trace element solution (per liter: 0.03 g CuSO4·5H2O, 0.06 g Na2MoO4·2H2O, 0.12 g MnCl2·4H2O, 0.12 g ZnSO4·7H2O, 0.15 g H3BO3, 0.15 g CoCl2·6H2O, 0.18 g KI, 1.5 g FeCl3·6H2O, and 10 g ethylene diamine tetraacetic acid (EDTA)) [21] was fed into the reactor during each cycle.

2.3. Analytical Methods

All wastewater samples were filtred through 0.45 μm filters before analysis. COD was monitored by a COD quick-analysis apparatus (LH-3C, Lanzhou, China), NO2−-N was determined by N-(1-naphthyl)-ethylenediamine spectrophotometry, NO3−-N was analyzed by UV spectrophotometry (U-T6), and the above determinations were made by the standard methods [22]. The temperature was monitored by the WTW meters (WTW Multi 3420, Germany). The Pearson correlation analysis [23,24] between the C/N ratio, NO3−-N, temperature with NO2−-N, NTR, and NRE was conducted by SPSSPRO.
The removal efficiency of total nitrogen (ReTN) was calculated as follows:
ReTN (%) = [1 − (NO2−-Neff + NO3−-Neff)/(NO2−-N)inf + NO3−-Ninf)] × 100%
NTR and NRE were expressed by the following equations [14]:
NTR (%) = (NO2−-Neff − NO2−-Ninf)/(NO3−-Ninf − NO3−-Neff) × 100%
NRE (%) = (NO3−-Ninf − NO3−-Neff)/NO3−-Ninf × 100%
where NO3−-Ninf, NO2−-Ninf, NO3−-Neff, and NO2−-Neff were the influent and effluent concentrations of NO3−-N and NO2−-N in the PD-SBRs, respectively, mg/L.

2.4. High-Throughput Sequencing

The SS and five PD-SBR samples of the R80 group after the steady operation were collected for high-throughput sequencing analysis. Following the manufacturer’s instructions, DNA was extracted using the E.Z.N.A.® Soil DNA Kit (Omega Bio-tek, Norcross, GA, USA). The NanoDrop1000 spectrophotometer was used to determine the qualitative and quantitative analysis at optical densities (OD) of 260 and 280 nm. In a sequential manner, the polymerase chain reaction (PCR) amplification was performed on an ABI GeneAmp® 9700 PCR System (Applied Biosystems, Foster City, CA, USA) using primers 338F (5′-ACTCCTACGGGGAGGCAGCA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). Thereafter, the PCR products were implemented on the Illumina MiSeq PE300 platform (Personalbio Biotechnology Co., Ltd., Shanghai, China) [21], and all the raw data were provided by Meiji BioCloud (SRP057140, Shanghai, China).

3. Results and Discussion

3.1. Substrate Variation and Nitrite Accumulation in the Long-Term Operation

The evolutions of NO3−-Ninf, NO3−-Neff and NO2−-Neff, NTR, and NRE at different temperatures in R40 and R80 groups were revealed and compared at given C/N ratios (0.5, 1.5, 2.5, 3.5, and 4.5) (Figure 2). All 10 PD-SBR were operated for 120 cycles at room temperature, which can be categorized into two phases based on the temperature change trends: Phase Ⅰ (1–56 cycles) with the temperature fluctuating around 10 ± 2 °C, and Phase II (57–120 cycles), with the temperature maintained at approximately 5 ± 2 °C.
For the R40 systems, the average NO2−-Neff values were 0.056, 4.63, 9.35, 17.07, and 13.88 mg/L in Phase I, while the relevant concentrations reduced to 0, 3.30, 6.28, 12.70, and 9.75 mg/L in Phase II, respectively. Due to the sensitivity of denitrifying bacteria to temperature changes and the greater impact of temperature on PD [15], the average NO2−-Neff in Phase I was higher than that in Phase II of both the R40 and R80 groups. Thereinto, the peak NTR occurred at the temperature of 9–10 °C in the R80 systems under all C/N ratio conditions (0.8-R80 (34.24%), 1.5-R80 (63.51%), 2.5-R80 (76.79%), 3.5-R80 (75.57%), 4.5-R80 (68.15%)), presenting the same rules with the R40 systems (0.8-R40 (4.00%), 1.5-R40 (36.17%), 2.5-R40 (44.31%), 3.5-R40 (66.89%), 4.5-R40 (66.16%)). According to previous studies, lower temperatures (<10 °C) inhibited microbial activity associated with denitrification rates, thereby disrupting the anoxic environment and limiting NO2−-N accumulation [9]. Similarly, in this study, when the temperature was lowered from 10 °C to 5 °C, the NTR decreased significantly in the R40 (0.8-R40 (4.00% → 0.00%), 1.5-R40 (36.17% → 21.21%), 2.5-R40 (44.31% → 17.32%), 3.5-R40 (66.89% → 42.15%), 4.5-R40 (66.16% → 29.03%)) and R80 (0.8-R80 (34.24% → 12.94%), 1.5-R80 (63.51% → 38.19%), 2.5-R80 (76.79% → 40.21%), 3.5-R80 (76.57% → 45.76%), 4.5-R80 (68.15% → 38.07%)) groups (Figure 2). It was noteworthy that the average NO2−-Neff of the 3.5-R40 (20.00 → 11.00 mg/L) and 2.5-R80 (43.00 → 18.90 mg/L) systems was reduced by nearly half.
In addition, a positive correlation between NRE and NTR was observed; for example, in the 3.5-R40 system, NRE peaked at 66.69% at 10 °C but decreased to 54.99%, 47.86%, and 43.59% as the temperature dropped to 5 °C, 4 °C, and 3 °C, respectively (Figure 2f), showing that the nitrogen removal efficiency was depressed with decreasing ambient temperature [7]. Nevertheless, there is no doubt that the PD performance was closely related to temperature variations. However, it was reported that lowering the temperature from 22 °C to 14 °C resulted in enhanced NO2−-N accumulation along with an increase in NRE from 72.2% to 77.2% [25]. It was also found that the nitrite accumulation was facilitated from 60% to 75% as the temperature reduced from 30 °C to 20 °C [18], and the PD performance could be enhanced under a low temperature of 15 °C [26]. Combining with the results of this experiment, it can be inferred that the PD performance was free from the negative influences at a lower temperature of 10 °C, but the obvious deterioration of NO2−-N accumulation and NTR efficiency occurred by lowering the temperature to the threshold level of <5 °C. Because the rate of PD was related to enzyme activities (e.g., nitrate reductase (Nar) and nitrite reductase (Nir)), where Nir was more sensitive to temperature than Nar, and Nir inhibition under high temperatures led to more NO2−-N accumulation [27].
Specifically, the average NTR values of the R40 group at the five conditions (C/N = 0.5, 1.5, 2.5, 3.5, and 4.5) were much lower than those of the R80 group. Under the same influent C/N of 0.8 (Figure 2a), the average NTR and NRE were only 0.5% and 8.63% in the R40 systems, while the corresponding values reached 19.5% and 9.16% in the R80 systems, respectively. The peak NTR was 44.31% in the 2.5-R40 system and 76.79% in the 2.5-R80 system, which was consistent with previous findings that higher NO3−-N concentrations promoted nitrite accumulation at the same C/N ratio (e.g., 0.8-R40: 0.5%; 0.8-R80: 19.16% [28]). Similarly, NTR increased from 87.76% to 89.31% when NO3−-N concentration climbed from 20 mg/L to 150 mg/L [15], and the possible reason has been speculated to be the inhibited NO2−-N reduction triggered by the unbalanced activities between Nar and Nir under higher NO3−-N environment [21]. Because more NO3−-N concentration would significantly increase the Nar activity and accelerate the reduction of NO3−-N to NO2−-N.
Moving on to the influence of the C/N ratio, the mean NTR increased from 46% to 60.42% in the R80 systems, while NRE fluctuated from 24.68% to 55.75% as the C/N ratio increased from 1.5 to 3.5 (Figure 2b–d). However, when the C/N ratio continued to soar up to 4.5 (Figure 2e), the mean values of NTR and NRE exhibited a decreasing trend, measuring 56.98% and 40.55%, respectively. The above trends of NTR and NRE changed in alignment with those in the R40 systems, displaying an optimal C/N range around 2.5–3.5. The optimal C/N ratio range of 1.5–3.0 was also previously proposed [29], and numerous scholars have shown similar NO2−-N accumulation and NTR in excess of 80% when the C/N ratio was set between 2.5 and 3.0 using sodium acetate as a carbon source [30]. The optimal NTR value of 45.28–47.50% (C/N = 2.5–3.0) was also reported with a significant decline in NTR when the C/N ratio exceeded 3.5 [27]. These findings indicated that both excessively high and low C/N ratios were unfavorable for NTR and NRE. However, different from these conclusions, it was worth noting that the key factor affecting denitrification was the residual NO3−-N concentration rather than the C/N ratio [31], which implied that stable NO2−-N accumulation was virtually independent of the C/N ratio [15]. In fact, except NO3−-N concentration, both temperature and C/N ratio were the essential factors influencing NO2−-N accumulation in PD systems. On the one hand, the low temperatures resulted in decreased microbial activity and lower reaction rates, so NO3−-N and COD concentrations were more in demand than in high-temperature environments [32]. On the other hand, superior NO2−-N accumulation could also be realized at a relatively low temperature with higher C/N ratios (e.g., >4 [33]), since lower temperature prompted an increase in the optimal C/N ratio.

3.2. Substrate Variation and Nitrite Accumulation in the Typical Cycle

The variation profiles of NO3−-N, NO2−-N and COD in the typical cycle at the test temperature of 10 ± 2 °C were exhibited, and the mechanism of NO2−-N accumulation during the stable operation was further elaborated (Figure 3). Based on the observed changes in substrate concentration over reaction time, the denitrification process can be divided into three distinct phases: Phase i (0–60 min), Phase ii (60–180 min), and Phase iii (180–210 min).
On the one hand, the COD utilization amounts increased from 54 mg/L to 196 mg/L when the C/N ratio varied from 0.8 to 4.5 in the R80 group, which were much higher than the COD consumption in the R40 group (Figure 3a,b). This implied that the high influent NO3−-N could promote the high-efficiency utilization of carbon sources. Furthermore, the COD degradation rate was positively correlated with the C/N ratio in all systems (y4.5 (1.30) > y3.5 (1.09) > y2.5 (0.91) > y1.5 (0.52) > y0.8 (0.05) in the R40 group (Figure 3a); y4.5 (3.27) > y3.5 (2.53) > y2.5 (1.96) > y1.5 (1.37) > y0.8 (0.89) in the R80 group (Figure 3b)). It was worth noting that 4.5-R40 (70.00 mg/L), 3.5-R80 (60.00 mg/L) and 4.5-R80 (81.00 mg/L) showed higher COD residuals, probably due to the “carbon breakthrough” phenomenon [12], implying that the denitrifying bacteria no longer conducted the excess COD in the denitrification stage; consequently, not all COD was utilized for NO3−-N removal. As well, the theoretical and actual COD consumptions linked with C/N ratio and NO3−-N concentration in the R40 and R80 systems were further calculated and compared based on the operating data (Figure 3k), in which 1.14 and 1.72 mg of COD were utilized to reduce 1 mg of NO3−-N to NO2−-N and 1 mg of NO2−-N to N2 [24]. It was found that the actual COD consumption was generally higher than the theoretical values for all C/N ratios (especially for 4.5-R40 and 4.5-R80), and the high NO3−-Ninf utilized more COD under the same C/N ratio. It was speculated that the low temperature led to inhibited enzyme activity and reduced electron transfer, but a higher C/N ratio or NO3−-Ninf facilitated the replenishment of energy loss for microorganisms to maintain cellular activity through endogenous respiration [28]. However, for the lower C/N ratios under similar NO3−-N concentrations (e.g., 0.8-R80 and 1.5-R80 systems), the effluent COD at 180 min (5–27 mg/L) was much lower with continued degradation of NO3−-N, presumably owing to the possibility of sludge adsorption [34,35]. Hence, due to the secondary release of carbon adsorbed on the sludge flocs (Figure 3b), the COD concentration exhibited a slight increasing trend (5 → 8 mg/L; 27 → 32 mg/L) after aeration (180–210 min), presenting various substrate transformation and metabolic mechanisms for PD maintenance.
On the other hand, obvious NO2−-N accumulation (Figure 3c,d) was observed as well as significant NO3−-N reduction (Figure 3e,f). During Phase I, NO3−-N concentration decreased rapidly (slopes: 0.10–0.47 in the R40 group; 0.14–0.99 in the R80 group), accompanied by the rapid NO2−-N generation. The peaks of NO2−-N accumulation appeared at 60 min (19.20 mg/L (3.5-R40) > 16.96 mg/L (4.5-R40) > 11.20 mg/L (2.5-R40) > 4.14 mg/L (1.5-R40); 46.6 mg/L (2.5-R80) > 39.20 mg/L (3.5-R80) > 25.20 mg/L (4.5-R80) > 17.71 mg/L (1.5-R80)) in addition to 0.8-R40. Correspondingly, the highest NO2−-N accumulation rates of the two groups were also found at C/N ratios between 2.5 (y2.5 = 0.17x; y2.5 = 0.83x) and 3.5 (y3.5 = 0.29x; y3.5 = 0.66x), respectively. The results were consistent with previous studies that C/N ratios of 2.5–3.5 favored nitrite accumulation, while higher C/N ratios (>3.5) may result in suppressive NO2−-N transformation [36]. It suggested that limited carbon sources can facilitate greater enrichment of PD denitrifying bacteria [37,38] although an extremely low C/N ratio (e.g., 0.8) may inhibit microbial growth or colonization [39]. At Phase II, the two groups were accompanied by significant decreases in NO2−-N concentration, with the slopes changing around 0.001–0.045 (R40) and 0.001–0.148 (R80), indicating that the excessive NO2−-N was gradually denitrified to N2 as an electron acceptor [32]. Obviously, NO2−-N was almost non-existent at the C/N ratio of 0.8, and studies have shown that insufficient carbon source led to bacterial lysis and death, which deteriorated the PD performance [40]. As for Phase III, the concentrations of NO3−-N and NO2−-N in all reactors were basically unchanged, confirming that the nitrifying bacteria (especially NO2−-N-oxidizing bacteria, NOB) had been swept out during the short aeration [21].
From the perspectives of TN (Figure 3g,h) and ReTN variations (Figure 3i,j), the denitrification patterns of the two groups were comparable, where TN removal mainly concentrated in Phases I and II (0–180 min). In Phase III (180–210 min), the TN concentrations were overall unchanged. For the R80 systems, the effluent TN concentrations were 71.73. 70.50, 44.90, 34.50, and 37.50 mg/L, corresponding to ReTN of 13.1%, 14.6%, 46.1%, 56.8%, and 53.8% in the R40 systems (e.g., 13.3% (C/N = 0.8), 39.9% (C/N = 1.5), 56.3% (C/N = 2.5), 51.1% (C/N = 3.5), and 53.5% (C/N = 4.5)). The denitrification performance was greatly enhanced when the influent C/N ratio increased from 0.8 to 3.5–4.5, and it was supposed that the influent carbon source was relatively insufficient at C/N ratios of 1.5–2.5, especially in the R80 systems, contributing to lower ReTN but higher nitrite accumulation [21]. Conversely, under higher C/N ratios of 2.5–3.5, the overall performance was relatively remarkable, despite slight differences in NO2−-N accumulation and ReTN, which demonstrated that the effective denitrification system could be carried out only when the carbon source was sufficient [41]. In addition, the correlation based on Pearson analysis (Figure 3l) revealed that the C/N ratio was positively correlated with NO2−-N concentration (r = 0.50, p < 0.01), NTR (r = 0.63, p < 0.01) and NRE (r = 0.67, p < 0.01), conforming to the superior PD performance in the 3.5-R40 and 2.5-R80 systems (Figure 2 and Figure 3). By contrast, NO3−-N concentration was less relevant to NO2−-N concentration (r = 0.45, p < 0.01), NTR (r = 0.23, p < 0.01), and NRE (r = −0.23, p < 0.01). Notably, temperature showed an inconspicuous correlation with NTR (r = 0.31, p < 0.01) and NRE (r = 0.25, p < 0.01), suggesting a strong shock resistance ability to environmental factors.

3.3. Species Diversity

The smoothest SS curve implied the highest microbial diversity (Figure 4a), while the steepest curve at the C/N ratio of 2.5 represented the lowest biodiversity [21]. Microbial diversity suggested that the sludge diversity in the PD-SBRs had been changed through the cultivation with different influent C/N ratios. The clustering analysis (Figure 4b) demonstrated that at a 0.97 similarity threshold [29], the species composition for a C/N ratio of 2.5–3.5 was most similar, with the similarity distance coefficients (SDC) of 0.22, equating to the similarity of 78%. In particular, data from the typical cycle (Figure 3) showed that NO2−-N accumulation under these conditions was closely aligned. In contrast, when the C/N ratios were 0.8 and 1.5, the sludge samples exhibited the most similarity with SS species composition, with a distance coefficient of 0.43, corresponding to 57% similarity. Similarly, the principal coordinates analysis (PCoA) on the genus level (Figure 4d) exhibited that the 6 samples were divided into three clusters: cluster I containing SS only, the samples of C/N = 0.8 and C/N = 1.5 belonging to cluster II, and the remaining samples (e.g., C/N = 2.5, C/N = 3.5, C/N = 4.5) forming cluster III, which conformed to the results of the hierarchical clustering tree (Figure 4b). The operational taxonomic units (OTUs) in the overlapping portions of the Venn diagrams (Figure 4c) represented the species numbers that were common to all samples, while non-overlapping portions symbolized the species numbers that were unique to the corresponding samples [19,35]. The common number of OTUs was 514, which accounted for 27.35% (SS), 37.35% (C/N = 0.8), 38.36% (C/N = 1.5), 55.15% (C/N = 2.5), 47.46% (C/N = 3.5), and 53.65% (C/N = 4.5) in the respective samples. However, the individual numbers of OTUs being unique to the samples were 1275 (SS), 862 (C/N = 0.8), 826 (C/N = 1.5), 418 (C/N = 2.5), 569 (C/N = 3.5), and 444 (C/N = 4.5), implying the continuous enrichment of unique genera with higher microbial aggregation, especially at C/N = 2.5.
Combined with the microbial diversity index presented in Table 2, the sequence range of all samples fell between 44,032 and 60,472, with 932–1879 OTUs obtained by clustering valid sequences at 97% similarity. Although the coverage exceeded 0.99, the abundance and diversity of sludge samples varied significantly compared to SS. Overall, the microbial diversity decreased across the five reactors, as confirmed by different diversity indices. Specifically, Chao and ACE for community richness declined from 2084 and 2052 to 1296–1752 and 1276–1727, respectively. Additionally, the Shannon and Simpson indices for community diversity [42] also shifted considerably, with the minimum Shannon value of 3.81 and the maximum Simpson value of 0.095 at C/N = 2.5, proving that the microbial richness was at its lowest. The above results also coincided with the changes in OTUs illustrated in Figure 4.

3.4. Dominant Microbial Community

The microbial distribution of functional bacteria in each sludge sample at a temperature of 3–12 °C was compared at both phylum and genus levels (Figure 5). Compared to SS, the proportions of Proteobacteria and Bacteroidetes, the two dominant phyla, increased from 35.31% and 18.34% to 51.69–60.35% and 18.08–35.21%, respectively. This shift resulted in an enhancement of denitrification performance and improved the conversion rates of NO3−-N to NO2−-N, while Chloroflexi capable of oxidizing NO2−-N to NO3−-N reduced from 8.42% to 1.47–3.95% (Figure 5a). Another phylum, Myxococcota, which is unfavorable for NO2−-N accumulation [43], also decreased significantly with the increasing C/N ratio, dropping from 2.10% (SS) to 0.17% (C/N = 4.5). Additionally, Patescibacteria (1.27–0.38%), Actinobacteria (2.95–0.53%), Firmicutes (3.97–0.15%), and Acidobacteria (14.70–1.74%), all of which play vital roles in degrading carbohydrates during the heterotrophic metabolism [44], exhibited a significant decreasing trend under all working conditions compared to SS.
Significant differences were observed at the genus level across the six samples (Figure 5b), where Thauera, known as denitrifying bacteria that stably maintain NO2−-N accumulation [20], accounted for a relatively high percentage of 19.31–31.83% (C/N = 0.8–4.5) compared to SS (0.87%). Thauera enrichment was associated with the inhibition of NO2−-N reduction [15] due to denitrifying enzyme synthesis at different electron acceptors (NO3−-N or NO2−-N). The macro-genomic analyses showed that the abundance of NO3−-N reductase (Nar: NO3−-N → NO2−-N) was higher than that of NO2−-N reductase (Nir: NO2−-N → NO) in Thauera [45]. Moreover, Nar was more competitive than Nir for electron donors during denitrification, highlighting the strong influence of the C/N ratio on the activities of Nar and Nir [19]. At lower C/N ratios, Nar preferentially utilized the carbon source to reduce NO3−-N, which inhibited Nir due to insufficient carbon access and resulted in NO2−-N accumulation. Conversely, at higher C/N ratios, where carbon sources were sufficient, Nir could also access adequate carbon capacity, reducing the likelihood of NO2−-N accumulation. Flavobacterium exhibited similar denitrifying properties to Thauera [19,46,47] and also proliferated in the reactors, increasing from 0.31% (SS) to 0.42–20.85% (C/N = 0.8–4.5). In particular, at a C/N ratio of 2.5, the two genera accounted for 31.83% and 20.30%, respectively, confirming the earlier findings that better NO2−-N accumulation was achieved (Figure 2 and Figure 3).
It was noteworthy that Flavobacterium showed better denitrification ability and strong adaptability to cold climates [46], and its abundance reached 20.30% and 20.85% at C/N ratios of 2.5 and 4.5, respectively, which was significantly higher than the other reactors (ranging from 0.31% to 13.94%). It was also found that Flavobacterium was more effective at generating NO2−-N in cold conditions, and its abundance increased to 16.6% when the temperature reduced from 32 °C to 5 °C [47]. Considering the ambient temperature changes in this experiment, it was hypothesized that the low-temperature environment (5–10 °C) accelerated the enrichment of Flavobacterium, which was the key factor in the enhanced PD performance observed at a C/N ratio of 2.5 (Figure 2 and Figure 3). However, Nitrospira and Nitrobacter, known as NOB [48], were undetected after long-term operation, and the elimination of nitrifying bacteria prevented NO2−-N from being destroyed during the short oxic stage, in accordance with the substrate variation in the typical cycles (Figure 3). In addition, Saprospiraceae, Comamonadaceae, and Terrimonas, which play key roles in the denitrification process, accounted for 3.03–5.01%, 3.07–8.20%, and 2.66–3.62%, respectively. The genera Ferruginibacter and Simplicispira, primarily involved in the degradation of organic matter [47], changed from 0.73% and 0.02% to 5.64% and 7.73%. Zoogloea, which is vital for bioconcentration and sludge granulation [49], also showed better enrichment at C/N ratios of 0.8 and 1.5 with the abundances achieving 5.66% and 3.66%, implying the COD release triggered by sludge adsorption (Figure 3b). Meanwhile, the results indicated that the genus of Zoogloea could also maintain good biological activity at low C/N ratios.

3.5. Application Feasibility of PD-Related Processes

Currently, PD is the most common method to achieve NO2−-N accumulation in wastewater treatment, offering many advantages over conventional BNR processes. As shown in Figure 6a, PD is often combined with the Anammox process, creating a new application prospect with outstanding advantages of higher economic value (e.g., stable NO2−-N production, high NO3−-N removal, low carbon consumption) and environmental benefit (e.g., reduced greenhouse gas, low sludge production) [14,31]. Nevertheless, it still faces many technical challenges in terms of long start-up cycles, microbial activity inhibition, unstable NO2−-N production, and low treatment efficiency. From the perspective of functional genes, the transcription and translation levels were suppressed with reduced metabolism-related enzyme activities at low temperatures [50]. As reported, napA and narG genes were important factors for NO2−-N accumulation in the PD process [51], but denitrification was less competitive for NO2−-N generation [52] when the nirS and nirK genes were hindered at lower temperatures. Taken together, it can be speculated that the essential reasons for the higher NTR and NO2−-N accumulation at increased temperature were the stimulant functional genes of narG and napA accompanied by restrained abundances of nirS and nirK. However, the potential mechanism of temperature effect on transcribed genetic expression needs to be further investigated.
Furthermore, a summary of how temperature, C/N ratio, and NO3−-N concentration affect PD performance in relation to NO2−-N buildup was provided (Table 3). It was found that NTR reached 71.7% at a temperature of about 22 °C under the C/N ratio of 2.5 [16], when the temperature increased to 23.6–28.8 °C [53]. As a contrast, at the same C/N ratio (2.5), NTR at lower temperatures (3–12 °C) was 76.79% in the present study (R80 system), but it changed to 68.15–75.57% as the C/N ratio rose to 3.5–4.5. Consistent with the results of our study, the PD process presented a high NTR of 80% at the C/N ratio of 3.0 under temperatures between 16 and 28 °C [15]; however, NTR declined to 57.5% when the temperature dropped to 10.6–18.3 °C [54]. In addition to high temperature, a suitable carbon source, lower C/N ratio, and higher NO3−-N concentration were also the key factors to obtain stable NO2−-N production [28], and many studies have reached similar conclusions that NTR was around 80% when the C/N ratio was set between 2.5 and 3.0 using acetate as a carbon source [15,16,53]. In the case of glycerol, the peak NTR of 72.5% was attained at a C/N ratio of 2.6 [55], showing the importance of carbon source type [19]. Even so, conventional denitrification processes required a higher C/N of 4.0–6.0 [56], which significantly increased the carbon demand and operating cost of low C/N ratio wastewater treatment. Moreover, the industrial products often generated significant amounts of high-strength NO3−-N wastewater [13], which typically relied on traditional BNR technologies that were costly with limited applicability. As shown in Figure 6b, one-stage and two-stage PD/A systems were regarded as the two important approaches to treat NO3—N-rich and domestic wastewater simultaneously [20,26], where the oxygen demand, carbon source requirement, and sludge production could be reduced by 31.07%, 89.86%, and 81.65% when compared with the traditional nitrification–denitrification [48]. For real applications, the two-stage PD/A process showed prominent advantages under low-temperature operation [54], since the separate regulation of two reactors was more suitable to resist environmental factors for low C/N ratio wastewater treatment.
In addition, systems treating wastewater with elevated influent NO3−-N concentrations (30–400 mg/L) [53] exhibited significantly superior NTR compared to those with lower NO3−-N levels. In this study, the PD performance of the R80 group also outperformed that of the R40 group (Figure 2 and Figure 3). Previous research corroborated that when the influent NO3−-N concentration increased from 29.5 mg/L to 64.9 mg/L, the optimal NO2−-N accumulation correspondingly rose from 18.9 mg/L to 37.8 mg/L [57]. The reason may be attributed to the fact that the higher NO3−-N concentration provided more sufficient electron acceptors [28] to promote the metabolic activity of PD denitrifying bacteria by inhibiting the degradation rate of NO3−-N. Generally, moderately elevating influent NO3−-N concentration or nitrate loading rates (NLR) enhanced the stability of PD systems [58], which could be used to alleviate the inhibition effect of low temperature, providing a new operation strategy of the PD processes for cold regions. Even so, there is a pressing need to explore additional effective control strategies of PD/A process, as well as to investigate the impacts of heavy metals, antibiotics, and other substances on microbial activity.

4. Conclusions

The NO2−-N accumulation and NTR performance were free from the negative influences at a lower temperature of 10 °C, but obvious inhibition occurred at the threshold of <5 °C, which should not be overlooked under seasonal changes. The 3.5-R40 and 2.5-R80 systems demonstrated the optimal PD efficiency, and elevated influent NO3−-N concentration effectively alleviated the inhibition effect of low temperature. The optimal C/N ratio range of 2.5–3.5 promoted the enrichment of distinct bacterial taxa with higher aggregation levels (932–1083 OTUs), predominantly within the phyla of Proteobacteria and Bacteroidetes. Specifically, the enrichment of Thauera and Flavobacterium played a pivotal role in NO2−-N accumulation, contributing to the enhanced PD performance, especially under low-temperature conditions.

Author Contributions

Conceptualization, J.J.; methodology, T.Y.; validation, M.Z.; visualization, Y.S.; data curation, Y.C.; software, T.Y.; supervision, M.Z.; investigation, Y.S.; resources, Y.C.; project administration, J.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was financially supported by the Research and Development Project of Jiangsu Environmental Engineering Technology Co., Ltd. (Research and Application of Wetland Green Substrate Products Based on the Resource Utilization of Construction Waste, Grant No. JSEP-GJ20220011-RE-ZL) (China).

Data Availability Statement

Data will be made available on request from the corresponding author.

Conflicts of Interest

Author Ying Cai was employed by the company Jiangsu Environmental Engineering Technology Co., Ltd., while authors Yujun Song, Tangbing Yin, and Junjie Ji were employed by the company Jiangsu Visionage Environmental 417 Technology Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors declare that this study received funding from Jiangsu Environmental Engineering Technology Co., Ltd. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.

References

  1. Thakur, I.S.; Medhi, K. Nitrification and denitrification processes for mitigation of nitrous oxide from waste water treatment plants for biovalorization: Challenges and opportunities. Bioresour. Technol. 2019, 282, 502–513. [Google Scholar] [CrossRef] [PubMed]
  2. Hu, J.; Qian, F.; Li, X.; Tang, Y.; Zhu, C.; Fu, J.; Wang, J. Rapid start-up and operational characteristics of partial denitrification coupled with anammox driven by innovative strategies. Sci. Total Environ. 2024, 927, 172442. [Google Scholar] [CrossRef]
  3. Li, W.; Li, X.; Zhang, Q.; Kao, C.; Hou, X.; Peng, Y. Recent advances of partial anammox by controlling nitrite supply in mainstream wastewater treatment through step-feed mode. Sci. Total Environ. 2024, 912, 168965. [Google Scholar] [CrossRef] [PubMed]
  4. Wang, X.; Yang, H. Nitrogen removal performance of anammox immobilized fillers in response to seasonal temperature variations and different operating modes: Substrate utilization and microbial community analysis. Sci. Total Environ. 2022, 829, 154574. [Google Scholar] [CrossRef]
  5. Di Capua, F.; Iannacone, F.; Sabba, F.; Esposito, G. Simultaneous nitrification-denitrification in biofilm systems for wastewater treatment: Key factors, potential routes, and engineered applications. Bioresour. Technol. 2022, 361, 127702. [Google Scholar] [CrossRef]
  6. Lu, X.; Oehmen, A.; Zhao, J.; Duan, H.; Yuan, Z.; Ye, L. Insights on biological phosphorus removal with partial nitrification in single sludge system via sidestream free ammonia and free nitrous acid dosing. Sci. Total Environ. 2023, 895, 165174. [Google Scholar] [CrossRef]
  7. Wu, H.; Bai, X.; Li, L.; Li, Z.; Wang, M.; Zhang, Z.; Zhu, C.; Xu, Y.; Xiong, H.; Xie, X.; et al. Two-stage partial nitrification-denitrification and anammox process for nitrogen removal in vacuum collected toilet wastewater at ambient temperature. Environ. Res. 2024, 262, 119917. [Google Scholar] [CrossRef]
  8. Li, Y.; Wang, Y.; Wan, D.; Li, B.; Zhang, P.; Wang, H. Pilot-scale application of sulfur-limestone autotrophic denitrification biofilter for municipal tailwater treatment: Performance and microbial community structure. Bioresour. Technol. 2020, 300, 122682. [Google Scholar] [CrossRef]
  9. Yao, S.; Ni, J.; Ma, T.; Li, C. Heterotrophic nitrification and aerobic denitrification at low temperature by a newly isolated bacterium, Acinetobacter sp. HA2. Bioresour. Technol. 2013, 139, 80–86. [Google Scholar] [CrossRef]
  10. Strous, M.; Pelletier, E.; Mangenot, S.; Rattei, T.; Lehner, A.; Taylor, M.W.; Horn, M.; Daims, H.; Bartol-Mavel, D.; Wincker, P.; et al. Deciphering the evolution and metabolism of an anammox bacterium from a community genome. Nature 2006, 440, 790–794. [Google Scholar] [CrossRef] [PubMed]
  11. Hoover, N.L.; Bhandari, A.; Soupir, M.L.; Moorman, T.B. Woodchip Denitrification Bioreactors: Impact of Temperature and Hydraulic Retention Time on Nitrate Removal. J. Environ. Qual. 2016, 45, 803–812. [Google Scholar] [CrossRef]
  12. Ge, S.; Peng, Y.; Wang, S.; Lu, C.; Xu, C.; Zhu, Y. Nitrite accumulation under constant temperature in anoxic denitrification process: The effects of carbon sources and COD/NO3-N. Bioresour. Technol. 2012, 114, 137–143. [Google Scholar] [CrossRef]
  13. Mohan, T.V.K.; Nancharaiah, Y.V.; Venugopalan, V.P.; Sai, P.M.S. Effect of C/N ratio on denitrification of high-strength nitrate wastewater in anoxic granular sludge sequencing batch reactors. Ecol. Eng. 2016, 91, 441–448. [Google Scholar] [CrossRef]
  14. Fan, Y.; Zhang, M.; Li, B.; Cheng, J.; Wu, J.; He, C. Nitrogen degradation performance and microbial dynamic analysis for the efficient combination of partial denitrification and anammox (PD/A) process. J. Environ. Chem. Eng. 2024, 12, 112002. [Google Scholar] [CrossRef]
  15. Du, R.; Peng, Y.; Cao, S.; Li, B.; Wang, S.; Niu, M. Mechanisms and microbial structure of partial denitrification with high nitrite accumulation. Appl. Microbiol. Biotechnol. 2016, 100, 2011–2021. [Google Scholar] [CrossRef]
  16. Gong, L.; Huo, M.; Yang, Q.; Li, J.; Ma, B.; Zhu, R.; Wang, S.; Peng, Y. Performance of heterotrophic partial denitrification under feast-famine condition of electron donor: A case study using acetate as external carbon source. Bioresour. Technol. 2013, 133, 263–269. [Google Scholar] [CrossRef]
  17. Im, H.; Jeong, S.; Kim, H.; Yoon, S.; Yu, J.; Ni, S.-Q.; Chung, J.; Lee, T. Mainstream application of the partial denitrification-anammox process for carbon-neutral wastewater treatment: A review. J. Water Process Eng. 2025, 72, 107558. [Google Scholar] [CrossRef]
  18. Liu, Q.; Peng, Y.; Zhao, Y.; Zhao, Q.; Li, X.; Zhang, Q.; Sui, J.; Wang, C.; Li, J. Excellent anammox performance driven by stable partial denitrification when encountering seasonal decreasing temperature. Bioresour. Technol. 2022, 364, 128041. [Google Scholar] [CrossRef] [PubMed]
  19. Zhang, M.; Liu, J.; Wang, D.; Lu, M.; Fan, Y.; Ji, J.; Wu, J. Combined effects of carbon source and C/N ratio on the partial denitrification performance: Nitrite accumulation, denitrification kinetic and microbial transition. J. Environ. Chem. Eng. 2024, 12, 113343. [Google Scholar] [CrossRef]
  20. Du, R.; Cao, S.; Li, B.; Niu, M.; Wang, S.; Peng, Y. Performance and microbial community analysis of a novel DEAMOX based on partial-denitrification and anammox treating ammonia and nitrate wastewaters. Water Res. 2017, 108, 46–56. [Google Scholar] [CrossRef] [PubMed]
  21. Zhang, M.; Tan, Y.; Fan, Y.; Gao, J.; Liu, Y.; Lv, X.; Ge, L.; Wu, J. Nitrite accumulation, denitrification kinetic and microbial evolution in the partial denitrification process: The combined effects of carbon source and nitrate concentration. Bioresour. Technol. 2022, 361, 127604. [Google Scholar] [CrossRef]
  22. AWWA. Standard Methods for the Examination of Water and Wastewater, 21st ed.; American Water Works Association: Denver, CO, USA, 2005. [Google Scholar]
  23. Wu, X.; Chen, Y.; Liu, H.; Ma, J.; Dang, H. Characteristics of NO2−-N accumulation in partial denitrification during granular sludge formation. Biochem. Eng. J. 2023, 194, 108817. [Google Scholar] [CrossRef]
  24. Zhang, M.; Liu, J.; Liang, J.; Fan, Y.; Gu, X.; Wu, J. Response of nitrite accumulation, sludge characteristic and microbial transition to carbon source during the partial denitrification (PD) process. Sci. Total Environ. 2023, 894, 165043. [Google Scholar] [CrossRef] [PubMed]
  25. Li, W.; Li, X.; Li, J.; Gao, R.; Kao, C.; Zhang, Q.; Hou, X.; Peng, Y. Improved nitrogen removal performance by enhanced denitratation/anammox as decreasing temperature for municipal wastewater treatment. Resour. Conserv. Recycl. 2023, 190, 106869. [Google Scholar] [CrossRef]
  26. Gao, R.; Peng, Y.; Li, J.; Liu, Y.; Deng, L.; Li, W.; Kao, C. Mainstream partial denitrification-anammox (PD/A) for municipal sewage treatment from moderate to low temperature: Reactor performance and bacterial structure. Sci. Total Environ. 2022, 806, 150267. [Google Scholar] [CrossRef]
  27. Li, W.; Zheng, P.; Guo, J.; Ji, J.Y.; Zhang, M.; Zhang, Z.H.; Zhan, E.C.; Abbas, G. Characteristics of self-alkalization in high-rate denitrifying automatic circulation (DAC) reactor fed with methanol and sodium acetate. Bioresour. Technol. 2014, 154, 44–50. [Google Scholar] [CrossRef]
  28. Zhang, M.; Tan, Y.; Fan, Y.; Wu, J.; Yu, L. Insights into nitrite accumulation and microbial structure in partial denitrification (PD) process by the combining regulation of C/N ratio and nitrate concentration. J. Environ. Chem. Eng. 2023, 11, 109891. [Google Scholar] [CrossRef]
  29. Zhang, M.; Gao, J.; Liu, Q.; Fan, Y.; Zhu, C.; Liu, Y.; He, C.; Wu, J. Nitrite accumulation and microbial behavior by seeding denitrifying phosphorus removal sludge for partial denitrification (PD): The effect of COD/NO3− ratio. Bioresour. Technol. 2021, 323, 124524. [Google Scholar] [CrossRef]
  30. Cao, S.; Li, B.; Du, R.; Ren, N.; Peng, Y. Nitrite production in a partial denitrifying upflow sludge bed (USB) reactor equipped with gas automatic circulation (GAC). Water Res. 2016, 90, 309–316. [Google Scholar] [CrossRef]
  31. Le, T.; Peng, B.; Su, C.; Massoudieh, A.; Torrents, A.; Al-Omari, A.; Murthy, S.; Wett, B.; Chandran, K.; DeBarbadillo, C. Impact of carbon source and COD/N on the concurrent operation of partial denitrification and anammox. Water Environ. Res. 2019, 91, 185–197. [Google Scholar] [CrossRef]
  32. Park, G.; Takekawa, M.; Soda, S.; Ike, M.; Furukawa, K. Temperature dependence of nitrogen removal activity by anammox bacteria enriched at low temperatures. J. Biosci. Bioeng. 2017, 123, 505–511. [Google Scholar] [CrossRef]
  33. Shen, Q.; Ji, F.; Wei, J.; Fang, D.; Zhang, Q.; Jiang, L.; Cai, A.; Kuang, L. The influence mechanism of temperature on solid phase denitrification based on denitrification performance, carbon balance, and microbial analysis. Sci. Total Environ. 2020, 732, 139333. [Google Scholar] [CrossRef]
  34. Kotrba, P.; Inui, M.; Yukawa, H. Bacterial phosphotransferase system (PTS) in carbohydrate uptake and control of carbon metabolism. J. Biosci. Bioeng. 2001, 92, 502–517. [Google Scholar] [CrossRef] [PubMed]
  35. Ji, J.; Zhao, Y.; Wu, G.; Hu, F.; Yang, H.; Bai, Z.; Jin, B.; Yang, X. Responses of endogenous partial denitrification process to acetate and propionate as carbon sources: Nitrite accumulation performance, microbial community dynamic changes, and metagenomic insights. Water Res. 2025, 268, 122680. [Google Scholar] [CrossRef] [PubMed]
  36. Yuan, Y.; Huang, Y.; Deng, H.-P.; Sheng, X.-M.; Pan, Y.; Li, X. Effect of C/N Ratio on Nitrite Accumulation During Denitrification Process. Huanjing Kexue 2013, 34, 1416–1420. [Google Scholar]
  37. Takeda, P.Y.; Paula, C.T.; Borges, A.d.V.; Shibata, A.E.; Grangeiro, L.C.; Damianovic, M.H.R.Z. A critical review of the mainstream anammox-based processes in warm climate regions: Potential, performance, and control strategies. J. Environ. Chem. Eng. 2024, 12, 113691. [Google Scholar] [CrossRef]
  38. Zhang, L.; Hao, S.; Wang, Y.; Lan, S.; Dou, Q.; Peng, Y. Rapid start-up strategy of partial denitrification and microbially driven mechanism of nitrite accumulation mediated by dissolved organic matter. Bioresour. Technol. 2021, 340, 125663. [Google Scholar] [CrossRef] [PubMed]
  39. Peng, Z.; Lou, T.; Jiang, K.; Niu, N.; Wang, J.; Liu, A. Characteristics of nutrients removal under partial denitrification initiated by different initial nitrate concentration. Bioprocess Biosyst. Eng. 2021, 44, 2051–2059. [Google Scholar] [CrossRef]
  40. Fu, X.; Hou, R.; Yang, P.; Qian, S.; Feng, Z.; Chen, Z.; Wang, F.; Yuan, R.; Chen, H.; Zhou, B. Application of external carbon source in heterotrophic denitrification of domestic sewage: A review. Sci. Total Environ. 2022, 817, 153061. [Google Scholar] [CrossRef]
  41. Xu, Z.S.; Dai, X.H.; Chai, X.L. Effect of different carbon sources on denitrification performance, microbial community structure and denitrification genes. Sci. Total Environ. 2018, 634, 195–204. [Google Scholar] [CrossRef]
  42. Du, R.; Cao, S.; Peng, Y.; Zhang, H.; Wang, S. Combined Partial Denitrification (PD)-Anammox: A method for high nitrate wastewater treatment. Environ. Int. 2019, 126, 707–716. [Google Scholar] [CrossRef]
  43. Zhang, L.; Huang, X.Y.; Zhou, J.Z.; Ju, F. Active predation, phylogenetic diversity, and global prevalence of myxobacteria in wastewater treatment plants. ISME J. 2023, 17, 671–681. [Google Scholar] [CrossRef]
  44. He, Q.L.; Song, Q.; Zhang, S.L.; Zhang, W.; Wang, H.Y. 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]
  45. Qian, W.; Ma, B.; Li, X.; Zhang, Q.; Peng, Y. Long-term effect of pH on denitrification: High pH benefits achieving partial-denitrification. Bioresour. Technol. 2019, 278, 444–449. [Google Scholar] [CrossRef]
  46. Králová, S. Role of fatty acids in cold adaptation of Antarctic psychrophilic Flavobacterium spp. Syst. Appl. Microbiol. 2017, 40, 329–333. [Google Scholar] [CrossRef]
  47. Chen, K.; Zhang, L.; Sun, S.; Li, J.; Jia, T.; Peng, Y. In situ enrichment of anammox bacteria in anoxic biofilms are possible due to the stable and long-term accumulation of nitrite during denitrification. Bioresour. Technol. 2020, 300, 122668. [Google Scholar] [CrossRef]
  48. Zhang, M.; Li, B.; Wang, D.; You, Y.; Fan, Y.; Wu, J.; Lv, X. Nitrite production mechanism and microbial evolution characteristic influenced by pH during partial denitrification (PD) process. J. Environ. Chem. Eng. 2023, 11, 111451. [Google Scholar] [CrossRef]
  49. Zhang, M.; Wang, Y.; Fan, Y.; Liu, Y.; Yu, M.; He, C.; Wu, J. Bioaugmentation of low C/N ratio wastewater: Effect of acetate and propionate on nutrient removal, substrate transformation, and microbial community behavior. Bioresour. Technol. 2020, 306, 122465. [Google Scholar] [CrossRef] [PubMed]
  50. Zhen, X.; Luo, M.; Dong, H.; Fang, L.; Wang, W.; Feng, L.; Yu, Q. Analysis of enzyme activity and microbial community structure changes in the anaerobic digestion process of cattle manure at sub-mesophilic temperatures. Green Process. Synth. 2021, 10, 644–657. [Google Scholar] [CrossRef]
  51. Liao, R.; Miao, Y.; Li, J.; Li, Y.; Wang, Z.; Du, J.; Li, Y.; Li, A.; Shen, H. Temperature dependence of denitrification microbial communities and functional genes in an expanded granular sludge bed reactor treating nitrate-rich wastewater. RSC Adv. 2018, 8, 42087–42094. [Google Scholar] [CrossRef]
  52. Wang, W.; Yan, Y.; Song, C.; Pan, M.; Wang, Y. The microbial community structure change of an anaerobic ammonia oxidation reactor in response to decreasing temperatures. Environ. Sci. Pollut. Res. Int. 2018, 25, 35330–35341. [Google Scholar] [CrossRef] [PubMed]
  53. Du, R.; Cao, S.; Niu, M.; Li, B.; Wang, S.; Peng, Y. Performance of partial-denitrification process providing nitrite for anammox in sequencing batch reactor (SBR) and upflow sludge blanket (USB) reactor. Int. Biodeterior. Biodegrad. 2017, 122, 38–46. [Google Scholar] [CrossRef]
  54. Du, R.; Cao, S.; Wang, S.; Niu, M.; Peng, Y. Performance of partial denitrification (PD)-ANAMMOX process in simultaneously treating nitrate and low C/N domestic wastewater at low temperature. Bioresour. Technol. 2016, 219, 420–429. [Google Scholar] [CrossRef] [PubMed]
  55. Matthew, B.; Chenghua, L.; Luke, P.; Jeffrey, S.; Michael, B.; Kartik, C. Optimization of partial denitrification to maximize nitrite production using glycerol as an external carbon source—Impact of influent COD:N ratio. Proc. Water Environ. Fed. 2017, 2017, 1356–1360. Available online: https://www.researchgate.net/publication/321336954_Optimization_of_partial_denitrification_to_maximize_nitrite_production_using_glycerol_as_an_external_carbon_source_-_impact_of_influent_CODN_ratio (accessed on 12 July 2025).
  56. Nancharaiah, Y.V.; Venugopalan, V.P. Denitrification of synthetic concentrated nitrate wastes by aerobic granular sludge under anoxic conditions. Chemosphere 2011, 85, 683–688. [Google Scholar] [CrossRef]
  57. Sun, H.; Yang, Q.; Peng, Y.; Shi, X.; Wang, S.; Zhang, S. Nitrite Accumulation during the Denitrification Process in SBR for the Treatment of Pre-treated Landfill Leachate. Chin. J. Chem. Eng. 2009, 17, 1027–1031. [Google Scholar] [CrossRef]
  58. Cao, S.; Peng, Y.; Du, R.; Zhang, H. Characterization of partial-denitrification (PD) granular sludge producing nitrite: Effect of loading rates and particle size. Sci. Total Environ. 2019, 671, 510–518. [Google Scholar] [CrossRef]
Water 17 02583 g001aWater 17 02583 g001b
Figure 1. Experimental device (a) and operational mode (b) of the PD-SBR system.
Figure 1. Experimental device (a) and operational mode (b) of the PD-SBR system.
Water 17 02583 g001aWater 17 02583 g001b
Water 17 02583 g002
Figure 2. Variations in substrate concentration (a–e), NTR, and NRE (f) in different reactors.
Figure 2. Variations in substrate concentration (a–e), NTR, and NRE (f) in different reactors.
Water 17 02583 g002
Water 17 02583 g003aWater 17 02583 g003bWater 17 02583 g003c
Figure 3. Variations in COD (a,b), NO2−-N (c,d), NO3−-N (e,f), TN (g,h), ReTN (i,j) in the typical cycles; carbon source consumption (k) and correlation analysis (l) linked with the C/N ratio and NO3−-N concentration.
Figure 3. Variations in COD (a,b), NO2−-N (c,d), NO3−-N (e,f), TN (g,h), ReTN (i,j) in the typical cycles; carbon source consumption (k) and correlation analysis (l) linked with the C/N ratio and NO3−-N concentration.
Water 17 02583 g003aWater 17 02583 g003bWater 17 02583 g003c
Water 17 02583 g004
Figure 4. Microbial diversity analysis based on OTUs: (a) rank–abundance curves; (b) hierarchical clustering tree; (c): Venn diagram; (d) PCoA analysis.
Figure 4. Microbial diversity analysis based on OTUs: (a) rank–abundance curves; (b) hierarchical clustering tree; (c): Venn diagram; (d) PCoA analysis.
Water 17 02583 g004
Water 17 02583 g005
Figure 5. Microbial taxonomic compositions at the (a) phylum and (b) genus level.
Figure 5. Microbial taxonomic compositions at the (a) phylum and (b) genus level.
Water 17 02583 g005
Water 17 02583 g006
Figure 6. Mechanism analysis linked with (a) [51,52] temperature and (b) potential application of PD/A process.
Figure 6. Mechanism analysis linked with (a) [51,52] temperature and (b) potential application of PD/A process.
Water 17 02583 g006
Table 1. Influent quality characteristics.
Table 1. Influent quality characteristics.
SystemsC/NInfluent NO3−-N
(mg/L)		Influent COD
(mg/L)		NTR A
(%)		NRE A
(%)		Other Parameters
R400.840 ± 132 ± 80.508.63Operation cycle: 270 min
Cycle: 120
VSS: 2500 ± 100 mg/L
SRT: 25 d
Temperature: 10 ± 2 °C–5 ± 2 °C
1.540 ± 260 ± 727.7931.10
2.540 ± 1100 ± 531.5440.15
3.540 ± 1140 ± 952.8754.96
4.540 ± 2180 ± 848.8745.67
R800.880 ± 164 ± 619.159.16
1.580 ± 2120 ± 746.0024.68
2.580 ± 1200 ± 657.1251.19
3.580 ± 1280 ± 860.4255.75
4.580 ± 2360 ± 956.9840.55
Note: A: The average values during the stable operation.
Table 2. Comparisons of microbial diversity index.
Table 2. Comparisons of microbial diversity index.
SamplesSequenceOTUsACEChaoShannonSimpsonCoverage
SS50,3471879208420526.090.0060.993
C/N = 0.860,4721376175217274.880.0400.991
C/N = 1.549,5511340169316664.870.0380.992
C/N = 2.546,142932129612763.810.0950.992
C/N = 3.550,8251083146914454.290.0570.992
C/N = 4.544,032958156413703.840.0760.992
Table 3. Comparisons of PD performance under different C/N ratios, NO3−-N concentrations, and temperatures.
Table 3. Comparisons of PD performance under different C/N ratios, NO3−-N concentrations, and temperatures.
ReactorsWorking Volume (L)Carbon SourceC/N RatioInfluent NO3−-N
(mg/L)		Temperature
(°C)		NTR
(%)		References
SBR10Acetate2.541.622 ± 271.7[16]
SBR5Acetate2.530–40023.6–28.883.3[53]
SBR5Acetate3.02516–28~80[15]
SBR5Acetate3.05010.6–18.3 57.5[54]
SBR12Glycerol2.5–2.810020–2372.5, C/N = 2.6[55]
SBR10Acetate2.5–4.5803–1276.79, C/N = 2.5
75.57, C/N = 3.5
68.15, C/N = 4.5		This study
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Cai, Y.; Song, Y.; Yin, T.; Zhang, M.; Ji, J. Combined Effects of Carbon-to-Nitrogen (C/N) Ratio and Nitrate (NO3−-N) Concentration on Partial Denitrification (PD) Performance at Low Temperature: Substrate Variation, Nitrite Accumulation, and Microbial Transformation. Water 2025, 17, 2583. https://doi.org/10.3390/w17172583

AMA Style

Cai Y, Song Y, Yin T, Zhang M, Ji J. Combined Effects of Carbon-to-Nitrogen (C/N) Ratio and Nitrate (NO3−-N) Concentration on Partial Denitrification (PD) Performance at Low Temperature: Substrate Variation, Nitrite Accumulation, and Microbial Transformation. Water. 2025; 17(17):2583. https://doi.org/10.3390/w17172583

Chicago/Turabian Style

Cai, Ying, Yujun Song, Tangbing Yin, Miao Zhang, and Junjie Ji. 2025. "Combined Effects of Carbon-to-Nitrogen (C/N) Ratio and Nitrate (NO3−-N) Concentration on Partial Denitrification (PD) Performance at Low Temperature: Substrate Variation, Nitrite Accumulation, and Microbial Transformation" Water 17, no. 17: 2583. https://doi.org/10.3390/w17172583

APA Style

Cai, Y., Song, Y., Yin, T., Zhang, M., & Ji, J. (2025). Combined Effects of Carbon-to-Nitrogen (C/N) Ratio and Nitrate (NO3−-N) Concentration on Partial Denitrification (PD) Performance at Low Temperature: Substrate Variation, Nitrite Accumulation, and Microbial Transformation. Water, 17(17), 2583. https://doi.org/10.3390/w17172583

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop