The bioenhanced effect of biochar-based aerobic denitrifying bacteria on a sequencing batch reactor under different stress conditions

Xu, P., Song, J., Yao, H., Tang, X., Qian, F., Lin, T., and Yuan, X. (2026). "The bioenhanced effect of biochar-based aerobic denitrifying bacteria on a sequencing batch reactor under different stress conditions," BioResources 21(1), 1065–1083.

Abstract

Biochar-based aerobic denitrifying functional bacteria (BADB) have the advantages of excellent biochar adsorption performance and high nitrogen removal efficiency. In this study, a sequencing batch reactor (SBR) system was employed to explore the impacts of various stress conditions on the pollutant removal efficiency and metabolic pathways of BADB. Additionally, the adaptation mechanisms and response patterns of functional bacteria under different stress conditions were revealed. The structure of the microbial community was analyzed through high-throughput sequencing. The research results indicated that aerobic denitrification bacteria had good growth and nitrate removal performance under various conditions. Aeration rate exhibited positive relationship with denitrification efficiency, and the effect was enhanced when the ion concentration increased. Carbon source type significantly influenced the denitrification efficiency of functional bacteria, among which sodium acetate showed the best effect. Within the appropriate C/N ratio range, greater amounts of carbon led to higher denitrification efficacies of functional bacteria. Sequencing results revealed the key role of Brachymonas in organic degradation and denitrification process, with a percentage of 13.9% in the system. This study can provide a reference for the optimization and utilization of biochar-based aerobic denitrification technology, which is of great significance for improving the quality of water environment.

Download PDF

Full Article

The Bioenhanced Effect of Biochar-Based Aerobic Denitrifying Bacteria on a Sequencing Batch Reactor under Different Stress Conditions

Peng Xu,^a,b,c Jianyang Song ,^b,c,* Huimin Yao,^b,c, Xiaowen Tang,^d Fangyi Qian,^d Tongtong Lin,^d and Xinfang Yuan ^b,c

DOI: 10.15376/biores.21.1.1065-1083

Keywords: Biochar; Aerobic denitrification; Immobilization; Biological denitrification; Denitrification efficiency

Contact information: a: School of Materials and Chemical Engineering, Zhengzhou University of Light Industry, Zhengzhou 450001, China; b: Nanyang Key Laboratory of Water Pollution Control and Solid Waste Resource, Nanyang Institute of Technology, Nanyang 473004, China; c: School of Civil Engineering, Nanyang Institute of Technology, Nanyang 473004, China; d: Henan Key Laboratory of Industrial Microbial Resources and Fermentation Technology, Nanyang Institute of Technology, Nanyang 473004, China;*Corresponding author: songjianyang66@163.com

Graphical Abstract

INTRODUCTION

With agricultural and industrial development, eutrophication of water bodies by nitrogenous pollutants has become the focus of global environmental management. The traditional biological method of nitrogen removal relies on “nitrification – denitrification”, which needs to be carried out step by step in anoxic and aerobic environments, and there are problems such as complicated process flow, high energy consumption, and limited nitrogen removal efficiency (Qiu et al. 2025). Heterotrophic Nitrification-Aerobic Denitrification (HN-AD) bacteria have transcended the conventional theoretical framework. Their distinct capacity for Simultaneous Nitrification and Denitrification (SND) offers a new direction for the innovation of wastewater denitrification technology (An et al. 2024). These strains can directly transform nitrite and nitrate into nitrogen gas under aerobic conditions. Not only does this shorten the denitrification pathway, but it also maintains the pH stability of the system through an alkalinity compensation mechanism, thereby significantly reducing the operational costs (Xiao et al. 2024).

HN-AD bacteria had demonstrated greater environmental adaptability in denitrification (Huang et al. 2020). To date, multiple HN-AD strains such as Pseudomonas, Halomonas, Bacillus, and Acinetobacter had been isolated from diverse environments (Song et al. 2021). These species mainly carry out the gradual reduction of nitrate to N₂ through a series of denitrification enzyme systems, such as Nitrate reductase (Nar), Nitrous oxide reductase (Nos), Nitrite reductase (Nir), Periplasmic nitrate reductase (Nap), and Nitric oxide reductase (Nor) (Zhu et al. 2020). N and C metabolism was found to be the foundation of all microbial cell metabolic processes involved in wastewater treatment through biological method (X. Yang et al. 2025). The biodegradabililty of the carbon source, its molecular weight, and its chemical structure could influence the activity of microbial enzymes, growth, metabolism, and N degradation (Lu et al. 2024). During nitrification, an appropriate carbon-nitrogen ratio (C/N) could markedly enhance the rate of nitrification (Zhao et al. 2017; Zhang et al. 2023). HN-AD bacteria exhibit a broad adaptability to varying C/N ratios (Bian et al. 2022; Hu et al. 2023). Dissolved oxygen (DO) is critical for both ammonia oxidation and denitrification. However, it may impede the growth and metabolic activities of anaerobic denitrifying bacteria (DNB) (Ji et al. 2023; Su et al. 2024). Notably, HN-AD bacteria could perform aerobic denitrification, with different strains requiring distinct optimal DO concentrations (Chen et al. 2019; Xia et al. 2020; Bian et al. 2022). Recent research has predominantly focused on individual purified strains, while studies on the denitrification effects and methods to enrich HN-AD bacteria within reactors remain scarce.

If the HN-AD bacteria were directly added to the biological system for better N removal, there will be problems such as easy loss, difficulty in enrichment, and the need for regular addition of functional strains. Additionally, multiple environmental stresses (e.g., pH fluctuations, heavy metal impacts, carbon scarcity, etc.) in the actual wastewater treatment system could also inhibit the activity of free strains, thus limiting their practical applications (Liu et al. 2024; Lu et al. 2024; Sethi et al. 2025). Immobilizing HN-AD bacteria onto carriers not only prevents microbial loss but also enhances resistance to adverse conditions such as low temperatures, low C/N ratios, and heavy metals, while facilitating recycling (Li et al. 2025). Carrier materials play a pivotal role in microbial immobilization. Yang et al. (2021) used macro-genomic technology to analyze the metabolic pathways and community structure of microbes in the solid-opposed nitrification system. They found that the use of natural materials or artificial synthesis biodegradable materials as carbon sources and biofilm carriers not only solved the problem of the amount of the traditional carbon source injection, but also provided a safe and stable survival environment for the denitrifying bacterial flora. In an earlier study (Song et al. 2023), immobilization of HN-AD bacteria screened in the waste leachate environment with sodium alginate (SA) and polyvinyl alcohol (PVA) as the implanting carriers and Artemisia argyi stem biochar as an adsorption carrier led to better biofortification.

Based on this, the present study employed SA and PVA as immobilization matrices, with Artemisia argyi stem biochar serving as the adsorbent support. These composite particles were used to immobilize the HN-AD bacteria. Their addition to the SBR reactor had the effects of constructing a biofortification system of BADB. The research focused on the mechanisms governing the influence of different stress conditions, such as aeration rate, C/N ratio, carbon source, etc. on the efficiency of their denitrification. A further goal was to make clear the critical value of the functional bacterial group’s stress tolerance, as well as to provide theoretical support for the biological fortification technology under the complex water quality conditions. The results of the study will promote the transition of aerobic denitrification technology from laboratory research to engineering application. The results also can have an important practical value for the deep treatment of high ammonia-nitrogen industrial waste waters.

EXPERIMENTAL

Preparation of Seed Sludge and Immobilized Functional Microbial Gel Spheres

This experiment used sludge from a sewage treatment plant sludge in Nanyang. Its sludge settling ratio, initial concentration, volatile sludge concentration, and other indexes were detected by using the procedures described in the Urban Construction Industry Standard of China (CJ/T 221-2005). After the sludge was recovered and left for 24 hours, the supernatant was excluded as the sludge used in this test reactor, and its sludge settling proportion at 30 min (SV30) was about 28.4%. Other sludge characteristics were as follows: mixed liquor suspended solids (MLSS): 4370 mg/L; Mixed liquor volatile suspended solids (MLVSS): 3550 mg/L; MLVSS/MLSS ratio: 0.81; and sludge volume index at 30 min (SVI): 65.0.

The detailed preparation method of the immobilized spheres with loaded microorganisms was shown in the earlier paper published by the group (J. Song et al. 2023), and the embedded bacterial strains were the bacteria screened in the activated sludge of the waste leachate biological treatment system by the previous personnel of this group.

Reactor Construction for Different Systems

Three identical SBR reactors were set up with specifications of 120 mm internal diameter, 400 mm height, 3.7 L effective volume, and 3.3 height-to-diameter (H/D) ratio. The reactors were numbered from left to right as 1#, 2#, and 3#, where 1# reactor was filled with activated sludge only, without gel spheres, 2# was filled with activated sludge and immobilized functional microorganisms gel spheres, and 3# was filled with activated sludge and unloaded functional microorganisms gel spheres. Activated sludge and unloaded functional microorganisms were added into the reactor.

The test used artificial water simulation of domestic sewage as the source of water intake. To ensure stable water quality, on-site preparation was undertaken. The chemical oxygen demand (COD) of prepared water was provided separately by anhydrous sodium acetate (NaAc), total phosphorus (TP) was provided separately by potassium dihydrogen phosphate (KH₂PO₄), and ammonia nitrogen (NH₄⁺-N) was provided separately by ammonium chloride (NH₄Cl) alone. Influent pH was adjusted to the neutral level. The pH was no longer controlled during the operating phase of the reactor, and the water temperature was room temperature. At the same time, a solution of trace elements (1 mL/L) was added during the preparation of artificially simulated wastewater to provide necessary trace elements for microbial reproduction and growth. The composition of the wastewater used for artificial preparation and the added trace elements were as shown in Table 1.

At the beginning of the experiment, about 400 mL of thickened activated sludge was injected into each reactor, and 66 g of immobilized functional microorganisms and unloaded functional bacteria were injected into reactors 2# and 3#, respectively. Reactor operation was conducted in the same A/O/A mode, with each cycle set at 8 h and a hydraulic retention time (HRT) of about 16 h. Three cycles were operated per day, with the following cycle composition: influent time of 5 min, anaerobic phase of 155 min, aerobic phase of 160 min, anoxic phase of 125 min, settling time of 30 min, and anaerobic phase of 30 min. In the anaerobic stage, no stirring and aeration were provided to control the corresponding DO below 0.20 mg/L. In the aerobic stage, the aeration was carried out by the air pump, and the mechanical stirrer was also started to work to keep DO values above 2.0 mg/L. In the anoxic stage, aeration stopped, and the stirring kept DO concentrations within 0.20~0.50 mg/L. The system was regularly drained during operation, and the water temperature was indoor temperature; the actual water temperature was about 20±2 °C.

Table 1. Artificial Water Quality and Trace Element Composition of Water Distribution

Reactor Construction for Different Conditions of Operation

Influence of aeration rate on the decontamination performance of reaction system

To explore the impacts of varying DO levels on the decontamination effect of immobilized functional microbial gel spheres, a control group 4# and a reactor 5# with changed aeration rate were set up with the same influent as in Table 1. The test was carried out with the sludge that had been matured and operated stably for more than 15 d in 2#. At the beginning of the test, 1 L of sludge and 90 g of immobilized functional microorganism gel spheres were added to each reactor. After the system was stabilized, the operation mode was kept unchanged, and the aeration rate of reactor 5 was set to 3 L/min, and that of reactor 4 was kept at 2 L/min.

Impact of C/N on decontamination in the reaction system

An SBR reactor identical to 2.2 was utilized, noted as 6#. The previous operation mode and water distribution were kept the same as 4#. For the purpose of researching the impact different C/N on the decontamination effect of immobilized functional microbial gel spheres, after the system operation was stabilized, the COD of the water distribution in the 6# reactor was changed to 240 mg/L, so that the C/N of the system was 8:1, and the rest of the conditions were kept unchanged, and the subsequent decontamination effect was observed.

Influence of different sources of carbon on the decontamination performance of reaction system

An SBR reactor identical to that of 2.2, noted as 7#, was utilized. To study the impact of C source on the decontamination of immobilized functional microbial gel spheres, all other conditions were kept constant, and only the carbon source was changed to glucose in reactor 7#.

Measurement and Analysis

According to the standard method for determination of COD, TN, NH₄⁺-N, NO₃^–-N, NO₂^–-N, MLVSS, MLSS, and SVI₃₀ (Apha, 2012). The pH was monitored through a pH meter (pHS-25, Shanghai Leici Instrument Factory, China).

All statistical analyses were performed using SPSS version 15.0. Pair-sample t-tests were used to assess whether the water quality was significantly different between samples based on p-values. A p-value of <0.05 was considered significant.

High-throughput Sequencing

Appropriate amounts of sludge were extracted as test samples at the end of each operation cycle. The sludge samples obtained from 1#, 2#, 3#, 4#, 5#, 6#, and 7# were designated as S1, S2, S3, S4, S5, S6, and S7, respectively. After sampling, they were immediately frozen for preservation and entrusted to Sangon Biotech Co., Ltd. (Shanghai, China) for Illumina MiSeq sequencing. Using the genomic DNA of the above samples as templates, PCR amplification the V3-V4 sections of 16S rRNA genes of bacteria were amplified with primers B341F and B785R. Quality control of high-throughput sequencing sequences was conducted using Cutadapt (v1.9.1), Prinseq (v0.20.4), and Flash (1.2.3) software. The 97% similar sequences were collected into operational taxonomic units (OTUs). Using the Silva database and Mothur (1.30.1) software, the composition of microbial population in each sample was statistically analyzed at the species level. In addition, coverage and alpha diversity indices of microbes in the individual samples were calculated, namely, the Simpson, Shannon, ACE, and Chao1 indices.

RESULTS AND DISCUSSION

Effluent Decontamination by Different System Reactors

Previous studies had confirmed the specific role of biochar as a carrier (J. Song et al. 2023). Figure 1 illustrates the pollutant removal performance of different reactor systems (p < 0.05). The COD removal performance of Reactor 2# remained at approximately 94% after stabilization (p < 0.05). In contrast to the experimental data for Reactor 1# and 3#, the degradation of organic matter in Reactor 2# was maintained at a relatively elevated level. It was concluded that the loaded microorganisms played a significant role in the reaction process. The functional bacteria acclimated to the sewage environment during this period, and their activity increased rapidly. The removal performance was enhanced and remained stable during operation (Fig. 1a). Based on the experimental data from Reactor 1# and 3#, although the activated sludge possessed a certain COD removal capacity, it was unstable and susceptible to environmental factors. In contrast, the immobilized functional microorganism enhancement system demonstrated relatively robust resistance to impact loading. This was attributed to the highly porous structure of the biochar, which provided excellent growth sites for microorganisms. Thus, the biochar exhibited a favorable adsorption effect on COD, and microorganisms accelerated its degradation. Additionally, during the operation of Reactor 2# and 3#, the effluent COD initially increased slightly, and then it gradually decreased. The reason for the initial increase was likely that the gel spheres, which were initially tested in a shaker, were subjected to their first operational trial in the reactor. Their mechanical strength was insufficient to withstand the shear force generated by the reactor’s mixing device, resulting in the fracture and subsequent washout of a portion of the gel spheres. This disrupted the system within the reactor. The subsequent decline in COD might have been due to the remaining intact gel spheres continuing degradation after the fractured ones were discharged. After approximately four weeks of operation, COD removal in the reactor stabilized essentially. The COD removal effect of Reactor 2# was optimal, indicating that the immobilized functional microbial gel spheres could effectively eliminate COD.

Fig. 1. Variation of pollutant removal in reaction systems 1#, 2#, and 3# with operating time: (a) COD removal; (b) NH₄⁺-N removal; (c) TN removal; (d) NO₃^–-N and NO₂^–-N changes. The three systems were: 1# (activated sludge only), 2# (activated sludge with immobilized functional microorganism gel spheres), and 3# (activated sludge with unloaded gel spheres).

The NH₄⁺-N decontamination performances of the system were stable at 87% (1#), 96% (2#), and 89% (3#) throughout the whole reaction stage (p < 0.05). This initially indicated that the immobilized gel spheres loaded with the dominant bacterial strains improved NH₄⁺-N removal in the system to a degree, which can be attributed to nitrification. The differences in NO₃^–-N and NO₂^–-N contents are presented in Fig. 1d. Combined with Fig. 1b, it could be observed that nitrification was stronger in reactor 2# than in 1# and 3#, and the NH₄⁺-N removal in reactor 3# was also stronger than that in 1#. It was hypothesized that the reason for this might be that the biochar pores supported microbial growth and enhanced NH₄⁺-N removal (Zhou et al. 2017). Moreover, it had been pointed out that the carbon-rich biochar may also serve as a C source to promote denitrification (Zhou et al. 2017). The nitrite and nitrate contents in the effluent from reactor start-up to the system stabilization were low. In combination with TN removal (Fig. 1c), these results showed that the TN removal performance was unstable in the initial stage due to the lack of microbial adaptation to the environment. The removal performance increased significantly in the middle and late stages of the experiment, which might be mainly due to alterations in the structure of microbial population and the evolution of nitrifying bacterial community structure (D. Chen et al. 2023). After completion of reaction, nitrite and nitrate levels decreased under denitrification. TN removal stabilized at approximately 84% (1#), 94% (2#), and 87% (3#), respectively (p < 0.05). Despite the fluctuations in the influent TN concentration, the TN removal rate generally presented an upward trend. Effluent TN slightly increased at the outset. It was noteworthy that the main cause of TN fluctuation was related to NO₃^–-N and NH₄⁺-N, which may be because of the reductions in C/N and DO (Huang et al. 2022). However, as the operation time increased, effluent TN level gradually declined, and the TN removal performance in 1# and 3# at the end of the reaction could reach more than 85%. TN removal in the 2# reactor with the immobilized gel ball of loaded bacteria was more than 95% (p < 0.05). The results demonstrated that, compared with the activated sludge method alone, the combined immobilized functional microbial gel ball possessed a more efficient nitrogen removal capacity.

Effect of Different Aeration Rates on Biological Systems Loaded with Microbially Immobilized Spheres

To investigate the influence of aeration rate on the decontamination efficacy of biogel balls, the other conditions were kept the same and the aeration rate was varied. TN and NH₄⁺-N removal performances are given in Fig. 2(b, c). When the C/N of influent was 15:1, NH₄⁺-N removal efficacy (NRE) of system reached about 90%, with a maximum removal of 99.2% at an aeration rate of 3 L/min (p < 0.05). The results showed that the appropriate increase of the aeration in different environments could improve the NRE of immobilized gel spheres. NRE comparison of different experimental groups showed significantly positive effects of aeration on nitration process, DO concentration, and nitrification (Jin et al. 2019). There was adequate DO in the 5# reactor to promote both nitrification and denitrification. The supply of external oxygen supplementation (particularly at high C/N levels) boosted NRE because, at greater ratios of C/N in influent, organic matter contended with autotrophic nitrifying microbes for DO, while heterotrophic microbial reproduction restrained the growth of autotrophic nitrifying microorganisms (Peng et al. 2025). This might be the cause of the decline in the NH₄⁺-N removal rate under a high carbon-to-nitrogen ratio. In HN-AD, NH₄⁺ first by ammonia monooxygenase (AMO), ammonia nitrogen was oxidized to NH₂OH. Hydroxylamine oxidoreductase (HAO) catalyzed the transformation of hydroxylamine into NO₂^–, which was then converted to NO₃^– by nitrite oxidoreductase. Reduction of nitrite and nitrate is crucial for denitrification. During the denitrification process, both NO₃^– and O₂ could serve as the ultimate electron acceptors, and O₂ was consumed when NO₃^– was eliminated. This suggested that HN-AD bacteria may have relatively high demands for DO. The generation of NO₃^–-N and NO₂^–-N is presented in Fig. 2d. Compared with 4#, nitrification and denitrification in 5# reactor with a higher aeration rate were more rapid.

It was also observed that 5# with the same higher aeration rate was more effective in COD removal (Fig. 2a), presumably because the more environmentally adapted HN-AD bacteria proliferated faster, thus contributing to the more significant COD removal in reactor 5#. Another main reason is that, at high aeration rate, the DO in the reactor was sufficient to supply enough oxygen for organic matter oxidation, while there was still abundant oxygen for oxidation of NH₄⁺-N. Therefore, COD and NH₄⁺-N removal efficiencies were more significant at high aeration rate under this condition. These results indicated the selectivity of heterotrophic bacteria associated with organic matter removal and nitrification-related AOB for high DO. At both aeration rates, the system showed COD and nitrogen removal advantages for different DO environments, especially at slightly higher DO.

Fig. 2. Variation of pollutant removal in reaction system 4# and 5# with operating time: (a) COD removal; (b) NH₄⁺-N removal; (c) TN removal; (d) NO₃^–-N and NO₂^–-N change

Influence of Different C/N on the Biological System of Immobilized Spheres Loaded with Microorganisms

Carbon to nitrogen ratio as a key parameter that directly affects the efficiency and effectiveness of the denitrification process, where microorganisms require a C source as a donor of electrons for denitrification, thus reducing nitrate to nitrogen. Most studies have shown that a proper carbon to nitrogen ratio promotes the TN and ammonia removal and increases the rate of nitrification. Too high or too low a carbon to nitrogen ratio could reduce TN and ammonia removal, and when the C/N is low, it usually exhibits poor TN removal and denitrification capabilities (Hill and Khan 2008; Sha et al. 2024). However, when the C/N exceeds the ideal level, it results in slightly lower capacities of TN removal and ammonia oxidation (Hu et al. 2023). This experiment explored the treatment of wastewater by the reaction system at C/N of 15 and 8.

The TN and NH₄⁺-N removal effects, as well as nitrite and nitrate contents in the effluent are shown in Fig. 3 NH₄⁺-N removal was greatly affected by C/N, and the two reactors showed different NRE in the reaction stage. In the last stage, NRE at C/N 15 and 8 were 95.2% and 88.3% (p < 0.05), respectively. The extent of TN removal in the 4# reactor remained at a relatively high and stable level of about 94% (p < 0.05). Nitrate was non-accumulative, and denitrification was more thorough. TN removal in 6# system with low carbon and nitrogen ratio was lower than that of the 4# reaction system with high carbon and nitrogen ratio. After two weeks of operation, nitrate accumulation was more obvious, and the rate of TN removal fluctuated. Shi et al. (2024) showed that TN and NH₄⁺-N removal improved significantly with increasing carbon to nitrogen ratio, and that carbon supplementation enhanced both nitrification and denitrification. Functional pellet-loaded HN-AD bacteria could adapt to an extensive C/N range, while normal HN-AD bacteria need greater C/N levels than the autotrophic nitrifying bacteria (ANB) and had shown optimal carbon to nitrogen ratios of 8 to 15 in several studies. It was thus clear that high carbon to nitrogen ratios were more favorable to functional pellet-loaded systems. They were more conducive to denitrifying microbial proliferation, as well as to activity It could be seen that a high carbon to nitrogen ratio was more favorable to the functional pellet loading system and the proliferation and activity of denitrifying microorganisms.

In terms of COD removal (Fig. 3a), 4# and 6# were roughly close to each other, both reaching more than 90% (p < 0.05).

Fig. 3. Variation of pollutant removal in reaction system 4# and 6# with operating time: (a) COD removal; (b) NH₄⁺-N removal; (c) TN removal; (d) NO₃^–-N and NO₂^–-N change

Influence of C Sources on Immobilized Spheres with Microorganisms

To understand the influence of C source on decontamination of immobilized materials, the effluent indicators were measured during the reactor operation in the presence of different C sources. Carbon source has been found to be crucial for denitrifying bacteria as a source of electron and energy (M. Chen et al. 2023), and denitrifying bacteria are known to utilize organic carbon sources while denitrifying. The process of nitrification denitrification is a redox reaction, wherein the carbon source provides the required electrons and energy for microbial growth. The extent of bacterial growth varies with the type of C source, which affects the degree of nitrate reduction and accumulation of intermediates, and therefore can have a great influence on denitrification/nitrification rates (Lu et al. 2024). The glucose used as a carbon source easily caused the system to acidify, which lowered the local pH and impaired the activity of microorganisms involved in nitrogen metabolism, leading to a slower denitrification rate. In addition, NO₂^–accumulation was greater in presence of glucose as a C source. As shown in Fig. 4, COD was found to be rapidly utilized in the reactor in the presence of exogenous C sources (p < 0.05), indicating that the acetate and glucose were readily biodegradable (Sun and Li 2024). However, the reactors showed significant differences in denitrification performance, which was closely connected to the C metabolic pathway of the microbes. When the source of C was glucose, COD removal efficiency declined substantially and the pH value in the system gradually decreased from the initial 7.2 to 6.3 ± 0.2. This may be due to the acidic intermediates such as short-chain fatty acids (i.e., propionic acid, acetic acid) generated by glucose during microbial metabolism, which led to the acidification of the liquid phase (Huang et al. 2024).

Fig. 4. Variation of pollutant removal in reaction system 4# and 7# with operating time: (a) COD removal; (b) NH₄⁺-N removal; (c) TN removal; (d) NO₃^–-N and NO₂^–-N change

Analysis of the Dynamic Structure of Microbial Populations

Results of sequencing and alpha diversity analysis

The sequence data of sludge samples were analyzed and screened for quality. The partial results are shown in Table 3. The numbers of valid sequences in S1, S2, S3, S4, S5, S6, and S7 samples were 26284, 24519, 27325, 23147, 22392, 19055 and 22618, and the OTUs obtained at the 97% similarity level were 737, 729, 745, 709, 660, 649 and 600, respectively. The Coverage index was more than 0.99 for all samples. Simpson and Shannon indices represent the statistical homogeneity and diversity of microbial population, and Chao and ACE represent the richness of the microbial community structure.

Table 2. Sequencing Results and Diversity Indices of Species Diversity and Richness Index Analysis

Table 2 shows that the diversity of microorganisms in the three reactor samples (1#, 2#, and 3#) set up for the evaluation study of the treatment effect of different systems was higher than that of the reactor samples for the subsequent evaluation experiments of the different influencing factors. This may be due to the more homogeneous composition of the artificially dispensed water, and the microbial diversity of the 4#, 5#, 6#, and 7# reactors, which were used with the sludge of the reactor #2 as the initial sludge for the evaluation of the subsequent operation, was reduced. The diversity of microbes in the reactors with carriers was slightly greater compared to the control system, and the increase in aeration further improved the diversity of microbes within the system.

Structure of microbial populations

Relative abundance greater than 1% was considered as dominant phylum, and on this basis there were 11 dominant phylum in the three reactors in the research experiments of different systems. Among them the absolute dominant phylum was Proteobacteria with relative abundances of 27.7%, 45.0%, and 51.9%, respectively (Fig. 5A). Proteobacteria had been consistently found to be the most abundant phylum in the bioreactors because of its P and N removal potential (Liao et al. 2021). The average relative abundance of Bacteroidetes was greater than 10%. In addition, Firmicutes, Chloroflexi, Nitrospirae, Planctomycetes and Armatimonadetes were detected.

Table 3. List of Key Functional Bacteria Related to N Removal

Most denitrifying bacteria were classified as Ascomycota. These bacteria have been found to be crucial for denitrification (Karanasios et al. 2010), while the phylum Porphyromonas may also perform denitrifying functions in intermediate stages (Kartal et al. 2007). The phylum Nitrospirae is a group of Gram-negative bacteria, in which Nitrospirae spp. function as nitrifying bacteria to oxidize nitrite into nitrate. Nitrospirae abundance levels in control system S1 and carrier-only system S3 were 3.76% and 1.84%, respectively, while Nitrospirae were reduced to non-dominant in the S2 system loaded with synchronous nitrifying and denitrifying functional bacteria, which may be due to the fact that the functional bacteria loaded in S2 system had the ability to perform SND, and they partially replaced the function of Nitrospirae in terms of ecological niche, leading to the decrease in Nitrospirae‘s abundance.

At the level of class, 18 dominant classes were found in different systems, as shown in Fig. 5B. Many classes were prevalent in wastewater treatment systems, including Alpha, Delta-, and Betaproteobacteria as well as Clostridia, Bacteroidia, and Sphingobacteria. In comparison to S1, the abundance of Betaproteobacteria, Gammaproteobacteria, Clostridia, and norank_Candidatus_Saccharibacteria doubled in S2 and S3 systems with additional vectors and functional bacteria. In contrast, the relative abundance of the four orders Anaerolineae, Planctomycetia, Acidobacteria, and Nitrospira decreased by a factor of two.

Figure 5C shows the 25 dominant genera in different reactors. Among them, 10 genera of microorganisms, namely Zoogloea, Brachymonas, Acinetobacter, Clostridium_sensu_stricto, Gemmobacter, Paracoccus, Pseudomonas, Defluviimonas, Hydrogenophaga, and Ottowia, all presented themselves as non-dominant bacteria in the blank control system S1, and growing into dominant genera in the S2\S3 system, with a growth rate of about 2-30 times. A review of the literature revealed that eight of these ten genera, except Zoogloea and Clostridium_sensu_stricto, were highly efficient denitrifying bacteria, and Acinetobacter, Gemmobacter, Paracoccus, Pseudomonas and Hydrogenophaga were typical of the Acinetobacter, Paracoccus, Pseudomonas, and Hydrogenophaga were typical aerobic denitrifying bacteria. Acinetobacter, Paracoccus and Pseudomonas were the strains used for loaded microbial immobilized spheres. Consequently, these genera were more abundant in the S2 system, as compared to S3 system, and the gel spheres carrier used in the present study was conducive to enhancement of denitrogenation.

A total of 9, 10, 5, and 9 phyla were identified within samples S4 to S7 (Fig. 5A), respectively. There were fewer phyla in the systems with insufficient carbon sources. The Proteobacteria phylum was dominant in all four reactors, with a relative abundance of more than 50% in all of them, including as high as 73.0% in reactor S6. The Bacteroidetes phylum was also dominant, with an average relative abundance of more than 18%. Three phyla, Firmicutes, Chloroflexi, and Candidatus_Saccharibacteria, had significant organic matter degradation, nitrogen treatment in wastewater treatment, with higher relative abundance in control system S4 than in other conditioned reactors. Nitrospirae remained non-dominant in other systems loaded with functional bacterial pellets except S5, which may be due to the increased aeration, prompting the function of Nitrospirae.

At the class level, compared with the other three reactors, the S7 reactor had the least number of dominant classes, which was 12 (Fig. 5B). Betaproteobacteria was its absolute dominant class, with a relative abundance as high as 43.7%. Nitrospira remained a non-dominant bacterium in the control system S4 and the well-aerated system S3, but its relative abundance increased in the reactor with a low carbon-nitrogen ratio and glucose as the carbon source, transforming it into a dominant bacterium.

Figure 5C shows the 32 dominant genera that were observed in the three reactors. The relative abundance of aerobic DNB Acinetobacter, Gemmobacter, Paracoccus, Pseudomonas, Delftia, and Hydrogenophaga was found to be higher in the well aerated S5 system and the S4 control system than in the S6 and S7 systems, and it was hypothesized that the low C/N and inorganic C source may not favor the aerobic denitrifying bacteria. Glucose could negatively affect the growth of these bacteria. Synergistic denitrification between Gemmobacter and Hydrogenophaga and Pseudomonas had also been reported in the literature. The dominant genera with relative abundance more than 10% were Brachymonas and Azonexus in S4,Brachymonas in S5 system, and Zoogloea in S6 and S7 systems. Brachymonas, as a major genus of functional denitrifying bacteria in the short-range nitrification-denitrification process, was experimentally shown to specific conditions could increase the total nitrogen removal rate substantially (C. Yang et al. 2022).

Fig. 5. Bacterial compositions of communities: microbial compositions distributions at phylum A, class B, and genus C level

Key functional species

To clarify the relationship between microorganisms and removal performances, studies on key functional species associated with carbon, nitrogen and Extracellular Polymeric Substances (EPS) production were particularly necessary. It is well known that traditional biological denitrification involves two main microbial processes, nitrification and denitrification, and only Nitrospira, which were reported as nitrite-oxidizing bacteria (NOB), were also observed in this study. The growth of Nitrospira was inhibited and its relative abundance became lower in the system loaded with synchronized nitrifying denitrifying functional bacteria. There were a large number of denitrifying bacteria (DNB) to ensure the effective and reliable water nitrogen denitrification process, and most of the DNB carried out heterotrophic denitrification, thus consuming carbon sources during denitrification (Table 3).

A total of 22 species of DNB were detected in the three samples in the different system experiments, including aerobic denitrifying bacteria Brachymonas, Acinetobacter, Paracoccus, Delftia, Pseudomonas, Gemmobacter, Thauera, and Aeromonas. As can be seen from Table 3, the relative abundance of most aerobic DNB in the reactors of different systems showed a more significant increase under the effect of immobilization, which explains the higher nitrogen removal capacity of reactor #2, compared to reactor #1.

Under different working conditions, DNB growth was more pronounced in the S4 and S5 systems, with a combined relative abundance of more than 50%. At present, the denitrification pathway of aerobic denitrifying bacteria was relatively clear, i.e., NO, N₂O, NO, N₂, NO₂^–-N, NO₃^–-N, and Azonexus had the highest abundance of 15.1% in the S4 reactor, and it was found that Azonexus could efficiently remove denitrification intermediates (NO₂^–) during denitrification, with slight accumulation of NO₂^– in this reactor, which was speculated to be the reason for the massive growth and reproduction of Azonexus. As can be seen from Table 3, the low carbon to nitrogen ratio (S6) and glucose carbon source (S7) were unfavorable factors for the growth of DNB. The DNB consumed a huge amount of C source to perform nitrification, which well explains the previous results about organic matter degradation, which aligned with the COD removal performance.

CONCLUSIONS

The reactor amended with BADB (Reactor 2#) demonstrated superior and stable pollutant removal compared with the control with only activated sludge (Reactor 1#) and the carrier-control (Reactor 3#). This confirms a synergistic effect in which the biochar-based gel spheres do not merely act as a physical support. Rather, they create an optimized micro-environment that enhances microbial activity, protects functional bacteria, and prevents washout, leading to a more efficient and robust system.
An elevated aeration rate (3 L/min) was found to be beneficial, significantly boosting the removal performances of COD, NH₄⁺-N, and TN. This system can also maintain high processing efficiency under aerobic conditions.
The type and quantity of carbon source were found to be critical. Sodium acetate was a superior carbon source compared with glucose, which led to system acidification and performance deterioration. Maintaining a C/N ratio within an appropriate range was found to be essential for achieving high nitrogen removal efficacy. This study showed a broad range of carbon-nitrogen ratios (8 to 15).
The significant enrichment of key aerobic denitrifying genera, such as Brachymonas, Acinetobacter, Paracoccus, and Pseudomonas, directly explained the enhanced nitrogen removal capacity. The observed functional redundancy and community restructuring in response to different operational conditions provided biological resilience, ensuring stable performance under fluctuating environments.
Brachymonas was identified as a pivotal aerobic denitrifying bacterium in the system, with its relative abundance soaring under optimal conditions (up to 13.9%). Its prominent role underscores its importance in the short-range nitrification-denitrification process and its potential as a biomarker for a healthy, high-performance BADB system.
This work provides operational parameters for optimizing BADB technology. The combination of a protective biochar-hydrogel carrier with a diversified and adaptable microbial community presents a highly promising strategy for the advanced treatment of high-ammonia nitrogen wastewater, facilitating the transition of aerobic denitrification from laboratory research to practical engineering application.

ACKNOWLEDGMENTS

This work was financially supported by the Natural Science Foundation Project of Henan Province (252300421933), the Scientific and Technological Projects of Henan Province (242102320110), the Key Scientific Research Project Plan of Henan Province’s Higher Education Institutions (24B610010), the Training Program for Young Backbone Teachers in Higher Education Institutions of Henan Province, and the innovative Technology Team for Water Pollution Control and Solid Waste Resource Utilization of Nanyang Institute of Technology.

Conflict of Interest

The authors declare no conflict of interest.

Use of Generative AI

The authors declare that no AI was used.

REFERENCES CITED

An, F., Gao, Y., Yu, M., Xiao, T., Lin, H., and Sun, D. (2024). “Removal and recovery of nitrogen from anaerobically treated leachate based on a neglected HNAD nitrogen removal pathway: NH3 stripping,” Bioresource Technology 413, article 131488. https://doi.org/10.1016/j.biortech.2024.131488

Apha. (2012). “Standard methods for the examination of water and wastewater,” American Public Health Association (APHA). Washington, DC, USA.

Bian, X., Wu, Y., Li, J., Yin, M., Li, D., Pei, H., Guo, W. (2022). “Effect of dissolved oxygen on high C/N wastewater treatment in moving bed biofilm reactors based on heterotrophic nitrification and aerobic denitrification: Nitrogen removal performance and potential mechanisms,” Bioresource Technology 365, article 128147. https://doi.org/10.1016/j.biortech.2022.128147

Chen, D., Yang, Y., Geng, H., Chen, D., Qiao, Z., Yin, M., Zhao, L. (2023). “Start-up mechanism of simultaneous nitrification-endogenous denitrification process for treatment of low C/N wastewater: Insights into reactor performance and microbial community dynamics,” Journal of Cleaner Production 418, article 138093. https://doi.org/ 10.1016/j.jclepro.2023.138093

Chen, M., He, T., Wu, Q., Zhang, M., and He, K. (2023). “Enhanced heterotrophic nitrification and aerobic denitrification performance of Glutamicibacter arilaitensis EM-H8 with different carbon sources,” Chemosphere 323, article 138266. https://doi.org/10.1016/j.chemosphere.2023.138266

Chen, S., He, S., Wu, C., and Du, D. (2019). “Characteristics of heterotrophic nitrification and aerobic denitrification bacterium Acinetobacter sp. T1 and its application for pig farm wastewater treatment,” Journal of Bioscience and Bioengineering 127(2), 201-205. DOI: 10.1016/j.jbiosc.2018.07.025

Hill, C. B., and Khan, E. (2008). “A comparative study of immobilized nitrifying and co-immobilized nitrifying and denitrifying bacteria for ammonia removal from sludge digester supernatant,” Water, Air, and Soil Pollution 195(1), 23-33. https://doi.org/10.1007/s11270-008-9724-x

Hu, B., Lu, J., Qin, Y., Zhou, M., Tan, Y., Wu, P., and Zhao, J. (2023). “A critical review of heterotrophic nitrification and aerobic denitrification process: Influencing factors and mechanisms,” Journal of Water Process Engineering 54, article 103995. https://doi.org/10.1016/j.jwpe.2023.103995

Huang, R., Meng, T., Liu, G., Gao, S., and Tian, J. (2022). “Simultaneous nitrification and denitrification in membrane bioreactor: Effect of dissolved oxygen,” Journal of Environmental Management 323, article 116183. https://doi.org/10.1016/j.jenvman.2022.116183

Huang, X., Duddy, O. P., Silpe, J. E., Paczkowski, J. E., Cong, J., Henke, B. R., and Bassler, B. L. (2020). “Mechanism underlying autoinducer recognition in the Vibrio cholerae DPO-VqmA quorum-sensing pathway,” Journal of Biological Chemistry 295(10), 2916-2931. DOI: 10.1074/jbc.RA119.012104

Huang, X., Fan, W., Wang, S., Xiong, J., Chen, Y., and Xie, C. (2024). “Highly effective removal of nitrate from saline wastewater by glucose-enhanced sulfur autotrophic system,” Journal of Water Process Engineering 63, article 105439. https://doi.org/10.1016/j.jwpe.2024.105439

Ji, B., Qian, Y., Zhang, H., Al-Gabr, H. M., Xu, M., Zhang, K., and Zhang, D. (2023). “Optimizing heterotrophic nitrification process: The significance of demand-driven aeration and organic matter concentration,” Bioresource Technology 376, article 128907. https://doi.org/10.1016/j.biortech.2023.128907

Jin, P., Chen, Y., Xu, T., Cui, Z., and Zheng, Z. (2019). “Efficient nitrogen removal by simultaneous heterotrophic nitrifying-aerobic denitrifying bacterium in a purification tank bioreactor amended with two-stage dissolved oxygen control,” Bioresource Technology 281, 392-400. https://doi.org/10.1016/j.biortech.2019.02.119

Karanasios, K. A., Vasiliadou, I. A., Pavlou, S., and Vayenas, D. V. (2010). “Hydrogenotrophic denitrification of potable water: A review,” Journal of Hazardous Materials 180(1), 20-37. https://doi.org/10.1016/j.jhazmat.2010.04.090

Kartal, B., Kuypers, M. M., Lavik, G., Schalk, J., Op den Camp, H. J., Jetten, M. S., and Strous, M. (2007). “Anammox bacteria disguised as denitrifiers: Nitrate reduction to dinitrogen gas via nitrite and ammonium,” Environ Microbiol 9(3), 635-642. https://doi.org/10.1111/j.1462-2920.2006.01183.x

Li, T., Liu, C., Xi, Z., Li, N., Liao, L., Zhou, Y., Pan, L. (2025). “Screening and characterization of an Alcaligenes sp. HHVWA23 and the efficiency of nitrogen removal by biochar immobilization,” Journal of Environmental Management 390, article 126253. https://doi.org/10.1016/j.jenvman.2025.126253

Liao, W., Liang, Z., Yu, Y., Li, G., Li, Y., and An, T. (2021). “Pollution profiles, removal performance and health risk reduction of malodorous volatile organic compounds emitted from municipal leachate treating process,” Journal of Cleaner Production 315, article 128141. https://doi.org/10.1016/j.jclepro.2021.128141

Liu, Z., Liu, S., Ye, Y., Tang, Q., Tian, W., Liu, H., Liu, D. (2024). “Characteristics of a heavy metal resistant heterotrophic nitrification–aerobic denitrification bacterium isolated from municipal activated sludge,” Environmental Research 263, article 120111. https://doi.org/10.1016/j.envres.2024.120111

Lu, J., Tan, Y., Tian, S., Qin, Y., Zhou, M., Hu, H., and Hu, B. (2024). “Effect of carbon source on carbon and nitrogen metabolism of common heterotrophic nitrification-aerobic denitrification pathway,” Chemosphere 361, article 142525. https://doi.org/10.1016/j.chemosphere.2024.142525

Peng, Z., Qin, J., Zhao, Y., Li, Y., Hu, F., Bai, Z., and Ji, J. (2025). “Comparison of the performances and mechanisms of anammox bacteria in-situ self-enrichment under heterotrophic and autotrophic conditions by inoculating ordinary activated sludge,” Bioresource Technology 422, article 132213. https://doi.org/10.1016/j.biortech.2025.132213

Qiu, H., Zhao, W., Zhao, Z., Bai, M., Bi, X., Zhou, X., Wang, C. (2025). “Nitrogen removal activity and functional microbial community structure in IFAS, activated sludge, and MBBR systems under different salinity conditions,” Journal of Water Process Engineering 76, article 108285. https://doi.org/10.1016/j.jwpe.2025.108285

Sethi, S., Gupta, R., Sahu, R., Bharshankh, A., Funde, N., and Biswas, R. (2025). “Temperature variations help in-situ anammox self-enrichment in a single-stage partial nitrification-anammox system from unacclimatized biomass,” Journal of Water Process Engineering 76, article 108281. https://doi.org/10.1016/j.jwpe.2025.108281

Sha, H.-L., Shen, J.-C., Huang, M.-X., Cai, L.-X., and Guan, W.-Y. (2024). “Identification and synergistic denitrification of two heterotrophic nitrification-aerobic denitrification bacteria,” Water, Air, and Soil Pollution 235(6), article 338.

Shi, S., Shu, B., Cao, M., Liu, Y., Yao, X., Zhou, J., and Zhou, J. (2024). “Pre-anaerobic phase persists benefits for nitrogen removal in high carbon/nitrogen scenarios: Comparative study of aerobic–anoxic and anaerobic–aerobic–anoxic sequencing batch reactors,” Journal of Cleaner Production 434, article 140189. https://doi.org/10.1016/j.jclepro.2023.140189

Song, J., Li, M., Wang, C., Fan, Y., Li, Y., Wang, Y., and Wang, H. (2023). “Enhanced treatment of landfill leachate by biochar-based aerobic denitrifying bacteria functional microbial materials: Preparation and performance,” Frontiers in Microbiology 14, article 1139650. https://doi.org/10.3389/fmicb.2023.1139650

Song, T., Zhang, X., Li, J., Wu, X., Feng, H., and Dong, W. (2021). “A review of research progress of heterotrophic nitrification and aerobic denitrification microorganisms (HNADMs),” Science of The Total Environment 801, article 149319. https://doi.org/10.1016/j.scitotenv.2021.149319

Su, Y., Li, X., Wang, J., Du, R., Xue, X., Shi, Y., and Peng, Y. (2024). “Effect of anaerobic duration on nitrogen and phosphorus removal and carbon source utilization in integrated denitrifying phosphorus removal and partial denitrification coupled with anammox system,” Journal of Cleaner Production 474, article 143591. https://doi.org/10.1016/j.jclepro.2024.143591

Sun, S., and Li, R. (2024). “The superiority of citrate as denitrification carbon source in an activated sludge system: Substrate metabolism, electron transfer and microbial characteristics,” Journal of Water Process Engineering 61, article 105285. https://doi.org/10.1016/j.jwpe.2024.105285

Xia, L., Li, X., Fan, W., and Wang, J. (2020). “Heterotrophic nitrification and aerobic denitrification by a novel Acinetobacter sp. ND7 isolated from municipal activated sludge,” Bioresource Technology 301, article 122749. https://doi.org/10.1016/j.biortech.2020.122749

Xiao, W., Meng, G., Meng, C., Sun, R., Hu, S., Yi, M., and Wu, Y. (2024). “New insights into microbial community for simultaneous removal of carbon and nitrogen via heterotrophic nitrification aerobic denitrification process,” Journal of Environmental Chemical Engineering 12(3), article 112896. https://doi.org/10.1016/j.jece.2024.112896

Yang, C., Wang, L., Wang, H., Zhang, H., Wang, F., Zhou, H., and Chen, Y. (2022). “Dynamics of antibiotic resistance genes and microbial community in shortcut nitrification–denitrification process under antibiotic stresses,” Environmental Science and Pollution Research 29(31), 46848-46858. https://doi.org/10.1007/s11356-022-19160-8

Yang, X., Wang, W., Liu, X., Xie, S., Feng, J., and Lv, J. (2025). “Nitrogen metabolism functional shifts of indigenous bacteria and effect on nitrogen removal in microalgae-based municipal wastewater treatment system across aeration modes,” Bioresource Technology 435, article 132881. https://doi.org/10.1016/j.biortech.2025.132881

Yang, Z., Zhou, Q., Sun, H., Jia, L., Zhao, L., and Wu, W. (2021). “Metagenomic analyses of microbial structure and metabolic pathway in solid-phase denitrification systems for advanced nitrogen removal of wastewater treatment plant effluent: A pilot-scale study,” Water Research 196, article 117067. https://doi.org/10.1016/j.watres.2021.117067

Zhang, M., Lu, H., Cai, L., Sun, P., Ma, B., Li, J., and Ruan, Y. (2023). “C/N ratios inform sustainable aerobic denitrification for nitrogen pollution control: Insights into the key parameter from a view of metabolic division,” Journal of Cleaner Production 414, article 137565. https://doi.org/10.1016/j.jclepro.2023.137565

Zhao, B., Tian, M., An, Q., Ye, J., and Guo, J. S. (2017). “Characteristics of a heterotrophic nitrogen removal bacterium and its potential application on treatment of ammonium-rich wastewater,” Bioresource Technology 226, 46-54. https://doi.org/10.1016/j.biortech.2016.11.120

Zhou, X., Wang, X., Zhang, H., and Wu, H. (2017). “Enhanced nitrogen removal of low C/N domestic wastewater using a biochar-amended aerated vertical flow constructed wetland,” Bioresource Technology 241, 269-275. https://doi.org/10.1016/j.biortech.2017.05.072

Zhu, Z., Yang, Y., Fang, A., Lou, Y., Xie, G., Ren, N., and Xing, D. (2020). “Quorum sensing systems regulate heterotrophic nitrification-aerobic denitrification by changing the activity of nitrogen-cycling enzymes,” Environmental Science and Ecotechnology 2, article 100026. https://doi.org/10.1016/j.ese.2020.100026

Article submitted: September 2025; Peer review completed: November 22, 2025; Revised version received and accepted: December 3, 2025; Published: December 15, 2025.

DOI: 10.15376/biores.21.1.1065-1083