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Article

The Influence of Atmospheric Pressure and Organic Loading on the Sustainability of Simultaneous Nitrification and Denitrification

by
Wei-Jia Yu
1,†,
Ji Sun
1,†,
Wei-Jia Zhang
1,
Yue Chen
2,3,
Jun-Ling Yang
2,3,
Shu-Ping Li
2,3,
Guang-Can Zhu
1,2,3 and
Yong-Ze Lu
1,2,3,*
1
School of Energy and Environment, Southeast University, Nanjing 210096, China
2
Key Laboratory of Water Pollution Control and Ecological Restoration of Xizang, National Ethnic Affairs Commission, Xizang Minzu University, Xianyang 712082, China
3
Information Engineer College, Xizang Minzu University, Xianyang 712082, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Sustainability 2023, 15(22), 15689; https://doi.org/10.3390/su152215689
Submission received: 18 October 2023 / Revised: 2 November 2023 / Accepted: 5 November 2023 / Published: 7 November 2023
(This article belongs to the Section Sustainable Water Management)
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Abstract

:
In high-altitude regions, a diminished atmospheric oxygen content significantly impairs the aeration efficiency of municipal wastewater, posing a challenge to sustainable wastewater management. Consequently, conventional biological wastewater treatment methods necessitate elevated energy consumption in high-altitude areas, rendering them economically and environmentally unsustainable. The simultaneous nitrification and denitrification (SND) process, owing to its minimal oxygen requirements, emerges as a promising and sustainable solution in low-pressure environments. Additionally, owing to the unique lifestyle and natural conditions in plateau regions, the organic loading in municipal wastewater is often low. To comprehensively assess the impact of low pressure and organic loading on the SND process, three laboratory-scale reactors were implemented. This study revealed that low pressure and the introduction of organic matter enhanced both nitrogen removal performance and SND efficiency. The sludge volume index decreased by 93.5%, indicating a substantial improvement in the microbial aggregation ability and the formation of a more favorable SND sludge structure. 16S rRNA sequencing results demonstrated alterations in the microbial community structure due to low pressure and the addition of organic matter, leading to a substantial increase in the abundance of nitrifying and denitrifying bacteria. Furthermore, the prediction results of functional genes indicated the upregulation of genes related to the nitrification and denitrification processes with decreasing pressure and the addition of organic matter. This enhancement underlines the improved microbial nitrogen removal function. This study underscores the positive influence of low pressure and organic loading on the SND system, thereby substantially enhancing the economic and environmental sustainability of the SND process in plateau regions.

1. Introduction

In recent years, heightened attention has been directed toward environmental protection issues in high-altitude regions, driven by their fragile ecology. Efficient management of municipal wastewater is paramount for maintaining a delicate ecological equilibrium and promoting sustainable development in high-altitude regions. Currently, the Anaerobic Anoxic Oxic (A2O), Cyclic Activated Sludge System (CASS), and oxidation ditch processes serve as the predominant techniques utilized in urban sewage treatment plants within plateau regions. These methods rely on aerobic nitrifying and anaerobic denitrifying bacteria, each necessitating precise levels of oxygen and carbon sources. However, the decreased air pressure in plateau regions obstructs the efficient transfer of oxygen from air to water, resulting in notably low levels of saturated dissolved oxygen. Moreover, the reduced oxygen levels in the high-altitude atmosphere escalate the energy consumption in traditional biological nitrogen removal processes, presenting substantial challenges in mitigating these environmental concerns effectively [1,2,3]. Simultaneous nitrification and denitrification (SND), known for its low oxygen demand and rapid reaction rate [4,5], stands out as a promising and environmentally sustainable solution for municipal wastewater treatment in high-altitude regions [3].
Previous research has established the significant influence of organic matter on the denitrification process, acting as a carbon source for aerobic heterotrophic bacteria. This impact extends to dissolved oxygen levels, directly affecting the efficiency of the SND process [6,7]. However, the characteristics of wastewater in high-altitude areas differ markedly from those in plains due to variations in water consumption and drainage systems. Certain pretreatment units, such as aerated grit chambers, consume substantial amounts of carbon sources [8]. Additionally, the widespread presence of septic tanks in plateau regions further diminishes organic loading through fermentation. In high-altitude locales, open taps in winter, a measure to prevent freezing, lead to the dilution of organic matter in sewage. Similarly, the mixing of rainwater into sewage pipes has a similar effect [9], resulting in lower organic loading in plateau sewage. Generally, wastewater treatment processes require minimal aeration when organic loading is low. However, the plateau environment necessitates increased aeration volume. In light of these factors, it is imperative to comprehensively assess the combined impacts of air pressure and organic loading on the SND system. This holistic understanding is essential for achieving the efficient removal of pollutants, thereby enhancing the sustainability of wastewater treatment processes.
This study explored the intricate relationship between atmospheric pressure and organic loading in the SND process, employing sequential batch reactors (SBRs). We assessed the nitrogen removal performance of the SND systems and delved into the underlying mechanisms. Additionally, we detected changes in the microbial community structure to elucidate the impact of atmospheric pressure and organic loading on functional bacteria. Our research offers compelling evidence of enhanced nitrogen removal using the SND system in plateau-like environments. This study not only highlights the potential of SND but also outlines a sustainable approach for managing wastewater in high-altitude regions.

2. Materials and Methods

2.1. SND Reactor Setup and Operation

The experiment employed three reactors operating at different pressures (101 kPa, 85 kPa, and 70 kPa), each made of glass with a working volume of 3 L (Figure 1). The reactors featured a top inlet for water and a side outlet for sampling and drainage. Peristaltic pumps were utilized for aeration, maintaining dissolved oxygen levels at 1.0 mg/L. Additionally, a pressure console and a vacuum pump were integrated to regulate the pressure. If the pressure detected by the console deviated by more than 5 units from the set value, the vacuum pump initiated air pumping to maintain the desired pressure. The reactors functioned in a semi-continuous flow mode, with stirring and mixing operations. Stirring ceased once the ammonia concentration dropped significantly, after which the mixed liquid was settled and replaced with a fresh nutrient solution. To facilitate the growth and metabolism of functional bacteria, a heating belt was employed to maintain the reactors’ temperature between 25 and 30 °C, an optimal range.
To precisely control organic loading, glucose was chosen as the carbon source, with concentrations ranging from 0 to 80 mg/L, measured in terms of chemical oxygen demand (COD). The reactors, operating in the semi-continuous flow mode, received glucose supplements based on the COD consumption rate determined during the startup phase. The injection of glucose solutions at these specified concentrations into the reactors ensured COD supplementation without compromising pressure and dissolved oxygen levels.
The activated sludge used in the experiment was obtained from the secondary sedimentation tank of a municipal wastewater treatment facility. The nutrient solution consisted of 65–80 mg NH4+-N·L−1, 2 mg KH2PO4·L−1, 110 mg KHCO3·L−1, 20 mg MgSO4·L−1, 20 mg CaCl2·L−1, 1.5 mL of trace element solution I, and 1.5 mL of trace element solution II. Trace element solution I included 5 mg EDTA·L−1 and 5000 mg FeSO4·L−1, while trace element solution II contained 5000 mg EDTA·L−1, 240 mg CoCl2·6H2O·L−1, 430 mg ZnSO4·7H2O·L−1, 990 mg MnCl2·4H2O·L−1, 250 mg CuSO4·5H2O·L−1, 190 mg NiCl2·6H2O·L−1, 220 mg Na2MoO4·10H2O·L−1, 14 mgH3BO3·L−1, and 210 mg Na2SeO4·10H2O·L−1. All chemicals used were of analytical grade and were sourced from Aladdin Bio-Chem Technology in Shanghai, China.

2.2. Analytical Methods

The concentrations of the soluble compounds in the specimens were assessed following filtration through 0.45 μm cellulose acetate filters. Nitrate-N (NO3−-N), nitrite-N (NO2−-N), ammonia-N (NH4+-N), and total nitrogen (TN) were assayed according to the standard methods, using a UV/VIS spectrophotometer (UV9100, LabTech, Beijing, China) [10].
SND efficiency was calculated using Equation (1) [11]:
S N D   e f f i c i e n c y = 1 − ( ∆ N O 2 − + ∆ N O 3 − ) ∆ N H 4 + × 100 %
The sludge volume index (SVI) represents the volume of wet sludge produced by 1 g of dry sludge. SVI was calculated following the methodology outlined in the literature and is presented in SI units [12].

2.3. Microbial Community Analysis

To examine the fluctuations in microbial communities amid diverse SND conditions, samples of sludge from multiple reactors were dispatched to Shanghai Majorbio Bio-pharm Technology Co., Ltd. in Shanghai, China, for sequencing of the 16S ribosomal RNA (rRNA) gene amplicons. The sludge derived from two reactors operating at low pressures (85 kPa and 70 kPa) and exhibiting COD concentrations of 0 (designated as S1 and S2) and 20 mg/L (designated as S3 and S4) was analyzed. Additionally, a sludge sample from the atmospheric pressure stage with COD supplementation was tested for comparison (S5). The experimental conditions for each group are detailed in Table S1.
DNA extraction from the sludge specimens was conducted employing an EZNA® Soil Kit (Omega Bio-Tek, Norcross, GA, USA). The amplification of the 16S rRNA gene (V3-V4 region) was achieved with the primers 338F 5′-ACTCCTACGGGAGGCAGCAG-3′ and 806R 5′-GGACTACHVGGGTWTCTAAT-3′. Polymerase chain reaction (PCR) was performed in 20 μL reactions, including 0.4 μL FastPfu polymerase, 4 μL 5× FastPfu buffer, 0.8 μL (5 μM) of each primer, 2 μL 2.5 mM dNTPs, and 10 ng template DNA. The thermal cycling conditions comprised an initial denaturation at 95 °C for 3 min, followed by 27 cycles at 95 °C for 30 s, 55 °C for 30 s, 72 °C for 30 s, and a final extension at 72 °C for 10 min.
Following amplification, the PCR products underwent validation through 2% agarose gel electrophoresis, were then pooled, and purified utilizing an AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA). Sequencing was executed on the MiSeq PE300 platform (Illumina, San Diego, CA, USA) to generate clean data, which were processed by Majorbio BioPharm Technology Co., Ltd. (Shanghai, China). Sequences have been deposited in the NCBI under accession number PRJNA 1024543.
To evaluate the influence of air pressure and organic loading on microbial community functionality, the 16S rRNA gene data underwent an analysis using the phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) algorithm. PICRUSt predicts the functional composition of a metagenome utilizing marker gene data and a reference genome database [13]. For our analysis, the Kyoto Encyclopedia of Genes and Genomes (KEGG) catalog was used as the reference database, storing the molecular functions of genes and proteins.

2.4. Statistical Analysis

Experiments were conducted in triplicate, and the results are expressed as mean ± standard deviation. A one-way analysis of variance, performed using Microsoft Office Excel 2018, assessed differences within the same cohort, with significance set at p < 0.05. Graphs depicting the results were generated using OriginPro Version 2021(9.8) software (OriginLab, Northampton, MA, USA).

3. Results and Discussion

3.1. SND Reactor Performance

In Figure 2, the nitrogen removal performance of the SND reactors is depicted under varying air pressures and COD concentrations. Under atmospheric pressure, the total nitrogen (TN) removal efficiency increased steadily with rising COD concentrations from 0 to 80 mg/L, reaching 15.81%, 40.60%, 46.32%, and 57.93%. Similarly, under low-pressure conditions of 85 kPa and 70 kPa, the removal of NH4+-N and TN followed a similar trend to COD and increased from 20 mg/L to 80 mg/L. The addition of COD served as an electron donor for the denitrification process, enhancing nitrogen removal. The removal efficiency correlated positively with the added COD concentration. However, the presence of COD resulted in lower NH4+-N removal. In the low-pressure reactors (85 kPa and 70 kPa), the introduction of organic matter increased oxygen consumption, leading to insufficient dissolved oxygen levels and short-term fluctuations in the functional bacterial community structure. Consequently, NH4+-N removal was diminished in the presence of COD, affecting the TN removal efficiency.
In the absence of COD addition, the impact of different pressure conditions on reactor performance was analyzed. It was observed that, as the pressure decreased, the nitrogen removal efficiency of the three reactors markedly increased, resulting in TN removal efficiencies of 15.81%, 34.55%, and 56.28%. A comparison between the 85 kPa and 70 kPa reactors revealed TN removal efficiencies of 24.26% and 34.55% at a COD concentration of 20 mg/L, and 36.15% and 44.67% at a COD concentration of 50 mg/L. Notably, at a COD concentration of 80 mg/L, the TN removal efficiency of the 70 kPa reactor surpassed that of the 85 kPa reactor, accompanied by a significant reduction in the accumulation of NO2−-N and NO3−-N. These results suggest that low-pressure conditions promote nitrogen escape, stimulate the denitrification process, and enhance the overall total nitrogen removal efficiency of the reactor.
SND efficiency denotes the simultaneous presence of nitrification and denitrification processes carried out by microorganisms within a specific environment [14]. This efficiency functions as a crucial indicator, reflecting the equilibrium between nitrification and denitrification and providing insights into the nitrogen cycle status within the system. A value close to 1 signifies a relatively stable nitrogen cycle, indicating comparable efficiencies of nitrification and denitrification. Deviation toward nitrification implies potential nitrogen accumulation, while deviation toward denitrification suggests nitrogen deficiency. As the organic load increased, the SND percentage gradually rose, reaching 100% at the end of the operation for all three reactors, as depicted in Figure 3. The solid gray line represents the median, and the dashed line represents the mean value. A comparative analysis of different pressure conditions revealed that low-pressure environments were more conducive to simultaneous nitrification and denitrification. In the absence of an external carbon source, the reactor operating at 70 kPa exhibited the highest SND efficiency, averaging at 89.76%, followed by the 85 kPa reactor at 75.01%, while the atmospheric pressure reactor had the lowest SND efficiency at 32.76%. Similar trends were observed across various organic concentration conditions, indicating that low-pressure conditions enhanced the SND process. Furthermore, the SND efficiency increased by 65.91%, 22.85%, and 9.73% with the rise in the COD concentration in the different reactors, demonstrating a positive correlation between SND efficiency and the added COD concentration.
Microscopic observations of the bacteria-containing sludge from various reactors, conducted after a month of operation at a magnification of 100 times, are presented in Figure S1. The sludge’s aggregate performance notably improved with higher COD concentrations in the reactor solution. It was speculated that the addition of COD stimulated denitrifying bacteria, enhancing overall microbial activity in the reactor. This stimulation led to increased extracellular polymer (EPS) secretion by microbial cells. Chemical bonding and physical composition provided a network structure that facilitated microbial aggregate formation. Moreover, the dense structure of biological aggregates, such as biofilms, prevented outward EPS spreading, causing EPS to accumulate around the biofilm. EPS primarily comprises protein (PN) and polysaccharides (PSs) [15]. Protein and polysaccharide interactions, facilitated by hydrogen bonding and ion interactions, can modify the surface properties of activated sludge [16]. Moreover, EPS can form distinct network structures with cells, encouraging the development of tightly structured biofilms or granular sludge [17]. The alterations in sludge behavior further confirmed that the addition of COD enhanced the functionality of the SND system.
The SVI of the bacteria-containing sludge in the SND reactors was calculated under various COD concentrations, as presented in Table 1. The rise in the COD concentration correlated with a notable decline in SVI values, indicating a denser sludge with enhanced sedimentation characteristics and reduced susceptibility to expansion and flotation. The extracellular polymer is divided into Tightly Bound EPS (TB) and Loosely Bound EPS (LB). TB, located in the inner layer, firmly adheres to the cell surface and remains stable outside the cell wall, while LB, situated in the outer layer of TB, has a relatively loose structure and can expand into the surrounding environment [18]. An increase in the TB content improved sludge settling, while a higher LB content had the opposite effect [19]. By analyzing the SVI changes, it could be inferred that the gradual elevation in the COD concentration led to an increase in the TB content or a decrease in the LB content, resulting in a more condensed sludge structure. Since the TB content is linked to metabolic activity and LB primarily originates from cellular autolysis, it was speculated that COD supplementation positively influenced the microorganisms’ metabolic activity in the SND system. Furthermore, TB facilitated the formation of anoxic zones within the sludge, providing an appropriate environment for denitrifying bacteria metabolism and enhancing their activity [20]. In summary, the reactor operating at 70 kPa exhibited the highest SND efficiency, indicating a positive correlation with COD addition concentration and a negative correlation with SVI. SND efficiency peaked at a COD concentration of 80 mg/L and an SVI of 12.32 mL/g.

3.2. Variation of Microbial Diversity

Activated sludge community diversity was investigated under different pressure and organic load conditions. Higher Chao1 and Ace index values indicate a greater community richness, while a higher Shannon index corresponds to a lower Simpson index, reflecting greater community diversity [21]. A comparison among groups with different pressure and organic matter concentrations (Table 2) demonstrated that the microbial diversity in the reactor gradually decreased as the pressure decreased or the organic matter concentration increased. This trend aligns with the findings of prior studies on the activated sludge treatment of high-altitude wastewater samples [22,23]. This suggests an acclimation process where functional bacteria dominate, strengthening the overall denitrification function of the reactor and making it more stable. The phylum-level sequencing of the microbial structures under varied conditions (Figure S2) supports these findings. A principal component analysis (PCA) was utilized to analyze the evolution of the community composition under varying pressure and organic load conditions [24]. The point distance difference analysis in Figure S3 indicated substantial changes in the microbial community structure of the reactors under varying pressures and organic matter concentrations, with pressure having a more pronounced influence. The interpretation rates for the PC1 and PC2 axes were 62.6% and 22.94%, respectively.
Upon analyzing the microbial community structure at the genus level in the four low-pressure reactors (Figure 4), Rhodanobacter, known for their nitrification and denitrification abilities, were prominent in the SND system [25,26]. The abundance of Rhodanobacter increased from 23.7% in S1 to 45.7% in S2 and from 20.7% in S3 to 58.3% in S4, indicating enhanced denitrification under low-pressure conditions. At 85 kPa, the addition of organic matter had a negligible impact on Rhodanobacter abundance, whereas at 70 kPa, a significant increase was observed, confirming organic matter’s stimulating effect on denitrification. Additionally, Chujaibacter, a well-known denitrifying bacterium [27], thrived under reduced pressure. Its abundance rose from less than 3% in S1 and S3 to 24.6% in S2 and 17.5% in S4 as the reactor pressure decreased, reinforcing the idea that decreased pressure accelerated nitrogen escape and bolstered the denitrification process.
Certain bacterial genera, such as Micropepsacaea, Acidovorax, Stenotrophomonas, Nitrosomonas, and Nitrospira, are known for their denitrification and nitrification capabilities [27,28]. The abundance of these bacteria either decreased or remained relatively stable with a decreasing air pressure and the introduction of COD. This phenomenon is likely attributed to the dominance of bacteria like Rhodanobacter, which occupied the primary nitrogen removal functional sites in the system. Moreover, Chryseolinea, a filamentous bacterium commonly found in sludge systems, has been reported to assimilate and disassimilate nitrate [29]. Its abundance decreased from 6.5% in S1 to 1.9% in S3 when 20 mg/L of COD was introduced into the 85 kPa reactor and was not detected in the 70 kPa reactor. These findings confirm that specific low-pressure and organic conditions can enhance the denitrification process, altering the proportion of nitrate metabolic pathways and potentially inhibiting the expansion of filamentous bacteria in the sludge system.

3.3. Correlation Analysis between Microbial Communities and Environmental Factors

A Canonical Correspondence Analysis (CCA) is a unimodal model-based approach offering an intuitive visualization of the relationship between sample distribution and environmental factors [30]. In Figure 5, the projection extends from the sample point to the arrow indicating the quantitative environmental factor, and the distance from this projection point to the origin represents the relative influence of environmental factors on the sample community’s distribution [31]. CCA1 and CCA2 had explanatory degrees of 43.89% and 11.83%, respectively. Figure 5 demonstrates that the acute angle between the arrows depicting the organic matter concentration and pressure indicates a positive correlation between these factors and their impact on the bacterial sample structure. This observation supports the earlier conclusion that low pressure and organic matter bolster the denitrification process. Moreover, the longer arrow representing pressure compared to organic matter suggests that the pressure exerted a greater influence on the microbial community structure, corroborating the principal component analysis findings.
Upon analyzing the projection of sample points onto the pressure and COD arrows under various conditions, a clear pattern emerged. Under identical COD levels, the projection point of 70 kPa stood further from the origin than that of 85 kPa, highlighting the more significant impact of low-pressure conditions on the community structure. Similarly, under equal-pressure conditions, samples without COD addition exhibited a greater distance from the origin than the COD addition group, indicating the consistent influence of organic loading on the evolution of the microbial community structure.
The consistent alignment of these results with the genus-level sequencing outcomes indicates that major functional bacteria such as Rhodanobacter and Chujaibacter were indeed influenced by both pressure and organic loading conditions, with pressure exerting a more substantial impact. Consequently, these factors significantly influenced nitrogen metabolism during the SND process.
In Figure 6, the predicted abundance of nitrogen removal functional genes is depicted. Each of the four lines represents distinct nitrogen conversion pathways: nitrification mediated by ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB), denitrification mediated by denitrifiers, and dissimilating nitrate reduction and assimilating nitrate reduction involving multiple microorganisms [32,33]. We initially focused on the influence of pressure conditions. Upon comparing the results of S1 and S2, or S3 and S4, we observed a consistent increase in the abundance of the functional genes amoA, amoB, and amoC as the air pressure decreased. This indicates an enhancement in the function of AOB and a gradual increase in aminomonooxygenase production after reaching a stable reaction level [34]. Consequently, more NH4+-N could be oxidized to NH2OH. The atmospheric pressure reactor, S5, also displayed higher amoC abundance, aligning with the NH4+-N removal effect observed in the reactors. Moreover, the abundance of Hao, a functional gene encoding hydroxylamine oxidoreductase [35], increased with decreasing pressure, leading to a greater conversion of NH2OH to NO2−-N and promoting nitrogen conversion. In contrast, the abundance of NxrAB, encoding nitrite oxidase, decreased with increasing pressure, indicating an inhibition of the conversion from NO2−-N to NO3−-N and consequently reducing the accumulation of NO3−-N.
The genes NapAB and NarGHI encode nitrate reductase in denitrification and DNRA processes, while NirK is a functional gene for nitrite reduction. The abundances of NapAB and NarGHI were significantly upregulated with decreasing pressure, aligning with the previously mentioned promotion of the denitrification process under low pressure. This enhancement further improved the denitrification performance of the system. Similarly, the abundances of NorBC, involved in the conversion of NO to N2O, and NosZ, involved in the conversion of N2O to nitrogen, increased with decreasing pressure. This indicates that denitrifying bacteria utilized organic matter for growth and reproduction, and their functions were gradually enhanced. As a result, more NO was converted to N2O and further reduced to N2, leading to a reduction in the accumulation of the greenhouse gas N2O and an overall enhancement of the denitrification function in the reactors.
Additionally, the abundance of the functional genes NirA, NasB, and NirBD, which control the conversion of nitrite into ammonium salt in the processes of ANRA and DNRA, did not follow a clear pattern but decreased compared to S5 at atmospheric pressure. This suggests that nitrite was primarily transformed through the denitrification process, ultimately converting into nitrogen and enhancing the nitrogen removal efficiency.
To assess the impact of organic load, we compared the results of S1 and S3, or S2 and S4. It was evident that the abundance of the major functional genes NarGHI, NirK, and NosZ, involved in the denitrification process, was significantly upregulated with the increasing organic matter concentration. This led to a substantial enhancement of denitrification. Organic matter served as an electron donor for the denitrification process, intensifying the activity of functional bacteria and resulting in enhanced nitrogen removal. The increased conversion of nitrite in the denitrification process also bolstered the nitrification process, as evidenced by the upregulation of amoBC and Hao gene abundances. Conversely, the abundance of NxrAB showed no significant change, indicating that, under the influence of organic matter, the conversion of ammonium salts was enhanced, and less nitrate was produced. Instead, it predominantly participated in the denitrification process in the form of nitrite, consistent with the reduction in nitrate accumulation mentioned earlier. In the DNRA and ANRA processes, the addition of organic matter had no significant effect on the abundance of functional genes.

3.4. SND as a Sustainable Wastewater Treatment Process in High-Altitude Environments

One of the pivotal aspects of SND contributing to sustainability lies in its energy efficiency. Traditional wastewater treatment processes require substantial energy inputs for aeration, mixing, and various operations. SND, amalgamating nitrification and denitrification, significantly diminishes energy demands [36]. SND can effectively eliminate 80–96% of total nitrogen, significantly shortening the reaction time and potentially eliminating the need for external carbon sources. SND demands 22–40% less carbon and leads to a 30% reduction in sludge production [37]. This reduction in energy-intensive processes leads to a substantial decrease in the overall carbon footprint. This aligns seamlessly with the global efforts to curtail greenhouse gas emissions and combat climate change. The application of SND in high-altitude environments is particularly notable due to the unique challenges posed by such regions. High-altitude areas frequently encounter extremely low-pressure and low-temperature conditions, rendering conventional wastewater treatment methods less viable. In this study, SND technology demonstrated its effectiveness under varying pressure conditions. Additionally, numerous studies have affirmed SND’s excellent temperature adaptability [38,39]. The capacity to endure temperature fluctuations and low-temperature environments makes SND an auspicious choice for high-altitude regions, ensuring consistent and efficient wastewater treatment. Studies suggest that nitrification conditions enhance micropollutant removal through co-metabolism during biological treatment [40]. Simultaneous nitrification and denitrification (SND) facilitates various conversion pathways, enhancing the biodegradability of compounds. However, SND has limitations in micropollutant removal, and its efficiency can be bolstered by complementary methods like advanced oxidation technology [41,42].

4. Conclusions

This study examined the impact of low-pressure and organic loading conditions on the SND process, revealing its potential as a sustainable and eco-friendly method for plateau sewage treatment. It was observed that both low pressure and the introduction of organic matter significantly enhanced nitrogen removal. The maximum nitrogen removal efficiency increased by 36.42%, and the simultaneous nitrification and denitrification rate experienced a substantial boost. Notably, the SVI value of the sludge decreased from 190.26 mg/L to 12.32 mg/L, indicating a significant enhancement in the microbial aggregation ability and sedimentation performance. This transformation resulted in a more favorable structure for SND. Furthermore, 16S rRNA sequencing revealed significant alterations in the microbial community structure due to low pressure and the addition of organic matter. Nitrifying and denitrifying bacteria saw a significant increase in abundance, becoming the dominant species within the community. A correlation analysis of environmental factors further underscored the domestication effect of pressure and organic load on the microbial community. Notably, pressure conditions emerged as the predominant environmental factor. Additionally, the predictive results of functional genes demonstrated that the genes encoding nitrosation and denitrification processes were significantly upregulated with reduced pressure and the addition of organic matter. This indicates a strengthening of microbial nitrogen removal functionality. In summary, this study provides a comprehensive exploration, delineating the effects of low pressure and organic load on the SND process, paving the way for sustainable nitrogen removal strategies in high-altitude areas. These findings provide a potential framework for nitrogen removal in domestic sewage within high-altitude areas.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/su152215689/s1, Figure S1: Microscopic examination of sludge appearance at various COD concentrations: (a) 0 mg/L, (b) 20 mg/L, (c) 50 mg/L, (d) 80 mg/L; Figure S2: Phylum-level abundance percentage in microbial community; Figure S3: PCA of microbial community in SND reactors under varied air pressures and COD concentrations; Table S1: Operational parameters of SND reactors for microbial community analysis.

Author Contributions

Conceptualization, Y.-Z.L.; methodology, W.-J.Y. and J.S.; validation, W.-J.Y. and J.S.; formal analysis, W.-J.Y. and J.S.; investigation, W.-J.Y. and J.S.; resources, G.-C.Z. and Y.-Z.L.; data curation, J.S.; writing—original draft preparation, W.-J.Y. and J.S.; visualization, W.-J.Y. and J.S.; supervision, W.-J.Z., Y.C., S.-P.L. and Y.-Z.L.; project administration, Y.-Z.L. and J.-L.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Key Research and Development Program of Xizang, grant number XZ202301ZY0031G.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data collected or analyzed during this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. A schematic of the reactors employed to regulate low air pressure, including 1. pressure sensor, 2. pressure console, 3. vacuum pump, 4. aerator, 5. peristaltic pump, 6. blender, 7. packing, 8. sampling port, 9. dissolved oxygen console, 10. dissolved oxygen probe.
Figure 1. A schematic of the reactors employed to regulate low air pressure, including 1. pressure sensor, 2. pressure console, 3. vacuum pump, 4. aerator, 5. peristaltic pump, 6. blender, 7. packing, 8. sampling port, 9. dissolved oxygen console, 10. dissolved oxygen probe.
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Figure 2. Nitrogen concentrations in simultaneous nitrification and denitrification (SND) reactors were measured at various air pressures and chemical oxygen demand (COD) levels: (a) 100 kPa, (b) 85 kPa, (c) 70 kPa.
Figure 2. Nitrogen concentrations in simultaneous nitrification and denitrification (SND) reactors were measured at various air pressures and chemical oxygen demand (COD) levels: (a) 100 kPa, (b) 85 kPa, (c) 70 kPa.
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Figure 3. The SND efficiency of reactors was studied under various air pressures and COD concentrations: (a) 100 kPa, (b) 85 kPa, (c) 70 kPa. Phases 1 to 4 corresponded to COD concentrations of 0, 20 mg/L, 50 mg/L, and 80 mg/L, respectively.
Figure 3. The SND efficiency of reactors was studied under various air pressures and COD concentrations: (a) 100 kPa, (b) 85 kPa, (c) 70 kPa. Phases 1 to 4 corresponded to COD concentrations of 0, 20 mg/L, 50 mg/L, and 80 mg/L, respectively.
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Figure 4. Percentage of community abundance at the genus level (top 10) in SND reactor sludges under different air pressures and COD concentrations.
Figure 4. Percentage of community abundance at the genus level (top 10) in SND reactor sludges under different air pressures and COD concentrations.
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Figure 5. Canonical Correspondence Analysis (CCA) was conducted to assess the microbial community in SND reactors under various air pressures and COD concentrations. Species are denoted by blue inverted triangles, and brown arrows represent quantitative environmental factors. The arrow length signifies the degree of influence (explanatory quantity) of the environmental factors on the species data. The angle between the arrows indicates the positive or negative correlation (acute angle: positive correlation; obtuse angle: negative correlation; right angle: no correlation).
Figure 5. Canonical Correspondence Analysis (CCA) was conducted to assess the microbial community in SND reactors under various air pressures and COD concentrations. Species are denoted by blue inverted triangles, and brown arrows represent quantitative environmental factors. The arrow length signifies the degree of influence (explanatory quantity) of the environmental factors on the species data. The angle between the arrows indicates the positive or negative correlation (acute angle: positive correlation; obtuse angle: negative correlation; right angle: no correlation).
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Figure 6. Predicted abundance of nitrogen removal functional genes in SND reactor sludge under varying air pressures and COD concentrations.
Figure 6. Predicted abundance of nitrogen removal functional genes in SND reactor sludge under varying air pressures and COD concentrations.
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Table 1. The sludge volume index (SVI) values of the bacteria-containing sludge in SND reactors at varying COD concentrations.
Table 1. The sludge volume index (SVI) values of the bacteria-containing sludge in SND reactors at varying COD concentrations.
COD (mg/L)SV (mL/L)MLSS (g/L)SVI (mL/g)
0216.9 ± 0.0351.14 ± 0.008190.26
2063.0 ± 0.2370.98 ± 0.01164.29
5041.0 ± 0.0131.01 ± 0.00640.59
8012.2 ± 0.0300.99 ± 0.01012.32
Table 2. Diversity indices of microbial communities in SND reactors were assessed under varying air pressures and COD concentrations.
Table 2. Diversity indices of microbial communities in SND reactors were assessed under varying air pressures and COD concentrations.
SampleAceChao1CoverageShannonSimpson
S1345.9351.30.99853.2970.0704
S2176.7172.50.99912.0870.2334
S3417.7422.60.99853.2090.1044
S4310.5318.20.99822.0950.3102
S5879.9884.50.99855.1410.0222
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Yu, W.-J.; Sun, J.; Zhang, W.-J.; Chen, Y.; Yang, J.-L.; Li, S.-P.; Zhu, G.-C.; Lu, Y.-Z. The Influence of Atmospheric Pressure and Organic Loading on the Sustainability of Simultaneous Nitrification and Denitrification. Sustainability 2023, 15, 15689. https://doi.org/10.3390/su152215689

AMA Style

Yu W-J, Sun J, Zhang W-J, Chen Y, Yang J-L, Li S-P, Zhu G-C, Lu Y-Z. The Influence of Atmospheric Pressure and Organic Loading on the Sustainability of Simultaneous Nitrification and Denitrification. Sustainability. 2023; 15(22):15689. https://doi.org/10.3390/su152215689

Chicago/Turabian Style

Yu, Wei-Jia, Ji Sun, Wei-Jia Zhang, Yue Chen, Jun-Ling Yang, Shu-Ping Li, Guang-Can Zhu, and Yong-Ze Lu. 2023. "The Influence of Atmospheric Pressure and Organic Loading on the Sustainability of Simultaneous Nitrification and Denitrification" Sustainability 15, no. 22: 15689. https://doi.org/10.3390/su152215689

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