Abstract
Optimizing dissolved oxygen (DO) distribution is critical for enhancing nitrogen removal in oxidation ditch systems, yet requires robust statistical validation. This study investigates the impact of strategic aerator positioning on biological treatment performance using a pilot-scale oxidation ditch treating municipal wastewater. Three distinct aeration configurations were systematically evaluated across successive operational cycles. Performance was rigorously assessed using SPSS for Pearson correlation, ANOVA, and post-hoc LSD tests.The results revealed a tightly coupled relationship between ammonium (NH₄⁺) and total nitrogen (TN) removal (r = 0.972, p < 0.01). A key finding was the achievement of a high total nitrogen (TN) removal efficiency, reaching 80% in the optimized third cycle. However, a significant inverse correlation was identified between maximizing TN removal and the calculated SND efficiency (r = –0.899, p < 0.01), indicating a critical functional trade-off. ANOVA confirmed that modifying the aeration strategy yielded statistically significant improvements in performance across the cycles (p < 0.001), with a dominant effect size (η2 ≈ 0.89).This study statistically validates that simple, low-cost adjustments to aerator configuration can fundamentally enhance nitrogen removal efficiency. The findings provide a data-driven framework for designing more effective and sustainable decentralized wastewater treatment systems.
Keywords: Wastewater treatment, Dissolved oxygen (DO), Nitrogen removal efficiency, Oxidation ditches, Statistical analysis
Subject terms: Chemistry, Engineering, Environmental sciences
Introduction
Eutrophication remains one of the most pressing environmental challenges to global water resources, primarily driven by excessive nutrient loading—particularly nitrogen and phosphorus—from agricultural runoff, untreated wastewater, and aquaculture effluents. The accumulation of these nutrients stimulates algal blooms, depletes dissolved oxygen (DO), and leads to hypoxic conditions that threaten aquatic biodiversity and water usability1.
To mitigate these effects, biological nitrogen removal has become a core objective in wastewater treatment. Nitrogen in municipal wastewater typically exists in the forms of ammonium (NH₄⁺), nitrite (NO₂⁻), and nitrate (NO₃⁻), and its uncontrolled discharge causes eutrophication and ecological imbalance2. Among the available treatment technologies, Simultaneous Nitrification and Denitrification (SND) offers an energy-efficient alternative by integrating both aerobic and anoxic reactions within a single reactor3,4.
The success of SND processes strongly depends on the spatial distribution of dissolved oxygen. Distinct aerobic and anoxic zones are necessary for the coexistence of nitrifying and denitrifying microorganisms [2, p. 799]. In oxidation ditch systems, such zoning arises naturally from variations in aerator placement, flow velocity, and channel geometry, which create DO gradients along the ditch path5. Aerobic regions near aerators promote the oxidation of ammonium to nitrate, while anoxic regions downstream favor denitrification to nitrogen gas (N₂)6. This spatial DO stratification is essential for achieving simultaneous biological reactions within a single system.
Several studies have confirmed the importance of DO control in optimizing nitrogen removal performance7. demonstrated that functionally dividing the oxidation ditch into aerobic and anoxic zones enhanced SND efficiency and reduced sludge accumulation, achieving total nitrogen removal rates of approximately 60%. Similarly8, reported that maintaining low DO concentrations (0.15–0.25 mg/L) combined with internal recirculation improved total nitrogen removal up to 75%9. found that adjusting the number and arrangement of aerators significantly affected DO distribution, with higher DO levels (2.5–3.0 mg/L) leading to greater COD removal but poorer nitrogen removal efficiency.
Beyond aeration control, other operational factors also influence nitrogen removal efficiency. Adequate organic carbon availability is critical, as denitrifying bacteria require a carbon source for nitrate reduction10. Hydraulic retention time (HRT) has likewise been identified as a key design parameter: longer retention promotes nitrification but increases operational costs, emphasizing the need for optimization11,12. Environmental conditions also play a role; for instance, microbial adaptation under low temperatures—such as the increased abundance of Nitrospira observed by13 can offset performance losses in cold climates.
While numerous studies have examined advanced and often costly control strategies for nitrogen removal14,15, the systematic manipulation of basic, low-cost design parameters—specifically, the physical configuration of aerators and its direct effect on spatial DO gradients—remains insufficiently explored. Addressing this critical gap, the present study provides a novel, practical framework by investigating how sequential aerator repositioning, a simple and economically viable operational adjustment, dictates dissolved oxygen gradients and drives SND efficiency in a pilot-scale oxidation ditch. Utilizing a rigorous statistical approach across three operational cycles, this work demonstrates that strategic aeration positioning, without the need for complex retrofits, is a powerful and standalone tool for achieving high-rate nitrogen removal under resource-limited conditions.
Materials and methodspilot
Plant configuration
A pilot-scale treatment system was developed to assess the influence of aerator configuration on biological nitrogen removal efficiency. The system consisted of three main components: a wastewater collection basin, an oval-shaped oxidation ditch, and a secondary clarifier (Fig. 1). Raw municipal wastewater and the seed sludge used for inoculation were obtained from the wastewater treatment plant located in the Al-Sumaria area of Damascus. Although this plant operates using Sequential Batch Reactors (SBRs), its sludge and raw wastewater were used to initiate and operate the pilot-scale oxidation ditch in this study, due to the unavailability of a local oxidation ditch plant that was used as a seeding source.
Fig. 1.
Schematic diagram of the pilot-scale oxidation ditch showing the eight fixed sampling zones (1–8) and aerator configurations across three operational cycles: (a) Cycle 1—baseline with two aerators at midpoints (red circles); (b) Cycle 2—optimized distribution with aerators near influent/effluent points (blue circles); (c) Cycle 3—enhanced aeration with additional aerator at the curved bend (green circles).
The oxidation ditch was constructed from mild steel plates (80 cm (L) × 30 cm (W) × 25 cm (H)). Aeration was provided by custom-built surface impeller aerators, designed and fabricated locally to overcome the unavailability of commercial models in the local market, while maintaining comparable hydrodynamic performance. The formation of distinct aerobic and anoxic zones—a critical condition for achieving simultaneous nitrification and denitrification (SND)—was verified through direct measurement of dissolved oxygen (DO) gradients at multiple predefined points using a calibrated portable DO meter.
Operational cycles and conditions
The study was conducted over three distinct operational cycles, with the aerator configuration systematically varied to investigate its impact on system performance. Following each change in aerator configuration, a one-week stabilization period was implemented. System stability was confirmed, and experimental data collection began only after effluent ammonia and nitrate concentrations remained within a ± 10% variation over three consecutive days. The configurations were as follows:
Cycle 1 (Baseline): Two aerators were positioned in the middle of the ditch, opposite each other. This baseline configuration was designed to create a symmetrical flow pattern and establish a reference point for system performance.
Cycle 2 (Optimized Distribution): The two aerators were relocated to be near the influent and effluent points. Specifically, the first aerator was placed 15 cm from the inlet, and the second was placed 15 cm from the outlet, aiming to optimize the distribution of aerobic and anoxic zones by aligning mixing energy with the primary flow path.
Cycle 3 (Enhanced Aeration): A third aerator was added to the configuration from Cycle 2. This third aerator was positioned at the center of the ditch’s curved bend to aerate a region identified in Cycle 2 as having a tendency for lower flow velocity and potential oxygen depletion.
System stability was confirmed prior to data collection in each cycle by monitoring the effluent ammonia and nitrate concentrations until variations remained within ± 10% over consecutive days.
Wastewater characteristics
The pilot-scale system was fed with raw municipal wastewater sourced from the Al-Sumaria Wastewater Treatment Plant. The influent characteristics varied across the three operational cycles, reflecting the dynamic nature of real-world wastewater. The average characteristics for each cycle are summarized in Table1.
Table 1.
Average influent wastewater characteristics for each operational cycle (Mean ± SD).
| Parameter | Cycle 1 (April) | Cycle 2 (May) | Cycle 3 (June/July) |
|---|---|---|---|
| BOD (mg/L) | 352.13 ± 14.82 | 365.00 ± 13.86 | 386.08 ± 11.99 |
| TSS (mg/L) | 177.50 ± 8 | 340.00 ± 15.34 | 404.00 ± 9.44 |
| NH₄⁺-N (mg/L) | 48.17 ± 1.19 | 49.00 ± 1.49 | 47.16 ± 1.01 |
| TN (mg/L) | 69.01 ± 1.7 | 68.00 ± 2.8 | 69.10 ± 5.46 |
Sampling and analytical methods
Influent and effluent samples were collected daily for analysis of key water quality parameters. All analytical procedures followed Standard Methods for the Examination of Water and Wastewater16: BOD₅ was measured using the 5-day incubation test (Method 5210B), NH₄⁺-N was determined by the phenate method (Method 4500-NH₃ C), and NO₃⁻-N was analyzed by ultraviolet spectrophotometric screening method (Method 4500-NO₃⁻ B).
Results and discussion
The critical role of spatial DO distribution in driving SND
The findings of this study clearly demonstrate that aerator placement within the oxidation ditch plays a significant impact in shaping the spatial distribution of dissolved oxygen (DO), which in turn governs the extent of simultaneous nitrification–denitrification (SND). The controlled manipulation of aerator position established distinct functional microenvironments along the flow path, effectively creating aerobic, anoxic, and anoxic zones within a single reactor.
Zone classification and quantification
Spatial DO profiles were measured at five equidistant points along the ditch during each operational cycle. The results confirmed a clear redox stratification:
Aerobic zone: DO ≥ 1.5 mg/L, dominated by nitrification (mainly Nitrosomonas and Nitrospira).
Anoxic zone: DO < 1mg/L, facilitating denitrification by Pseudomonas and Paracoccus.
This classification aligns with previous observations by9, who reported effective simultaneous nitrification and denitrification (SND) at DO levels between 0.5 and 1.5 mg/L, achieving 68% total nitrogen removal. In contrast17, demonstrated that a DO concentration of 0.5 mg/L was optimal for achieving a high SND efficiency of 88.51% in an IFAS system, as it facilitated the formation of anoxic micro-zones within the biofilm and enriched denitrifying microbial communities. Furthermore, these findings are supported by8, who showed that maintaining low DO levels (0.15–0.25 mg/L) in a modified Orbal ditch enhanced total nitrogen removal up to 75%, underscoring the importance of balanced DO distribution in optimizing SND performance.
Cycle 1 – baseline performance
In the first operational cycle, the two aerators were positioned at the midpoint of the ditch, as illustrated in Fig. 1a. This arrangement, as shown by the resulting DO profile in Fig. 2, created a distinct oxygen gradient where the concentration peaked near the aeration wheels and sharply declined with increasing distance. This severe oxygen heterogeneity resulted in excessive anoxic volumes (VDN/VAT ≈ 0.5). As a consequence, ammonia accumulation was observed, with effluent NH₄⁺ exceeding 15 mg/L. Similar issues of localized oxygen depletion were previously reported by18, who noted that non-uniform aeration leads to poor nitrification and unstable nitrogen removal.
Fig. 2.
Illustrates the spatial distribution of DO, NH₄⁺–N, and NO₃⁻–N during Cycle 1, with error bars representing ± SD of triplicate measurements.
Cycle 2 – Improved DO homogeneity
Since the first operational cycle produced limited performance due to oxygen imbalance between aerated and anoxic regions, the second cycle aimed to improve nitrification efficiency by enhancing DO distribution. To achieve this, the aerators were repositioned near the influent and effluent points (15 cm from each end) to reduce the size of dead anoxic zones, as shown in Fig. 1b.
This modification enhanced DO uniformity (average DO = 1.03 ± 0.88 mg/L) and reduced the anoxic volume fraction (VDN/VAT ≈ 0.4). However, ammonium levels remained elevated (8–10 mg/L), indicating that while distribution improved, the total oxygen input was still insufficient for complete nitrification (Fig. 3). This finding is consistent with19, who emphasized that both DO magnitude and distribution must be balanced to achieve high SND efficiency. Similarly11, reported that extended aeration improves sludge stability and nitrogen removal efficiency by ensuring uniform oxygen availability across the reactor.
Fig. 3.
Shows the improved DO uniformity and partial recovery of nitrification following aerator repositioning.
Cycle 3 – optimized aeration and enhanced SND
Although performance improved in Cycle 2, it did not reach optimal conditions—particularly in Zone 6 (Fig. 3). Therefore, a third aerator was added in that area during the third cycle (Fig. 1c), a design modification intended to enhance both hydraulic and oxygen mixing.
The optimized aeration configuration produced a pronounced DO gradient spanning from 0.2 mg/L (anoxic) to approximately 2.5 mg/L (aerobic) with an average of 1.38 ± 0.89 mg/L, creating the redox heterogeneity necessary for efficient SND and 80% TN removal. The strong coupling between aerator configuration and zone functionality was supported by the observed correlation between NH₄⁺ oxidation and NO₃⁻ reduction profiles (Fig. 4). This finding aligns with the CFD modeling work of20, which demonstrated that optimized aerator placement creates the dissolved oxygen gradients and redox heterogeneity required to enhance Simultaneous Nitrification and Denitrification (SND), while also reducing energy consumption.
Fig. 4.
Presents the final optimized aeration pattern, displaying the stable DO gradient and synchronized NH₄⁺/NO₃⁻ profiles.
Taken as a whole, these findings support the conclusion that achieving high SND efficiency is not necessarily reliant on complex reactor geometries or costly structural retrofits. Instead, strategic aeration positioning and operational flexibility are powerful, low-cost tools for optimizing biological nitrogen removal. This is consistent with modern gradient-based design philosophies that leverage controlled oxygen microenvironments to promote energy-efficient nutrient removal17. Ultimately, simple operational tuning—specifically aerator redistribution—can yield performance comparable or superior to multi-stage systems, offering a sustainable and economically viable solution for small and medium-sized wastewater treatment facilities.
BOD removal and denitrification relationship
Beyond its effects on nitrogen species, the operational adjustments also influenced the removal of organic matter (BOD₅). A noticeable improvement in BOD removal efficiency was observed from Cycle 1 to Cycles 2 and 3, corresponding with enhanced denitrification performance. In such systems, denitrifying bacteria utilize influent organic matter (BOD) as a carbon source for nitrate reduction2. Therefore, the improved anoxic conditions in later cycles allowed more of the total BOD to be removed via denitrification—an added benefit of optimizing the DO profile.
System performance and pollutant removal efficiency
The strategic modifications to aeration not only optimized nitrogen removal but also markedly enhanced the overall treatment efficiency of the oxidation ditch. In the first cycle, the system demonstrated a respectable baseline performance, achieving 81% removal for biochemical oxygen demand (BOD₅) and 79% for total suspended solids (TSS) (Fig. 5).
Fig. 5.
Influent and effluent concentrations of BOD, TSS, NH₄⁺, and TN during Cycle 1. (b) Pollutant removal efficiencies for BOD, TSS, NH₄⁺, and TN in Cycle 1. Error bars represent the standard deviation of the mean (n = 8).
The observed performance occurred despite natural variations in the influent characteristics, a common feature of real municipal wastewater streams. This variability, particularly in TSS concentrations, is reflected in the standard deviation error bars presented in the figures. Importantly, the system maintained effective treatment despite these fluctuations, demonstrating its operational robustness.
While effective for carbon and solids removal, this initial setup was clearly insufficient for nitrogen treatment, with NH₄⁺ and TN removal efficiencies lagging significantly. Following the operational adjustments in the second cycle, the system was allowed a one-week acclimatization period to reach stability. Subsequent analysis confirmed significant improvements in nitrogen-related metrics compared to the first cycle. As shown in Fig. 6, the ammonium (NH₄⁺) removal efficiency rose to 65% from 55% in the previous cycle.
Fig. 6.
Influent and effluent concentrations of BOD, TSS, NH₄⁺, and TN during Cycle 2. (b) Pollutant removal efficiencies for BOD, TSS, NH₄⁺, and TN in Cycle 2. Error bars represent the standard deviation of the mean (n = 17).
This improvement directly reflects enhanced nitrifying bacterial activity, resulting from a more homogeneous distribution of dissolved oxygen. The third cycle marked a turning point, with the system demonstrating improved biological activity (Fig. 7). TN removal efficiency reached 80%, indicating a functionally integrated microbial activity.
Fig. 7.
Influent and effluent concentrations of BOD, TSS, NH₄⁺, and TN during Cycle 3. (b) Pollutant removal efficiencies for BOD, TSS, NH₄⁺, and TN in Cycle 3. Error bars represent the standard deviation of the mean (n = 13).
These findings align with those of21, who demonstrated that implementing intermittent aeration in municipal treatment plants improved TN removal by up to 57% without requiring major infrastructural changes. The efficacy of aeration control is further demonstrated by22, who achieved ultra-low effluent TN concentrations (below 1 mg/L) in an innovative biological aerated filter (I-BAF) through aeration optimization, underscoring its c essential contribution across different reactor configurations.
Figure 7 clearly illustrates the evolution of nitrogen removal efficiency across the three cycles, showing a direct and positive correlation between improved aeration distribution and TN removal. Crucially, this high level of performance was achieved not through advanced technologies or capital-intensive upgrades, but through a straightforward and cost-effective adjustment—adding a single aerator—based on analysis of previous operational data. This strongly demonstrates that redesigning air distribution within existing biological systems is, in itself, a highly effective and cost-efficient tool for performance optimization. While this study focused on the pivotal role of dissolved oxygen (DO) distribution, it is acknowledged that overall treatment efficiency is multifactorial.
Microbial diversity and functionality are paramount. As noted by23, synergistic interactions between microbial groups—such as denitrifiers and phosphorus-accumulating organisms—are vital for robust nutrient removal and system resilience. Furthermore, advanced solutions such as coupling biological treatment with Advanced Oxidation Processes (AOPs) can achieve even greater pollutant degradation. However, as highlighted by24, such approaches require careful balancing due to increased operational complexity and cost. The strength of the approach validated in this study lies in its simplicity, sustainability, and practical effectiveness, making it a relevant solution for broader application.
Statistical validation of system performance
Pearson correlation analysis
To rigorously quantify the relationships between performance indicators and validate the impact of operational changes, a comprehensive statistical analysis was conducted. A Pearson correlation matrix was generated to assess the interdependencies between key performance indicators (Table 2), following the approach widely used in wastewater treatment studies25
Table 2 .
Statistically significant Pearson correlations between key performance indicators.
| Variable Pair | Pearson’s *r* | *p*-value | N | Biological Interpretation |
|---|---|---|---|---|
| TN Removal vs. NH₄⁺ Removal | 0.972 | < 0.001 | 38 | Confirms ammonium oxidation as the rate-limiting step for total nitrogen elimination |
| NH₄⁺ Removal vs. BOD₅ Removal | 0.680 | < 0.001 | 38 | Links organic carbon availability to nitrifier activity and growth |
| TN Removal vs. SND Efficiency | −0.899 | < 0.001 | 38 | Reflects the effective conversion of nitrogen to N₂ gas via denitrification, which is not measured in the TN effluent concentration |
| NH₄⁺ Removal vs. SND Efficiency | −0.776 | < 0.001 | 38 | Indicates a metabolic trade-off where conditions favoring the simultaneous pathway can reduce the efficiency of the conventional nitrification pathway |
All presented correlations are statistically significant (p < 0.001).
TN Removal vs. NH₄⁺ Removal 0.972 < 0.001 38 Confirms ammonium oxidation as the rate-limiting step for TN elimination.
NH₄⁺ Removal vs. BOD₅ Removal 0.680 < 0.001 38 Links organic carbon availability to nitrifier activity.
TN Removal vs. SND Efficiency −0.899 < 0.001 38 Reflects competitive inhibition: Higher SND diverts nitrogen from TN measurement pathways.
NH₄⁺ Removal vs. SND Efficiency −0.776 < 0.001 38 Indicates metabolic trade-off between conventional nitrification and simultaneous pathways.
The analysis revealed a highly significant positive correlation between total nitrogen (TN) and ammonium (NH₄⁺) removal efficiencies, confirming that overall nitrogen elimination is closely coupled with the initial nitrification step. Furthermore, a moderate positive correlation was observed between NH₄⁺ and BOD₅ removal, reflecting the metabolic synergy of aerobic microbial communities processing both organic carbon and nitrogen simultaneously.
Interestingly, a strong inverse correlation was identified between effluent TN concentration and measured SND efficiency (r = –0.899, p < 0.001). This relationship is logical: as SND efficiency increases, more nitrogen is converted to nitrogen gas (N₂) and removed from the system, leading to a lower total nitrogen (TN) concentration in the effluent. This confirms that high SND efficiency is a direct indicator of effective overall nitrogen removal, a finding consistent with25, who demonstrated that optimized SND under controlled DO conditions enhances nitrogen removal performance.
Descriptive statistics and impact of operational cycles (ANOVA)
A descriptive overview of the system’s performance is presented in Table 3, showing progressive improvements across all metrics.
Table 3 .
Descriptive statistics of key pollutant removal efficiency indicators across the study period.
| Indicator | Mean ± SD (%) | Min–Max (%) | Median (%) |
|---|---|---|---|
| TN Removal Efficiency | 22.87 ± 7.53 | 11.08–35.62 | 23.83 |
| NH₄⁺ Removal Efficiency | 14.43 ± 6.15 | 4.61–22.40 | 16.56 |
| BOD₅ Removal Efficiency | 47.99 ± 7.36 | 36.90–57.60 | 49.10 |
| SND Efficiency | 74.04 ± 9.52 | 53.48–86.21 | 77.15 |
SD = Standard Deviation; TN = Total Nitrogen; BOD₅ = Five-day Biochemical Oxygen Demand; SND = Simultaneous Nitrification and Denitrification.
A one-way Analysis of Variance (ANOVA) confirmed that the improvements across the three operational cycles were statistically significant (F(2, 35) = 138.58, p < 0.001; Table 4). The calculated effect size (η2 ≈ 0.89) clearly indicates the influence of strategic operational changes on TN removal. This is substantiated by26, who demonstrated that intermittent aeration elevated nitrogen removal efficiency from 60.5% to 77.9%. Moreover27, provide comprehensive support through a review of aeration control strategies, affirming that optimized approaches not only enhance nutrient removal but also yield energy savings of up to 40% in full-scale wastewater treatment plants.
Table 4.
One-Way ANOVA results for total nitrogen (TN) removal efficiency across the three operational cycles.
| Source of Variation | Sum of Squares | df | Mean Square | F-value | p-value |
|---|---|---|---|---|---|
| Between Groups | 1861.412 | 2 | 930.706 | 138.580 | < 0.001 |
| Within Groups | 235.060 | 35 | 6.716 | ||
| Total | 2096.472 | 37 |
The p-value < 0.001 indicates that the differences in TN removal efficiency between the operational cycles are statistically significant at a 95% confidence level.*.
Pinpointing performance gains (LSD Post-Hoc Test)
A Least Significant Difference (LSD) post-hoc test quantified specific improvements between cycles (Table 5). Each successive cycle showed a statistically significant enhancement (p < 0.001), with Cycle 3 achieving the highest performance (+ 19.34% over Cycle 1). These results are aligned with28, who reported improved SND performance in low DO environments using advanced biofilm carriers.
Table 5 .
Post-hoc LSD pairwise comparisons for total nitrogen (TN) removal efficiency between operational cycles following a significant one-way ANOVA.
| Comparison | Mean Difference (%) | Std. Error | *p*-value | 95% Confidence Interval |
|---|---|---|---|---|
| Cycle 1 vs. Cycle 2 | + 8.94 | 1.101 | < 0.001 | 6.71 to 11.18 |
| Cycle 1 vs. Cycle 3 | + 19.34 | 1.183 | < 0.001 | 16.93 to 21.74 |
| Cycle 2 vs. Cycle 3 | + 10.39 | 0.966 | < 0.001 | 8.43 to 12.35 |
The mean difference is significant at the 0.05 level for all comparisons.
Hypothesis validation
The statistical analyses strongly support the study’s core hypotheses. Cycle 3 delivered a significantly superior TN removal compared to Cycles 1 and 2, supporting the hypothesis that strategic aerator positioning is a primary driver of nitrogen removal performance.
These findings are consistent with8,9, and11, all of whom highlighted the important role of DO distribution and aeration strategies in achieving high TN removal and system stability. This convergence validates that incremental improvements in aeration distribution foster effective functional zones, enhancing TN removal—particularly evident in Cycle 3, which recorded the peak performance across all operational indicators.
In conclusion, the statistical findings substantiate the central thesis: careful manipulation of dissolved oxygen distribution is a powerful and effective tool for optimizing reactor biology and nitrogen removal. Nevertheless, these results should be interpreted with caution, as seasonal variations and long-term climatic effects were not assessed and represent avenues for future research.
Conclusion
This study confirms that strategic management of dissolved oxygen (DO) distribution is a highly effective and practical approach for improving nitrogen removal in oxidation ditch systems. Through the systematic optimization of aerator placement across three operational cycles, the system achieved simultaneous nitrification–denitrification (SND) efficiencies, with total nitrogen removal reaching 80%. Statistical validation revealed that these improvements were highly significant (p < 0.001), with the aeration strategy accounting for approximately 89% of the observed performance variance (η2 ≈ 0.89). Importantly, the findings uncover a functional trade-off between maximizing TN removal and maintaining SND process synchrony—highlighting the need for balanced optimization strategies. Moving forward, the study recommends implementing dynamic and spatially targeted aeration to improve nitrogen removal while conserving energy. Designing functional zones within oxidation ditches can better support distinct biological processes, while incorporating seasonal and climatic factors will refine the applicability of aeration protocols. Real-time DO monitoring and adaptive control systems should be deployed to stabilize performance at full scale, and pilot-scale trials in developing regions are encouraged to validate the cost-effectiveness and adaptability of this model. Altogether, these insights offer a scalable, low-cost framework for enhancing biological nutrient removal in decentralized wastewater treatment contexts.
Acknowledgements
This manuscript is derived from the first author’s Master’s thesis submitted to Damascus University. The author gratefully acknowledges the invaluable support and guidance provided by Dr. Ghassan Durra Al-Haddad, the thesis supervisor, and Dr. Bassam Al-Aji, whose assistance was instrumental not only in the research process but also in identifying a suitable journal for publication. Their insights, encouragement, and continued support greatly contributed to the success of this study. The authors declare that there are no financial or non-financial conflicts of interest related to the publication of this work.
Author contributions
R.N.D. conceived and designed the study, performed all experiments, analyzed the data, and wrote the manuscript. G.D.A. supervised the research and provided guidance during the study. All authors approved the final version of the manuscript.
Data availability
The datasets generated and/or analysed during the current study are not publicly available due to institutional restrictions imposed by Damascus University, but are available from the corresponding author on reasonable request.
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analysed during the current study are not publicly available due to institutional restrictions imposed by Damascus University, but are available from the corresponding author on reasonable request.