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Article

Achieving High-Efficiency Wastewater Treatment with Sequencing Batch Reactor Grundfos Technology

by
Tomasz Sionkowski
1,
Wiktor Halecki
2,*,
Paweł Jasiński
1 and
Krzysztof Chmielowski
3
1
Grundfos Pompy Ltd., Klonowa Street 23, 62-081 Przeźmierowo, Poland
2
Institute of Technology and Life Sciences—National Research Institute, Falenty, Al. Hrabska 3, 05-090 Raszyn, Poland
3
Department of Natural Gas Engineering, Faculty of Drilling, Oil and Gas, AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland
*
Author to whom correspondence should be addressed.
Processes 2025, 13(4), 1173; https://doi.org/10.3390/pr13041173
Submission received: 15 February 2025 / Revised: 26 March 2025 / Accepted: 5 April 2025 / Published: 12 April 2025
(This article belongs to the Special Issue Novel Recovery Technologies from Wastewater and Waste)
Browse Figures
Review Reports Versions Notes

Abstract

:
Sequencing batch reactor Grundfos technology (SBR-GT) system efficiently treats municipal and selected industrial wastewater, designed for small and medium-scale facilities. It offers advanced solutions for biodegradable wastewater, including municipal and food industry effluents. Important features include stable sedimentation under fluctuating influent conditions, no need for sludge recirculation, and full process automation. The system uses a static decanter and constant chamber filling for optimal oxygenation efficiency and reduced costs. The system uses a static decanter and constant chamber filling for optimal oxygenation efficiency and reduced costs. It is ideal for small settlements with variable inflow, such as towns, allowing flexible operation and cost-effective maintenance. Implementations showed stable parameters for COD (chemical oxygen demand), BOD5 (biochemical oxygen demand), total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP) and up to 99% pollutant reduction, demonstrating high effectiveness in regular and stormwater conditions. Using multivariate multiple linear regression, significant relationships were identified. A multiple regression analysis revealed a strong relationship between water quality parameters. Total suspended solids, Total nitrogen, and Total phosphorus collectively and significantly influenced both chemical oxygen demand and biochemical oxygen demand (p < 0.01 for all). The models explained a high proportion of variance, with R2 values of 0.99 for COD and 0.93 for BOD5 (p < 0.001 for both). Specifically, TSS had a strong positive effect on COD (p < 0.001), while TN and TP also significantly affected COD (p < 0.01). Although the overall BOD5 model was highly significant, the individual effects of TSS, TN, and TP on BOD5 were not statistically significant in this model. This method demonstrated high effectiveness in both regular and stormwater conditions, enhancing overall treatment performance.

1. Introduction

Sequencing batch reactor (SBR) technology has emerged as a significant advancement in wastewater treatment, demonstrating diverse applications across various industries. Recent studies focus on its efficiency, modifications, and integration with other technologies to enhance performance [1,2]. Researchers have compared sewage sludge from treatment plants using MBR (membrane bioreactor) and SBR technologies, noting the potential for sustainable environmental applications [3,4,5]. Case studies have evaluated the performance of SBR and ASBR (anaerobic sequencing batch reactor) wastewater treatment plants, along with comparative analyses of SBR and SBR-IFAS (sequencing batch reactor integrated fixed-film activated sludge) processes for treating common effluent treatment plant [6,7]. Moreover, recent research on hybrid systems incorporating SBR has shown promising results. For instance, a combination of GAC SBR (granular activated carbon sequencing batch reactor) was used to treat leather wastewater with the help of a novel flocculant, enhancing treatment efficiency [8]. Similarly, co-treatment of stabilized landfill leachate and municipal wastewater using a granular activated carbon-SBR system has highlighted advancements in integrated technologies for complex wastewater streams [9]. Another significant area of focus is the microbial dynamics within SBR systems. Researchers have evaluated microbial communities in bioaugmented SBRs treating aniline wastewater, providing insights into microbial function during the start-up phase [10]. Reviews of SBR technology for landfill leachate treatment have also addressed microbial behavior and the potential for bioaugmentation to improve system performance [11]. Innovations in SBR performance optimization have been explored, focusing on improving simultaneous N, P, and C removal in an anaerobic-aerobic-anoxic SBR treating municipal wastewater. Additionally, dynamic compartmental models to enhance biological phosphorus removal in SBR systems offer a promising approach for future wastewater treatment designs. Studies emphasize the effectiveness of SBR technology in treating a variety of wastewater, from municipal and industrial to more specific types such as landfill leachate and leather wastewater [12]. As the field evolves, ongoing research continues to refine operational parameters, microbial management, and integration with other treatment processes, offering significant potential for more sustainable and cost-effective wastewater management solutions [13,14,15]. In recent years, the application of sequencing batch reactors in wastewater treatment has garnered considerable attention due to their ability to treat a wide range of wastewater types, including municipal, industrial, and landfill leachates.
Studies show that modifications and optimizations of SBRs can significantly enhance their performance in terms of nutrient removal, organic matter degradation, and sludge management. Organically rich wastewater has significant potential for yielding biohydrogen, with productivity influenced by nanoparticle concentration, size, pH, and temperature. Nanotechnology provides innovative solutions to address challenges in biohydrogen yield, utilizing nanomaterials with unique properties such as high surface-area-to-volume ratio, reactivity, and enhanced catalytic activity [16,17]. One such modification involves altering operational parameters like organic loading rates and dissolved oxygen levels to improve nitrogen, phosphorus, and carbon removal efficiency [18]. Furthermore, SBR technology is increasingly utilized for specialized applications such as leather wastewater treatment [19] and landfill leachate treatment, where the presence of specific contaminants requires customized treatment strategies. In some studies, integrating SBR with other processes like reverse osmosis or electro-enhanced systems has shown promising results for improving pollutant removal and achieving regulatory compliance [20,21]. In addition to environmental benefits, the operational cost-effectiveness of SBRs has been a focal point of recent research [22]. Optimizing operational parameters, such as aeration cycles and hydraulic retention time, can lead to both energy savings and improved treatment efficiency [23,24]. However, challenges still exist in terms of achieving rapid start-up and controlling microbial communities in the system [25], suggesting that further innovation in this field is essential for advancing the technology [26,27,28,29].
The use of sequencing batch reactor technology has become increasingly prominent in various wastewater treatment applications, with significant advancements made in optimizing its performance. A primal area of focus has been enhancing ammonium removal, especially in challenging environments such as landfill leachate. Recent studies have shown that employing either dispersed or attached biomass in SBR systems significantly impacts the efficiency of ammonium removal, with specific configurations providing better treatment outcomes [30]. In the petroleum industry, the application of SBR technology has also seen notable development. Researchers have focused on improving the design and operational parameters of SBRs to treat petroleum industry wastewater more effectively, addressing issues like high pollutant loads and complex chemical compositions [26]. These modifications are essential for achieving compliance with stringent environmental standards while maintaining operational efficiency. The SBR technology’s versatility is also evident in its application in Vietnamese wastewater treatment systems, where it has been assessed for its ability to handle various types of municipal wastewater. The evaluation indicated that SBR can be a reliable option for managing the country’s wastewater challenges, offering both flexibility and cost-effectiveness [31]. One of the most exciting advancements in SBR technology has been the improvement of nitrogen removal processes, particularly through the simultaneous nitrification and denitrification process. Recent studies have demonstrated that alternating dissolved oxygen levels in an oxygen-limited SBR can optimize nitrogen removal, significantly enhancing the system’s overall performance [32]. Furthermore, innovations like intermittently aerated SBRs have shown superior nitrogen removal capabilities compared to conventional SBRs, especially when treating specific types of wastewater, such as digested piggery wastewater [33].
This study highlights the innovative performance of a new wastewater treatment system tailored for small-scale applications, tackling complex challenges in municipal areas with emerging contaminants. The objectives of the study were (a) Assessing the usability of the sequencing batch reactor Grundfos technology; (b) Evaluating reductions in oxygen indicators (COD, BOD), total nitrogen, total phosphates, and total suspended solids concentrations; (c) Modeling flow patterns within the chamber of the newly developed wastewater treatment tank.

2. Materials and Methods

2.1. Technological Approaches in Sequencing Batch Reactors for Enhanced Landfill Leachate Treatment

This study employed the sequencing batch reactor Grundfos technology for the efficient and economical treatment of municipal and selected industrial wastewater in medium- and small-scale facilities. The system was suitable for both newly designed and modernized treatment plants, ensuring effective wastewater management in diverse applications. The SBR-GT was characterized by its ability to adapt to varying influent conditions, including changes in influent volume and composition. The treatment process was fully automated, offering ease of operation and consistent results, without the need for sludge recirculation. The SBR-GT was designed to ensure stable sedimentation, enabling precise control of the treatment cycle (Figure 1). Municipal wastewater is collected from households, businesses, and other urban areas and then transported to treatment plants for processing.
The wastewater from the buffer tank is pumped into the SBR reaction chamber in a manner that does not disturb the sediment layer accumulated at the bottom of the chamber after sedimentation. The incoming wastewater raises the liquid level, causing the treated wastewater to overflow into the static decanter, from where it is discharged to the receiving environment (Figure 2A). The mixing of raw wastewater with concentrated sludge promotes intensive anaerobic and anoxic processes, ensuring effective biological defosfitation and denitrification processes, while also improving the sedimentation capabilities of the sludge (anaerobic selector).
After filling the SBR reactor (Grundfos Pompy Ltd., Międzyrzec Podlaski, Poland) with a new batch of sewage, the reaction phase begins. Alternating mixing and aeration of the entire tank contents effectively reduces the contaminants in the sewage to the required level. The aeration process is controlled to optimize electricity consumption. In the final period of the reaction phase, it is possible to add chemicals to adjust pH and precipitate phosphorus (Figure 2B). Upon the completion of the treatment process, the aeration and mixing systems are halted, and the sedimentation process begins. During the final period of sedimentation, the submersible pump removes part of the thickened sludge from the bottom of the chamber as excess sludge. Once the sedimentation process is finished, the system enters a new cycle by simultaneously filling with a new batch of raw sewage and removing a batch of treated sewage (Figure 2C).

2.2. Chemical Analysis in Technological Approaches in Sequencing Batch Reactors

Samples were collected from both raw and treated wastewater at the sewage treatment plant in Międzyrzec Podlaski in Eastern Poland. Treated sewage, on the other hand, was collected from the reactor’s outflow trough. Samples were collected on an average daily basis. Forty samples were collected for each indicator. The wastewater samples underwent a thorough analysis to assess key parameters crucial for evaluating treatment efficiency and environmental impact, following internationally recognized standardized methods to ensure accuracy and comparability of results. The biochemical oxygen demand, determined using PN-EN ISO 5815-1:2019-12, reflects the amount of oxygen required by microorganisms to biologically degrade organic matter over five days, serving as an indicator of organic pollution [34]. The chemical oxygen demand, measured in accordance with PN-ISO 15705:2005, quantifies the total oxygen demand needed to chemically oxidize both biodegradable and non-biodegradable organic substances, providing insight into the overall pollution load [35]. The pH level, evaluated usingThe wastewater samples underwent a thorough analysis to assess key parameters crucial for evaluating treatment efficiency and environmental impact, following internationally recognized standardized methods to ensure accuracy and comparability of results. The biochemical oxygen demand, determined, reflects the amount of oxygen required by microorganisms to biologically degrade organic matter over five days, serving as an indicator of organic pollution. The chemical oxygen demand, quantifies the total oxygen demand needed to chemically oxidize both biodegradable and non-biodegradable organic substances, providing insight into the overall pollution load. The pH level, evaluated using PN-EN ISO 10523:2012, is critical for monitoring the acidity or alkalinity of wastewater, as extreme pH levels can disrupt biological processes in treatment systems [36]. Lastly, the total suspended solids, analyzed as per PN-EN 872:2007+A1:2007, represent the concentration of particulate matter suspended in the water, including organic and inorganic components, which directly influences the clarity and quality of treated water [37].

2.3. Statistical Analysis and Computational Fluid Dynamics

Multivariate multiple linear regression analyzed the effects of total suspended solids, total nitrogen, and total phosphorus, on chemical oxygen demand and biochemical oxygen demand. This method accounted for interdependencies among water quality parameters, providing a comprehensive understanding of their combined impact. Multivariate multiple linear regression improved efficiency and accuracy by considering all variables in a single model, reducing the risk of Type I errors. Detailed statistical insights, including coefficients, standard errors, t-values, and p-values, were obtained. We compared water quality indicators (COD, BOD, TSS, TN, and TP) across different treatment methods using a statistical test called Multivariate analysis of variance (MANOVA). This test uses a Wilks’ lambda to see if there are significant differences between the groups. The smaller Wilks’ lambda value indicates a greater difference. Data were analyzed for all monthly samples in the year period using the PaSt program, version 4.17 [38]. The model for streamline and velocity distribution was supported by CFD (Computational Fluid Dynamics) using ANSYS Fluent software version 14.5 to simulate the flow of water within the basin. The software calculates the velocity of water at various points within the basin, taking into account factors inclusing turbulence, flow resistance, and the influence of internal structures. The water velocity distribution within the treated basin was visualized using a 3D streamline plot. The color scale ranged from blue (indicating low velocity) to red (indicating high velocity). Streamlines illustrated the flow patterns within the rectangular basin, with higher velocity areas shown in red and lower velocity areas in blue. The plot provided a scale at the bottom, indicating the distance in meters.

3. Results

3.1. Analysis of Wastewater Treatment Parameters and Efficiency

The significant reduction in COD from 1263.0 mg/dm3 in raw wastewater to 28.8 mg/dm3 in treated wastewater indicated effective treatment. BOD5 measured the oxygen required for microbial decomposition of organic matter over five days, with a reduction from 382.5 mg/dm3 to 55 mg/dm3 in treated wastewater. Total suspended solids, which measured solids suspended in water, showed a reduction from 577.5 mg/dm3 to 4.48 mg/dm3, indicating improved water clarity and quality. Furthermore, total nitrogen, encompassing all forms of nitrogen in the water, was reduced from 106.9 mg/dm3 in raw wastewater to 11.63 mg/dm3 in treated wastewater. This reduction was crucial for preventing eutrophication in water bodies. Total phosphorus, which included all forms of phosphorus present in the water, was reduced from 18.93 mg/dm3 to 0.54 mg/dm3 in treated wastewater (Table 1).
The SBR-GT system features a 20% smaller volume (2 × 1010 m3) compared to alternatives, which significantly reduces investment costs. It achieves a 19% reduction in aerobic oxygen requirement, reaching 25.5 kg/h, and a 13% increase in standard oxygen transfer efficiency, achieving 34.6%. The air/pump flow rate has been reduced by 28% to 596 Nm3/h, while energy consumption has decreased by 13%, now totaling 560 kWh. Additionally, the system employs an ES65/2-P 22 kW motor, further lowering investment costs. These advancements collectively result in estimated annual energy savings of at least 4000 Euros (Table 2).
The presented data provide a thorough analysis of the impact of various water quality parameters, including total suspended solids, total nitrogen, and total phosphorus, on chemical oxygen demand and biochemical oxygen demand. Significant relationships were identified using multivariate multiple linear regression, with highly significant p-values for total suspended solids (p = 0.0002), total nitrogen (p = 0.0017), and total phosphorus (p = 0.0005), indicating strong statistical significance. For chemical oxygen demand, total suspended solids (coefficient = 1.259, p < 0.001) and total nitrogen (coefficient = 6.445, p = 0.0009) showed significant positive coefficients, suggesting that increases in these variables are associated with higher chemical oxygen demand. Total phosphorus (coefficient = −5.792, p = 0.0001) exhibited a negative coefficient, indicating an inverse relationship. For biochemical oxygen demand, total suspended solids (coefficient = 0.282, p = 0.165) and total nitrogen (coefficient = 2.356, p = 0.138) did not show significant coefficients, while total phosphorus (coefficient = −1.290, p = 0.223) demonstrated a negative coefficient. The results are summarized in Table 3.
Total phosphorus displayed a broad distribution, indicating variability in reduction percentages, with a median around 95%. Total nitrogen also exhibited variability, with a median reduction percentage around 93%. Total suspended solids had a narrower distribution, suggesting more consistent reduction, with a median near 90%. Biochemical oxygen demand presented a wide range of reduction percentages, with the median around 92%. Chemical oxygen demand demonstrated a more consistent reduction percentage, with the median around 94% (Figure 3).

3.2. The Simulation Results Visualized Using Streamline Plots

Using the collected data, a computational model of the treated basin was created. The model includes all the relevant components of the basin, such as inflow points, outflow points, and any internal structures such as baffles or aeration systems. The image visualizes the water velocity distribution within a treated basin using a 3D streamline plot. The color scale ranges from blue (indicating low velocity) to red (indicating high velocity). Streamlines illustrate the flow patterns within the rectangular basin, with higher velocity areas shown in red and lower velocity areas in blue. The plot provides a scale at the bottom, indicating the distance in meters. The treated basin was divided into two compartments: a settling or sedimentation tank on the left and a compartment with a perforated floor on the right, possibly for aeration or filtration. The entire setup included various pipes and equipment, showcasing a water treatment process (Figure 4).
The treated basin was divided into two compartments: a settling or sedimentation tank on the left and a compartment with a perforated floor on the right, possibly for aeration or filtration. The entire setup included various pipes and equipment, demonstrating the water treatment process. Both plots have areas of low velocity (blue), indicating potential sedimentation zones where particles could accumulate. The left plot showed a higher concentration of high-velocity regions (red and orange) near the top, while the right plot shows a more dispersed distribution of velocities with fewer high-velocity regions (Figure 5).

4. Discussion

4.1. Optimizing Flow Patterns in Waste Treatment and Technology

The study on sequencing batch reactors for landfill leachate treatment introduces new processes, including integrated treatment technologies combining anaerobic and aerobic processes for simultaneous nitrification, denitrification, and phosphorus removal. It also highlights advanced configurations using various materials and techniques to enhance treatment efficiency, along with improved operational flexibility to handle variable loads and ensure high biomass retention [39].
The SBR-GT efficiently treats municipal and selected industrial wastewater, making it ideal for medium and small-scale facilities, including tourist towns. It features flexible operation under varying inflow and pollutant loads, full process automation, and stable sedimentation without the need for sludge recirculation. The system’s design, with a static decanter and constant chamber filling, optimizes oxygenation efficiency and reduces investment costs by maximizing chamber volume use (Figure 1). To optimize the SBR for BOD and TSS reduction, the study emphasized efficient TSS removal during primary treatment, leading to reduced organic load, lower oxygen demand, and energy savings. Filtration using fine mesh sieves (1.2 µm to 150 µm) improved COD removal and required less oxygen, enhancing overall process efficiency [40].
High velocity areas may also suggest turbulence that could impact the settling of suspended solids. Conversely, areas of low velocity might suggest sedimentation zones where particles could accumulate, leading to potential dead zones that may not receive adequate treatment. Identifying these zones is crucial for ensuring uniform treatment and preventing operational inefficiencies (Figure 2). The study summarized the flow data of a biological reactor in a wastewater treatment plant, examining the effects of rotation speed and Superficial Gas Velocity (SGV) on flow patterns and mixing efficiency. It was observed that varying rotation speeds (100, 250, 300 rpm) and fixed SGVs (0.6, 1.2 cm/s) influenced liquid recirculation, with higher rotation speeds improving mixing by creating smaller vortices [37]. The differences in the velocity distributions between the two plots suggest variations in the surface velocity and configuration of the basin equipment. This visualization is valuable for understanding and optimizing water treatment processes by highlighting the areas with varying flow dynamics within the treated basin (Figure 5). During the first aeration phase of the SBR, multi-phase CFD simulations identified a reduced stagnation zone in the center of the bioreactor due to high air flow rates (average 4500 m3/h) compared to inflow rates (250 m3/h). The distribution of air was highly affected by circular and vertical flow driven by mixers, with less air present in areas without diffusers and a reduction in air volume in the center of the tank during the anaerobic phase [41]. The results from the computational model indicate that the water flow within the treated basin is not uniform. Higher velocities are observed in specific areas, such as near inflow points or regions with strong aeration. These high-velocity zones are represented in red on the 3D streamline plot. In contrast, lower velocities are observed in areas like the settling tank, where the flow is slower, allowing suspended solids to settle (Figure 4).
The SBR processes were modeled using principles of mass and momentum conservation. Forces such as gravity, buoyancy, fluid pressure, friction, and particle stress drive the movement and transportation of mixture components. The research involved detailed modeling of the sequencing batch reactor to monitor, control, and optimize operations, focusing on different models of activated sludge settling velocity. Simulations compared the impact of varying sludge settling velocities on the effectiveness of the SBR [42].
Adjusting the operation of internal structures such as baffles or weirs can help control the flow patterns. Properly placed baffles can reduce turbulence and ensure that all parts of the basin receive adequate treatment. The differences between the two plots suggest variations in the surface velocity and equipment configuration. The left plot might represent a scenario with higher turbulence and stronger flow near the surface, while the right plot could indicate a more controlled and uniform flow distribution (Figure 4). To create a more balanced and efficient flow, the location or orientation of inflow and outflow points can be adjusted. It can distribute the flow more evenly and prevent short-circuiting, where water bypasses certain areas of the basin.

4.2. Variations and Chemical Dynamics During Wastewater Treatment

The study found that nitrogen compounds (NO3-N, NO2-N) varied the most during wastewater treatment in activated sludge WWTPs (wastewater treatment plants), particularly during cold weather or rainfall, impacting nitrification and denitrification processes [43]. In the regression analysis, the influence of TSS, TN, and TP on COD and BOD5 was evaluated. For COD, TSS and TN showed significant positive coefficients, suggesting that increases in these variables are associated with increases in COD. TP, however, exhibited a negative coefficient, indicating an inverse relationship. In the case of BOD5, TSS and TN did not show significant coefficients, while TP showed a negative but insignificant coefficient (Table 3). The results of the violin plot can be attributed to the different behaviors and interactions of water quality parameters (TSS, TN, TP) in the treatment process. N exhibited variability with a median around 93%. TSS had a narrower distribution, median near 90%. BOD5 presented a wide range with a median around 92%. COD showed a consistent reduction, with a median around 94% (Figure 3). Results highlight the complex interactions between the different water quality parameters and their combined impact on chemical and biochemical oxygen demand in the studied environment. The GEV (generalized extreme value) function effectively models the distribution due to its low PWRMSE (piecewise root mean square error) values. It showed values of 0.802 mg O2·dm−3 for BOD5 and 1.511 mg O2·dm−3 for CODCr. The GMM (Gaussian mixture model) function also fit well for these parameters and biogenic compounds, demonstrating reliability in assessing wastewater treatment processes [44]. TP displayed a broad distribution and high median reduction due to effective removal processes but with variability. TN’s variability is influenced by nitrification and denitrification processes. TSS showed consistent removal due to stable sedimentation and filtration processes. BOD5’s wide range in reduction percentages is due to varying levels of organic matter and microbial activity. The consistent COD reduction indicates effective removal of chemical contaminants, leading to stable values. The sequencing batch reactor (SBR) effectively removed pollutants by handling high organic loads and low nutrient concentrations. It achieved 84.8% COD and >90% BOD5 removal, reduced color by 72.3% and turbidity by 83.3%, and assimilated nitrogen and phosphorus. Its flexibility allowed adaptation to varying conditions, making it efficient and cost-effective for wastewater treatment [45]. The sequencing batch reactor demonstrated high efficiency in eliminating BOD and COD. Controlled aerobic phases facilitated the degradation of organic pollutants, leading to 88% COD elimination and 97% BOD elimination. The system’s flexibility and adaptation to varying influent conditions further enhanced its effectiveness in reducing these contaminants [46]. Anaerobic sequencing batch reactors (ASBRs) efficiently removed carbon, nitrogen, and sulfur from high-nitrogen wastewater. They adapted to nitrite-stress conditions, achieving 99% nitrite-nitrogen removal by controlling C/N ratios. ASBRs supported a mixotrophic microbial community, enhancing treatment efficiency for complex wastewater [47]. Membrane technology is highly efficient for treating wastewater from fish processing. It effectively reduces organic pollutants, suspended solids, and nutrients. The study found that ring fixed bed reactors (RFBR) were the most efficient, achieving 44–80% COD reduction, 72–77% BOD5 reduction, and nutrient reductions of 16–34% for PO43− and 42% for NH4+. This makes membranes ideal for treating complex wastewater [48]. In raw sewage, the average BOD5/COD ratio was 0.45, while after treatment, it decreased to 0.13, indicating efficient organic matter decomposition. The BOD5/TN ratio in raw sewage was 6.72, suggesting high biodegradation potential, which improved after treatment. The average percentage reduction achieved was 99% for BOD5, 87% for TN, and 56 for BOD5/TP [49]. The study of the efficiency of a biological reactor in a domestic wastewater treatment plant identified significant positive relationships between BOD and COD (p < 0.001) and TSS (p < 0.001) using the generalized linear model [50].
Sequencing batch reactors are a flexible wastewater treatment technology. Recent research has focused on improving SBR performance and exploring new materials for related applications [51,52]. Cyclic technology-based sequencing batch reactors (SBRs) effectively reduced biochemical oxygen demand to below 10 mg/L and chemical oxygen demand to 10 mg/L. The resulting dewatered sludge, rich in nitrogen, phosphorus, and potassium, can be utilized as an effective organic fertilizer after drying or composting [53]. Enhancing sequencing batch reactor performance extends beyond dissolved oxygen control and requires advanced modeling to effectively treat municipal wastewater. Integrated hybrid control strategies—such as proportional integral, fractional proportional integral, and fuzzy logic—alongside real-time monitoring of critical parameters and the calculation of the effluent quality index are essential [54].
Similar to our SBR-GT technology, continuous-flow sequencing batch reactors improve wastewater treatment by allowing continuous flow during operation. This design reduces downtime, enhances efficiency, and minimizes the reactor’s footprint, making it ideal for various applications [55].

4.3. Limitation of the Studied Technology and Process

The SBR-GT offers an efficient and cost-effective solution for wastewater treatment, particularly in municipal and selected industrial applications. The system’s ability to adapt to varying influent conditions, along with its features such as stable sedimentation, controlled treatment cycles, and full automation, makes it highly versatile and reliable. The integration of simultaneous filling and decanting further optimizes the process, reducing investment costs while ensuring effective treatment. Additionally, the SBR-GT system’s ability to handle higher influent volumes through its stormwater mode enhances its capacity to address fluctuating demands. With its advanced features, the SBR-GT proves to be a valuable option for both new and retrofitted treatment plants, delivering high performance in various operational conditions. The SBR-GT has limitations, such as its reliance on stable conditions for optimal performance. Fluctuations in influent volumes may require adjustments to cycle times or settings. Although automated, regular maintenance is still needed to ensure the proper functioning of components like the static decanter. The system may not be cost-effective for very small-scale operations.
Adjusting the operation of internal structures, such as baffles or weirs, can help to distribute flow more evenly and prevent short-circuiting, where water bypasses certain areas of the basin. Modifying the aeration system, such as the placement and operation of diffusers, can enhance oxygen transfer and mixing, improving the overall treatment efficiency. Once the optimal configuration is determined, the adjustments are implemented in the actual treated basin. This process might involve physical modifications to the basin structure, such as installing new inflow and outflow points, or operational changes, such as altering the aeration schedule. Regular monitoring and analysis are crucial for the efficient operation of the system. Reviewing streamline plots and performance data allows for continuous optimization and quick adjustments to influent changes, ensuring the treatment plant consistently meets high performance and effluent quality standards. Another limitation is that its performance could decline with complex or high-load wastewater, requiring additional treatment or modifications. The SBR-GT wastewater treatment plant optimizes treatment by combining phases for simultaneous decanting and filling, reducing chamber volumes and capital costs. With cycles of 6–12 h, the system adapts to local conditions via a programmable control system. In response to sudden influent increases, the plant switches to “stormwater mode,” enhancing hydraulic capacity.
Modifying the placement and operation of the aeration system can enhance oxygen transfer and mixing. The process should improve the overall treatment efficiency and ensure that the entire basin is effectively aerated. Ongoing monitoring and analysis of the streamline plots and performance data are essential. Regularly reviewing the data allows for continual optimization and quick response to any changes in influent conditions, ensuring that the treatment plant maintains high performance. The SBR-GT reactor’s technological equipment ensures effective treatment but also has certain limitations. The simplicity of its design, with just four types of equipment—submersible pumps for sewage and excess sludge, submersible mixers, an aeration system, and a filling and decanting system for treated sewage—can be a limitation in more complex scenarios requiring advanced treatment processes. Submersible pumps, though reliable and suited for the medium they work in, may face challenges in handling high volumes or very coarse materials. Maintenance, even with facilitated features such as a detachable cable with a hermetic plug and a dismountable steel ring, can be cumbersome if pump failure occurs frequently. Submersible mixers with planetary gears, effective in mixing without destroying the structure of delicate activated sludge flocs, may still fall short in cases where higher mixing speeds or more robust mixing capabilities are needed. The key aeration process relies on membrane disc diffusers. Despite safeguards such as a non-perforated central part and a special ball check valve to prevent sludge ingress, they remain vulnerable to damage or clogging, especially in emergency situations. If the membrane is damaged, it could compromise the aeration efficiency and require prompt and potentially costly repairs.

5. Conclusions

The SBR-GT reactor’s water treatment process involves several stages: sewage is pumped into the reactor (filling), air is introduced to support microbial activity (aeration), the contents are mixed for efficient treatment (mixing), solids settle out (sedimentation), treated water is removed (decanting), and excess sludge is discharged (sludge removal). This process ensures effective treatment, though challenges may arise in handling high volumes or coarse materials. The reactor achieved a total suspended solids reduction of approximately 90%, indicating consistent performance. Biochemical oxygen demand showed more variability, with a median reduction of 92%, while chemical oxygen demand demonstrated a stable reduction of around 94%. Multivariate multiple linear regression analysis revealed positive relationships for TSS and total nitrogen with COD (p < 0.001 and p = 0.0009, respectively) and a negative relationship for total phosphorus with COD (p = 0.0001). The MMLR model provided valuable insights by accounting for confounding variables and improving predictive accuracy. A computational model and 3D streamline plot further illustrated critical dynamics within the treated basin, enhancing water treatment management. High-velocity zones supported mixing and aeration, while low-velocity zones improved sedimentation. These visualizations highlighted areas for optimization, ensuring effective treatment. The system’s ability to adapt cycle times and switch to “stormwater mode” enables it to perform efficiently under varying conditions, making it suitable for operations of different scales. However, regular maintenance and potential design modifications are necessary to handle complex or high-load wastewater effectively. The SBR-GT reactor is innovative in combining the decanting and filling phases to reduce costs, optimizing cycle times for efficiency, and switching to “stormwater mode” for sudden inflows. Its simplified design, with fewer equipment types, ensures cost-effectiveness and flexibility in wastewater treatment. Future work could focus on further enhancing efficiency and adaptability. Advanced monitoring and control systems may optimize mixing and aeration to lower energy consumption. Integrating real-time automation could improve performance under extreme inflow conditions. Additional treatment stages or hybrid configurations may address complex wastewater, while scalability studies would confirm its effectiveness across various operational sizes—from small-scale setups to large municipal plants.

Author Contributions

Conceptualization, T.S. and P.J.; methodology, T.S.; formal analysis, W.H.; investigation, T.S.; resources, P.J.; data curation, W.H.; writing—original draft preparation, W.H.; writing—review and editing, W.H., T.S. and P.J., project administration, T.S. and P.J. funding acquisition, W.H.; K.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data will be available on request.

Acknowledgments

Administrative and technical support for materials used for experiments was provided by Grundfos Pompy Ltd.

Conflicts of Interest

The authors declare no conflicts of interest. Authors Tomasz Sionkowski and Paweł Jasiński work at Grundfos Pompy Ltd. and are responsible for probing the SBR-GT as a new innovation and collaboration between business and science methodology.

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Processes 13 01173 g001
Figure 1. A schematic diagram of the whole processes SBR-GT. Sewage treatment processes, all arranged as follows: 1. Filling (green arrow means raw wastewater inflow); 2. Nitrification/Denitrification; 3. Sedimentation; 4. Excess sludge removal (brown arrow); 5. Decantation (blue arrow represents outflow of treated wastewater).
Figure 1. A schematic diagram of the whole processes SBR-GT. Sewage treatment processes, all arranged as follows: 1. Filling (green arrow means raw wastewater inflow); 2. Nitrification/Denitrification; 3. Sedimentation; 4. Excess sludge removal (brown arrow); 5. Decantation (blue arrow represents outflow of treated wastewater).
Processes 13 01173 g001
Processes 13 01173 g002
Figure 2. Process for SBR-GT reactor operation cycle: (A) Inflow of new portion of wastewater (green arrow); (B) Aeration of activated sludge (red arrow means no water inflow); (C) Activated sludge sedimentation and renewal (red arrow indicates no wastewater inflow). The blue arrow symbolizes the outflow of treated wastewater from the reactor. The white arrow indicates the direction of the treated wastewater flow, representing its removal or further transfer within the system.
Figure 2. Process for SBR-GT reactor operation cycle: (A) Inflow of new portion of wastewater (green arrow); (B) Aeration of activated sludge (red arrow means no water inflow); (C) Activated sludge sedimentation and renewal (red arrow indicates no wastewater inflow). The blue arrow symbolizes the outflow of treated wastewater from the reactor. The white arrow indicates the direction of the treated wastewater flow, representing its removal or further transfer within the system.
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Processes 13 01173 g003
Figure 3. Violin plot for reduction in TSS, TN TP and COD and BOD5.
Figure 3. Violin plot for reduction in TSS, TN TP and COD and BOD5.
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Processes 13 01173 g004
Figure 4. Example of velocity distribution for wastewater. The streamline technology for velocity distribution in a treated basin involves creating a visual representation of the flow patterns within the basin. This visualization was achieved using computational fluid dynamics simulations. The velocity is indicated by color coding, with different colors representing different velocity ranges. Blue represents low velocities, while red represents high velocities.
Figure 4. Example of velocity distribution for wastewater. The streamline technology for velocity distribution in a treated basin involves creating a visual representation of the flow patterns within the basin. This visualization was achieved using computational fluid dynamics simulations. The velocity is indicated by color coding, with different colors representing different velocity ranges. Blue represents low velocities, while red represents high velocities.
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Processes 13 01173 g005
Figure 5. Example of CFD simulation of wastewater velocity in basin equipment. Analyzing surface velocity and configuration differences for evaluating velocity differences at the surface of a basin for two equipment setup scenarios are indicated. The plots use a color scale to represent different velocity magnitudes, ranging from 0.01 to 1.00 (m/s). The color scale is as follows: red indicates the highest velocity. This image is relevant for checking the performance and efficiency of basin equipment by comparing the water velocity distributions under different configurations.
Figure 5. Example of CFD simulation of wastewater velocity in basin equipment. Analyzing surface velocity and configuration differences for evaluating velocity differences at the surface of a basin for two equipment setup scenarios are indicated. The plots use a color scale to represent different velocity magnitudes, ranging from 0.01 to 1.00 (m/s). The color scale is as follows: red indicates the highest velocity. This image is relevant for checking the performance and efficiency of basin equipment by comparing the water velocity distributions under different configurations.
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Table 1. Average content for parameters characterizing the level of efficiency in the treatment plant.
Table 1. Average content for parameters characterizing the level of efficiency in the treatment plant.
IndicatorRawRawLimit
mg/dm3
BOD5382.55.525
COD126328.8125
Total Suspended Solids577.54.4835
Total nitrogen11.6311.615
Total phosphorus18.930.542
Table 2. Parameters for wastewater treatment with sequencing batch reactor Grundfos technology.
Table 2. Parameters for wastewater treatment with sequencing batch reactor Grundfos technology.
ParameterValue
Q2830 m3/d
RLM17,640
Volume2 × 1010 m3 (−20%)
AOR25.5 kg/h (−19%)
SOR56.7 kg/h
Qp596 Nm3/h (−28%)
MotorES65/2-P 22 kW
Energy Consumption560 kWh (−13%)
Annual Energy Cost Savingsca. 4000 EURO
Footnote: Q is average daily flow rate. It represents the average volume of wastewater treated by the sewage treatment plant on a daily basis. RLM (real load measurement). It represents the number of people that generate the equivalent amount of wastewater as processed by the treatment plant. This stands for population equivalent (PE). It is a way to measure the capacity and performance of a treatment plant relative to the number of people contributing to the wastewater flow. AOR stands for aerobic oxygen requirement or actual oxygen rate. SOR is specific oxygen rate. SOTE is standard oxygen transfer efficiency. Qp is pump flow rate. The annual energy savings for the supply of nominal flow significantly below average 0.10 EURO/kWh.
Table 3. Multivariate multiple linear regression for TSS, TN, TP, COD, and BOD.
Table 3. Multivariate multiple linear regression for TSS, TN, TP, COD, and BOD.
Tests on Independent Variables
pdf2df1FWilks LambdaIndicator
<0.017235.920.09TSS
<0.017217.850.16TN
<0.017227.160.11TP
Tests on Dependent Variables
pdf2df1FR2
<0.00183649.50.99COD
<0.0018338.450.93BOD5
Regression Coefficients and Statistics
R2ptStandard ErrorCoefficient
0.17−1.5131.5−47.45ConstantCOD
0.96<0.0017.650.161.26TSS
0.49<0.015.061.276.45TN
0.05<0.01−6.650.87−5.79TP
0.67−0.4535.4−15.8ConstantBOD5
0.910.171.530.180.28TSS
0.620.141.651.432.36TN
Footnote: Wilks’ lambda is test statistic in MANOVA for group mean differences; smaller value means greater difference; F value (F-statistic) is used in ANOVA to compare group means by examining variance; df1 is degrees of freedom for numerator; number of group comparisons; df2 is degrees of freedom for denominator; total observations minus groups; p-value is probability of results occurring by chance; p indicates the probability that the coefficient is different from zero purely by chance. Smaller p-values suggest stronger evidence against the null hypothesis, indicating a significant predictor. R2 also known as the coefficient of determination, is a statistical measure used in regression analysis to evaluate the goodness of fit of a model. It represents the proportion of the variance in the dependent variable that is predictable from the independent variable(s); t (t-statistic) measures how many standard deviations the coefficient is away from zero. It is used to test the significance of each predictor in the model.
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Sionkowski, T.; Halecki, W.; Jasiński, P.; Chmielowski, K. Achieving High-Efficiency Wastewater Treatment with Sequencing Batch Reactor Grundfos Technology. Processes 2025, 13, 1173. https://doi.org/10.3390/pr13041173

AMA Style

Sionkowski T, Halecki W, Jasiński P, Chmielowski K. Achieving High-Efficiency Wastewater Treatment with Sequencing Batch Reactor Grundfos Technology. Processes. 2025; 13(4):1173. https://doi.org/10.3390/pr13041173

Chicago/Turabian Style

Sionkowski, Tomasz, Wiktor Halecki, Paweł Jasiński, and Krzysztof Chmielowski. 2025. "Achieving High-Efficiency Wastewater Treatment with Sequencing Batch Reactor Grundfos Technology" Processes 13, no. 4: 1173. https://doi.org/10.3390/pr13041173

APA Style

Sionkowski, T., Halecki, W., Jasiński, P., & Chmielowski, K. (2025). Achieving High-Efficiency Wastewater Treatment with Sequencing Batch Reactor Grundfos Technology. Processes, 13(4), 1173. https://doi.org/10.3390/pr13041173

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