
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)12049-X
10.1016/j.heliyon.2024.e36018
e36018
Research Article
Effect of settling time and organic loading rates on aerobic granulation processes treating high strength wastewater
Min Kyung Jin kyungjinm@konkuk.ac.kr
a1
Lee Eunyoung eylee84@gmail.com
b1
Lee Ah Hyun ahi0422@naver.com
b
Kim Do Yeon donim1020@naver.com
b
Park Ki Young kypark@konkuk.ac.kr
b⁎
a Department of Tech Center for Research Facilities, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul, 05029, South Korea
b Department of Civil and Environmental Engineering, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul, 05029, South Korea
⁎ Corresponding author. kypark@konkuk.ac.kr
1 These authors contributed equally to this work.

09 8 2024
30 8 2024
09 8 2024
10 16 e3601831 7 2024
7 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Despite its numerous advantages, the aerobic granular sludge (AGS) process faces several challenges that hinder its widespread implementation. One such challenge is the requirement for high organic load ratios (OLR), which significantly impacts AGS formation and stability, posing a barrier to commercialization. In response to these challenges, this study investigates the granulation and treatment efficacy of the AGS process for treating high-concentration wastewater under various OLR and settling time. Three sequential batch reactors (R1, R2, R3) were operated at OLRs of 0.167, 0.33, and 1 kg COD/m3·day. The study focuses on analyzing key parameters including sludge characteristics, extracellular polymeric substances (EPS) content, PN/PS ratio, and microbial clusters. Results demonstrate that reducing settling time from 90 to 30 min enhances sludge settleability, resulting in a maximum 50.8 % decrease in SVI30 (from 98.1 to 122.8 mL/g to 51.9–81.3 mL/g), thereby facilitating the selection of beneficial microorganisms during granulation. Particularly, at R2, the PN/PS ratio was 4.3, and EPS content increased by 1.52-fold, leading to a 1.41-fold increase in sludge attachment. This observation suggests a progressive maturation of AGS. Additionally, analysis of microbial diversity and cluster composition highlights the influence of OLR variations on the ratios of Proteobacteria and Bacteroidetes. These findings emphasize the significant impact of SBR operational strategies on AGS process performance and biological stability, offering valuable insights for the efficient operation of future high-concentration wastewater treatment processes.

Keywords

Aerobic granule sludge
Organic loading rate
Settling time
Extracellular polymeric substance
==== Body
pmc1 Introduction

Aerobic granular sludge (AGS) technology is recognized for its ability to self-agglomerate microorganisms into granular aggregates, making it a highly effective method for wastewater treatment. Its advantages include a compact structure, efficient settling performance, resilience to shocks, and high nitrogen removal efficiency [1]. Despite these merits, challenges persist in AGS technology, including prolonged granule formation, operational instability, and susceptibility to collapse. Current efforts to expedite AGS formation and enhance stability involve manipulating operating parameters, adding ions, and microbial inoculation. Among these approaches, controlling operating parameters is considered fundamental and critical compared to using exogenous substances [2].

The organic loading rate (OLR) significantly influences the formation and stability of AGS. A low OLR prolongs the granule formation period but results in small and stable particles. Conversely, a high OLR accelerates granule formation, but excessive microbial growth can lead to the formation of unstable granules [3]. In a study by Zhang et al. [4], AGS operated under high OLR conditions formed relatively larger and faster compared to conditions with low OLR. The size of activated sludge flocs generated in conventional activated sludge processes is proportional to the organic loading rate. A sudden increase in organic loading rate increases the size and density of AGS but reduces microbial species diversity, leading to a decrease in the solidity of the three-dimensional structure. Therefore, supplying appropriate organic loads is crucial for the vigorous formation and maintenance of heterotrophic granular sludge.

Recent studies on AGS have primarily focused on high or moderate OLRs [5,6]. However, municipal wastewater typically features low OLRs (0.28–2 kg COD/m3·day). Additionally, various types of real wastewater, such as side-stream from sewage treatment plants, fertilizer production wastewater, and leachate from landfills, generally have high nitrogen concentrations relative to COD. Consequently, operation under conditions of low OLR and high nitrogen loading rates is inevitable. Nevertheless, the operational feasibility of AGS processes under low OLR, such as 0.15 kg COD/m3·day, has been scarcely reported, particularly in nitrogen-rich wastewater. Moreover, intracellular protein hydrolysis, anaerobic granule core degradation, and the overgrowth of filamentous microorganisms are major causes of instability in AGS under high-concentration wastewater conditions [7]. Hamza et al. [8] found that culturing aerobic granular sludge at a high influent COD concentration of 4500 mg/L resulted in excessive biomass growth, negatively impacting the stability of AGS by causing the presence of methane-generating substances in the sludge core, leading to its degradation.

Among the parameters, the OLR plays a crucial role as an essential energy source for maintaining microbial activity and influences the formation and structural stability of AGS, while operational conditions such as settling velocity, shear force, and settling time can be key factors promoting granulation [9]. Settling time not only affects the formation of AGS but also plays a crucial role in regulating the long-term operational stability of granular sludge [10]. Peng et al. [11] reported that by employing strategies to reduce settling time, AGS reactors could be operated within 40 days with a sludge granulation degree of 90.22 %. While various studies are underway to promote AGS formation through diverse parameters such as inoculum sludge, substrate characteristics, organic loading, pH, temperature, and reactor operating conditions, cases of operating under low OLR conditions with high-concentration wastewater have not yet been reported.

This study aims to promote the formation of AGS for treating high-strength wastewater under two easily applicable field parameters: OLR and settling time. The main objective is to ensure stable operation and AGS formation by providing gradual changes. To achieve this goal, the study investigates sludge characteristics, changes in extracellular polymeric substances (EPS) content and composition, sludge adhesion, and microbial community changes in three sequential batch reactors (SBRs) operated under different OLR conditions. By identifying the effects of low OLR conditions on process performance and sludge characteristics, this study could provide a promising alternative for the treatment of high-strength wastewater containing high concentrations of organic matter and nitrogen.

2 Material and methods

2.1 Experimental design and operation

In this study, three SBRs with an effective volume of 3 L each were utilized, operating under distinct OLR conditions. The OLR conditions for the three reactors were set at 0.167, 0.33, and 1 kg COD/m3·day, designated as R1, R2, and R3, respectively. Corresponding to these OLR conditions, the volume exchange rates were 3.3 %, 6.7 %, and 20 %, respectively. The operational temperature was maintained at 28 ± 2 °C, while the pH was regulated within the range of 7.0–8.5. In instances where the pH dropped below 7.0, sodium bicarbonate (NaHCO3) from Samchun Pure Chemical Co., Ltd., Korea, was added to the reactor to sustain a pH above 7.0. The schematic representation of the SBR reactors is depicted in Fig. 1. For aeration under aerobic conditions, air was introduced from the bottom of the reactor utilizing an air pump (LP-60A, Kosung Valve Co., Ltd., Korea), while a stainless-steel stirrer facilitated mixing. The operational sequences of the SBRs were regulated through an automatic timer, managing influent addition (mixing), aeration, settling, and idling phases.Fig. 1 Schematic diagram of the lab-scale sequencing batch reactor setup.

Fig. 1

The experiment was structured into two phases, delineated by the operating conditions observed throughout the entire operation period (Table 1). Phase I (0–37 days) entailed 24-h cycles comprising four influent (mixing) stages, four aeration stages, one settling stage, and one effluent discharge stage per cycle, with the following time allocations: mixing for 1 h (including 10 min of influent addition), aeration for 4.5 h, settling for 1.5 h, and idling for 0.5 h. Phase II (38–122 days) mirrored the cycle composition and duration of Phase I, albeit with a reduced settling time of 0.5 h. To offset this reduction, the mixing time was proportionally increased.Table 1 SBR operating conditions.

Table 1Phase	Time (d)	Cycle (hr)	
Mixinga	Aeration	Settling	Idling	
Ⅰ	0–37	1	4.5	1.5	0.5	
Ⅱ	38–122	1.25	4.5	0.5	0.5	
a including 10 min of influent.

2.2 Inoculum and synthetic wastewater

The inoculum utilized in this study was sourced from the activated sludge of a biological reactor treating side-stream in a biogas plant situated in Yeongcheon City, South Korea, with MLSS 9290 mg/L, MLVSS 6640 mg/L and SVI30 221 mL/g. Synthetic wastewater, designed to emulate side-stream rich in organic matter and nitrogen, served as the influent. The synthetic wastewater composition comprised sodium acetate (CH3COONa) from Samchun Pure Chemical Co., Ltd., Korea, at a concentration of 6.6 g/L as the carbon source (COD 5000 mg/L), NH4Cl as the nitrogen source, and KH2PO4 as the phosphorus source, with NH4Cl at a concentration of 11.46 g/L (NH4+-N 3000 mg/L), KH2PO4 at 131.8 mg/L (PO43--P 30 mg/L), CaCl2 · 2H2O 30 mg/L, MgSO4 · 7H2O 25 mg/L, FeSO4 · 7H2O 20 mg/L, and trace elements at 1 mL/L (H3BO3 0.05 g/L, ZnCl2 0.05 g/L, CuCl2 0.03 g/L, MnSO4 · H2O 0.05 g/L, (NH4)6Mo7O24 · 4H2O 0.05 g/L, AlCl3 0.05 g/L, CoCl2 · 6H2O 0.05 g/L, NiCl2 0.05 g/L).

2.3 Analytical methods

Throughout the operational period, the reactors' COD, T-N, NH4+-N, NO2−-N, NO3−-N, mixed liquor volatile suspended solids (MLVSS), and SVI30 were analyzed following Standard Methods [12]. Periodic particle size analysis of the sludge was performed using a particle size analyzer (Malvern Mastersizer 2000, Malvern Panalytical Ltd., Malvern, UK), while EPS extraction from the sludge was conducted using the thermal extraction method outlined in previous studies [13]. The composition of the extracted EPS was assessed using the Bradford method for polysaccharides and the Lowry method in conjunction with the Bio-Rad DC protein assay for proteins. To characterize the organic matter composition, EPS samples underwent analysis using Fluorescence excitation–emission matrix (F-EEM) with an RF-5301 spectrofluorometer (Shimadzu Co., Japan). The fluorescence characteristics of organic matter were scanned utilizing an arc lamp with excitation wavelengths ranging from 220 to 400 nm (in 10 nm intervals) and emission wavelengths ranging from 280 to 600 nm (in 1 nm intervals).

For the analysis and quantification of biofilm formation and characteristics, sludge adhesion experiments were conducted as described by Song et al. [14]. Polyvinylidene fluoride (PVDF) membrane pieces measuring 150 mm × 150 mm were prepared and incubated in the sludge suspension with agitation at 150 rpm for 24 h. The microbial-attached membrane pieces were subsequently rinsed twice with 0.9 % NaCl solution and stained using the LIVE/DEAD BacLight Bacterial Viability Kit (Molecular Probe, Eugene, Oregon, USA). Stained membranes were mounted on glass slides (24 mm × 60 mm, thickness 0.17 m) with cover slips and analyzed utilizing confocal laser scanning microscopy (CLSM, LSM 810, Carl Zeiss, Germany). The COMSTAT program was employed to quantify CLSM images of biofilms formed on the membrane surface.

2.4 Microbial community analysis

For both the initial inoculum and samples obtained during Phase II of the three SBR reactors, microbial community analysis was undertaken. Total DNA extraction was carried out utilizing the Maxwell RSC PureFood GMO and Authentication Kit (Promega), following the manufacturer's protocol. PCR amplification was conducted using fusion primers targeting the V3 to V4 regions of the 16S rRNA gene with the extracted DNA. The quality and size of the PCR products were evaluated using a Bioanalyzer 2100 (Agilent, Palo Alto, CA, USA) equipped with a DNA 7500 chip. The resulting amplified DNA fragments were pooled, and sequencing was executed by CJ Bioscience, Inc. (Seoul, Korea), utilizing the Illumina MiSeq Sequencing system (Illumina, USA) in accordance with the manufacturer's guidelines. All these analytical processes were carried out on CJ Bioscience's bioinformatics cloud platform EzBioCloud (https://www.ezbiocloud.net/) employing 16S-based metagenome taxonomic profiling (MTP).

3 Results and discussion

3.1 Reactor performance under different OLR

Fig. 2a represents the monitoring of pH, DO, COD, and TN removal of R1, R2, and R3 throughout the entire operating period. DO was maintained within the range of 2–5 mg/L, and pH was also well controlled within the neutral range. However, R3 maintained a high pH due to insufficient nitrification. Fig. 2b illustrates the average COD and TN removal efficiency in R1, R2, and R3 across phases. Throughout the operation, the COD removal efficiency was highest in R2, ranging from 76.3 % to 83.4 % at an OLR of 0.33 kg COD/m3·day. Despite having the lowest OLR at 0.167 kg COD/m3·day, R1 exhibited lower removal efficiency ranging from 58.6 % to 68.5 %. In contrast to COD, TN removal efficiency ranged from 40.2 % to 51.2 % in R1 and was lowest in R3, ranging from 7.4 % to 27.4 %, even at the highest OLR. The low nitrogen removal in R3 could be attributed to the inhibition of nitrification by free ammonia at high pH [15].Fig. 2 Changes in a) pH, DO, COD and TN removal during the whole process, b) average COD and TN removal at different operating conditions, c) NH4+-N, NO2−-N, NO3−-N ratio in effluent at different operating conditions.

Fig. 2

In Phase II, where settling time was altered, both COD and TN removal efficiencies decreased across all conditions (Fig. 2b). This aligns with previous research findings where a reduction in settling time led to decreased COD and NH4+-N removal efficiencies [16]. This decrease in removal efficiency is attributed to the loss of sludge settling characteristics and PN content within EPS due to reduced settling time, coupled with the loss of heterotrophs and autotrophs. However, in the R1 condition with the lowest OLR, partial nitrification continued even after the phase change, indicating the presence of various microorganisms, including autotrophs, in the AGS structure, thus supporting the existing hypothesis of AGS formation (Fig. 2c). However, the proportion of nitrogen components in effluent changed with the phase change in the R1 condition. In Phase II conditions, the proportion of NO2−-N in the effluent of R1 ranged from 60 % to 72 %, indicating sufficient nitritation but continued inhibition of complete nitrification to NO3−-N. Further microbial analysis related to nitrogen removal will be discussed in section 3.4.

3.2 Effect of SBR operating control on sludge characteristics

Shortened settling times can enhance the development of favorable settling characteristics and dense AGS by eliminating sludge that hampers settling efficiency, primarily through generating higher hydraulic selective pressure [10]. In Fig. 3a, MLVSS and SVI30 were depicted to illustrate the relationship between biomass concentration and settling ability concerning variations in OLR and settling time across the SBR reactors. During Phase I, MLVSS increased with rising OLR. However, in Phase II, MLVSS decreased across all reactors as settling time diminished, a trend consistent with the observed changes in SVI30. The decline in MLVSS was attributed to the swift removal of sludge from the reactors prompted by abrupt alterations in operating conditions due to the shortened settling time. This outcome aligns with prior findings concerning biomass loss during the initial cultivation of AGS [17]. Ultimately, despite the microbial selection process due to the shortened settling time, this positively influenced sludge settling ability, as confirmed through SVI30 [18]. According to existing literature [19], the mature AGS's SVI30 ranges from 20 to 100 mL/g, varying greatly depending on experimental conditions, with an average of 30–50 mL/g. The results of this study were higher, indicating the formation of seed AGS rather than mature AGS. However, this was similar to the findings of Zou et al. [20], which reported a level of 71.1 ± 7.4 mL/g.Fig. 3 Changes in sludge characteristics at different operating conditions: a) MLVSS and SVI30, b) particle size.

Fig. 3

The development of AGS is directly influenced by changes in sludge particle size. Despite the decrease in MLVSS, R2 displayed an increase in average particle size (Fig. 3b). Additionally, while the average particle size of R3 remained relatively stable without a significant increase, considering the reduction in MLVSS, it suggests a gradual maturation of AGS. Conversely, in the case of R1, the average particle size decreased, likely due to the organic loading rate, particularly when compared to the greater reduction in MLVSS observed in R3. This observation aligns with previous findings suggesting that higher OLR speeds up AGS formation [3].

3.3 Effect of SBR operating control on EPS and sludge adhesion

EPS resides within the extracellular matrix and microbial aggregates, serving as a pivotal element of microbial biofilms. It typically comprises organic compounds such as proteins (PN), polysaccharides (PS), humus, nucleic acids, lipids, and glycoproteins, exerting significant influence on material transport, floc formation, and stability [21]. In Fig. 4a, the fluctuations in EPS content and PN/PS composition are depicted throughout the operational period of the SBR. While EPS content decreased with higher OLRs, the PN/PS ratio was higher in R2 compared to R1 and R3. A higher PN/PS ratio generally fosters microbial cell accumulation and aggregation. PN can enhance cell attachment and floc formation by modifying cell surface hydrophobicity, whereas PS can form a backbone encapsulating bacteria, thus creating a network structure [22]. Previous studies have reported inconsistent effects of OLR on polysaccharide content in flocs, with some indicating no alteration and others showing a decrease in protein and an increase in polysaccharide with increasing OLR [23,24]. However, under low OLR conditions, the PN/PS ratio may not exhibit a linear relationship, and consequently, as EPS increases, SVI30 decreases. Therefore, higher EPS levels lead to improved sludge settling and accelerated AGS formation. Notably, the PN/PS ratio in R2, at 4.3, was higher than that in R1 and R3, suggesting that maintaining a PN/PS ratio around 4 ensures a favorable structure and aids in promoting microbial accumulation and aggregation, consistent with previous research findings [21].Fig. 4 Changes in EPS and sludge adhesion at different operating conditions: a) EPS and PN/PS, b) attached biomass, and c) CLSM images of biofilm structure.

Fig. 4

Reducing settling time from Phase I to II resulted in increased EPS content in all reactors, aligning with previous reports indicating that shorter settling times promote the secretion of PN and PS compounds [10]. Particularly, in R2 and R3, the PN/PS ratio increased from 3.1 to 4.3 and from 2.7 to 3.0, respectively, indicating progressive AGS maturation. However, in R1, with the lowest OLR, while EPS content increased, there was no significant change in the PN/PS ratio. This contrasts with previous findings that suggest under prolonged low OLR conditions, sludge microbes may be in a starved state, leading to the breakdown of EPS matrices for exogenous metabolism, with PS content increasing more than PN [25]. Unlike PN, PS, despite being hydrophilic, can promote the formation of a stable floc structure by distributing throughout the floc and building a mesh skeleton [26]. However, PS is less supportive of AGS structure stability compared to PN [21], indicating a distinct difference in microbial attachment properties.

CLSM analysis is a method for assessing whether the generated EPS can bind or aggregate through contact with each other on hydrophilic membranes under different OLR and settling time conditions. The volume of actual attached biomass per membrane area increased with shortened settling time from Phase I to II under all experimental conditions (Fig. 4b). Microbial attachment was particularly proportional to EPS content and PN/PS ratio rather than OLR. This illustrates that as settling time decreases, microbes secrete abundant hydrophobic PN, thereby enhancing microbial cell aggregation and settling efficiency. In Fig. 4c, the results of image analysis at the center of the membrane show that all attached biomass under all experimental conditions exhibited strong green fluorescence indicative of high metabolic activity in live cells. Particularly, R2, with the highest attachment, exhibited denser green fluorescence compared to other experimental conditions, consistent with superior attachment characteristics.

Changes in the organic composition of EPS were analyzed using F-EEM fluorescence spectroscopy (Fig. 5). The F-EEM spectrum provides specific information about tryptophan protein-like (Peak A, Ex/Em = 220–240/330-360), aromatic protein-like (Peak B, Ex/Em = 270–280/330-360), humic acid-like (Peak C, Ex/Em = 300–340/400-450), and fulvic acid-like (Peak D, Ex/Em = 230–260/400-450) substances within sludge EPS. Throughout the entire SBR operation, significant changes in tryptophan protein-like (Peak A) and aromatic protein-like (Peak B) substances were observed in all sludge samples (R1, R2, R3), indicating their prominence as major components of EPS. Guo et al. [27] noted that aromatic and tryptophan protein-like substances contribute to sludge structure formation through surface charge regulation.Fig. 5 EEM fluorescence spectra of EPS at different operating conditions: a) Phase I, b) Phase II.

Fig. 5

During Phase II, where settling time was reduced, there was an increase in the intensity of Peak B observed under all conditions. This corresponds with the earlier finding of increased PN ratio within EPS and suggests that shorter settling time promotes microbial aggregation, crucial for granule formation [28]. Unlike R1 and R2, humic acid and fulvic acid-like substances were not observed in Phase II R2, which had the highest PN/PS ratio. Humic acid-like substances are associated with the growth of specific bacteria, degradation of macromolecular organic matter (e.g., PS and PN), and decomposition of dead cells [29]. The decrease in humic acid in R2 may be attributed to the consumption of PS during granulation, indicating maturation of the granular structure [30]. In the initial stages of granulation, PN is predominantly distributed on the surface of AGS, but after maturation, PS is more widely distributed, playing a crucial role in maintaining the granular structure [31]. Thus, these differences demonstrate that while R1 and R3 have entered a mature stage, R2 is in the stage of progressing towards maturity, indicating that even under low OLR conditions, AGS can operate stably.

3.4 Characteristics of microbial community analysis

3.4.1 Alpha diversity analysis

To explore the microbial characteristics of aerobic granular sludge and various SBRs in Phase II, high-throughput sequencing analysis of 16S rDNA amplicon technology was conducted. A total of 974–1326 OTUs were identified with over 99.4 % Good's coverage, indicating accurate interpretation of species abundance and diversity from the sequencing results. Alpha diversity metrics, including ACE and Chao1 for microbial community richness, and Shannon and Simpson for microbial community evenness, were employed to assess microbial clustering differences, as summarized in Table 2. In Phase II, all samples exhibited a lower Shannon index and a higher Simpson index compared to the initial phase, suggesting a potential decrease in microbial community diversity within the sludge. Particularly notable numerical changes were observed in R2 at an OLR of 0.33 kg COD/m3·day, indicating a significant impact on microbial clustering. This finding is consistent with similar observations by Liu et al. [32], suggesting that the granulation process may diminish microbial community diversity within the sludge. In contrast, ACE and Chao1 indices were lower only in R2 compared to aerobic granular sludge, implying a decrease in the uniformity of microbial clustering within the sludge during the granulation process.Table 2 Alpha diversity indices characterizing sludge samples.

Table 2Sludge samples	OTUs	ACE	Chao1	Shannon	Simpson	Good's coverage	
Inoculum	1069	1219.23	1156.02	4.53	0.04	0.9936	
R1	1326	1399.62	1349.26	3.88	0.06	0.9979	
R2	974	1109.04	1043.20	3.28	0.12	0.9966	
R3	1125	1237.01	1174.08	3.83	0.06	0.9972	

3.4.2 Microbial community structure analysis

To investigate shifts in microbial community composition in response to OLR variations, microbial community analysis was conducted during Phase II. The graph illustrates the microbial community composition of reactors at the phylum level based on OLR (Fig. 6). Overall, Proteobacteria were the dominant phylum, constituting 46.1 % in the inoculum and 64.1 %, 84.1 %, and 51.6 % in R1, R2, and R3, respectively, during Phase II. The Proteobacteria phylum plays a crucial role in organic and nitrogen removal and may contribute to the efficiency of AGS pollutant removal. Additionally, it is known to secrete abundant EPS, which can promote granulation by providing important metabolic diversity [33]. This finding is consistent with earlier results on organic removal efficiency, as reactor R2, which had the highest proportion of Proteobacteria, exhibited the highest COD removal efficiency, while reactor R3, with the lowest proportion of Proteobacteria, showed the lowest organic removal efficiency. The phylum Bacteroidetes is primarily involved in processes such as denitrification, accounting for only 3.4 % in the inoculum. However, following OLR variations in Phase II, it increased to 29.3 %, 7.5 %, and 26.7 % in R1, R2, and R3, respectively, indicating that OLR changes promoted the growth of the Bacteroidetes phylum.Fig. 6 Relative abundance of phyla bacterial classes.

Fig. 6

In the microbial community analysis at the genus level, as shown in Table 3, the Nitrosomonas genus, known as ammonia oxidation bacteria (AOB), was detected at 7.6 % and 1.8 % in reactors R1 and R2, respectively. This supports previous findings regarding partial nitrification. Conversely, Nitrosomonas was not detected in R3, correlating with the lowest ammonia nitrogen removal among the three conditions. Nitrite oxidation bacteria (NOB) were not detected in any of the reactors, suggesting an operation different from the typical nitrite oxidation-nitrate reduction pathway. The Comamonas genus, along with the Paracoccus genus, was dominant in the final stabilized AGS [34,35], with percentages of 3.9 % and 45.1 % in R1 and R2, respectively. The Thauera genus, representing denitrifying bacteria, showed relatively consistent abundance across the inoculum, R1, R2, and R3, ranging from 13.9 % to 19.0 % after OLR variation. The Pseudomonas genus, known for its involvement in various processes such as denitrification, showed the highest percentage in Phase II's R3 (10.4 %) and was detected at 2.5 % in R2. Aequorivita, Corynebacterium, Thiopseudomonas, and Zoogloeaceae are known as denitrifying bacteria (DNB), accounting for 3.6 %, 5.4 %, 1.7 %, and 1.2 %, respectively, in R3, with Zoogloeaceae recognized for its role in cell aggregation and EPS production [36]. Glycogen-accumulating organisms (GAO), represented by Caldimonas in the inoculum at 5.5 %, decreased to 1.6 % in R, with Alkalispirochaeta, Prolixibacteraceae, and Sphingobacteriaceae appearing. GAO bacteria were most detected in R1, with Saprospiraceae and Chitinophagaceae comprising 5.4 % and 3.9 %, respectively.Table 3 Heatmap presenting the evolution in dominant bacterial genera.

Table 3Nutrients removal microbe at genus level	Relative abundance (%)	
Inoculum	R1	R2	R3	
AOB	Nitrosomonas	0.0	7.6	1.8	0.0	
DNB	Azoarcus	5.0	0.0	0.0	0.0	
Comamonas	0.0	3.9	45.1	0.0	
Ottowia	0.0	12.2	5.0	0.0	
Paracoccus	0.0	0.0	0.0	3.4	
Thauera	16.7	19.0	13.9	15.7	
Zoogloeaceae_uc	0.0	0.0	0.0	1.2	
Aequorivita	0.0	0.0	0.0	3.6	
Castellaniella	0.0	1.3	0.0	0.0	
Corynebacterium	0.0	0.0	0.0	5.4	
Thiopseudomonas	0.0	0.0	0.0	1.7	
DPAO	Pseudomonas	0.0	0.0	2.5	10.4	
GAO	Alkalispirochaeta	0.0	0.0	0.0	1.8	
Caldimonas	5.5	0.0	0.0	1.6	
Chitinophagaceae_uc	0.0	3.9	0.0	0.0	
Prolixibacteraceae_uc	0.0	0.0	0.0	1.5	
Saprospiraceae_uc	0.0	5.4	1.3	0.0	
Sphingobacteriaceae_uc	0.0	0.0	0.0	2.6	

4 Conclusions

The optimization of short settling time in SBR operational parameters was found to enhance settling efficiency and promote dense AGS formation. As settling time decreased, the sludge exhibited improved settling ability, facilitating the selection of favorable microorganisms during the granulation process. Furthermore, the variation in EPS content was confirmed to be pivotal in sludge aggregation and AGS formation. Specifically, the increase in the PN/PS ratio within EPS positively influenced sludge attachment, contributing to the progressive maturation of AGS. Performance assessment of reactors under varying OLR conditions revealed that while COD removal efficiency was high at an OLR of 1 kg COD/m3·day, nitrogen removal efficiency was low. This was attributed to changes in microbial community composition, particularly fluctuations in the proportions of Proteobacteria and Bacteriodetes phyla, which elucidated the reasons for the differences in removal efficiency. Additionally, analysis of microbial diversity and community composition highlighted the impact of OLR variations on the diversity and structure of microbial communities. These findings underscore the significant influence of SBR operational strategies on the performance and biological stability of AGS processes, offering valuable insights for the efficient operation of high-strength wastewater treatment processes in the future.

CRediT authorship contribution statement

Kyung Jin Min: Conceptualization, Supervision, Writing – original draft. Eunyoung Lee: Investigation, Visualization, Writing – original draft. Ah Hyun Lee: Formal analysis, Methodology. Do Yeon Kim: Formal analysis, Methodology. Ki Young Park: Supervision, Writing – review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This paper was supported by 10.13039/501100002641 Konkuk University Researcher Fund in 2023 and Carbon Neutrality Specialized Graduate Program through the Korea Environmental Industry & Technology Institute(10.13039/501100003654 KEITI ) funded by the Ministry of Environment(MOE) (No. 202401260001 ).
==== Refs
References

1 Liu Y. Guo L. Ren X. Zhao Y. Jin C. Gao M. Ji J. She Z. Effect of magnetic field intensity on aerobic granulation and partial nitrification-denitrification performance Process Saf. Environ. Protect. 160 2022 859 867 10.1016/j.psep.2022.02.065
2 Liu Z. Zhang D. Yang R. Wang J. Duan Y. Gao M. Wang J. Zhang A. Liu Y. Li Z. Changes and stage disparity of aerobic sludge granulation with increasing organic load rate under low organotrophic conditions J. Clean. Prod. 450 2024 141937 10.1016/j.jclepro.2024.141937
3 Iorhemen O.T. Liu Y. Effect of feeding strategy and organic loading rate on the formation and stability of aerobic granular sludge J. Water Proc. Eng. 39 2021 101709 10.1016/J.JWPE.2020.101709
4 Zhang Y. Dong X. Nuramkhaan M. Lei Z. Shimizu K. Zhang Z. Adachi Y. Lee D.J. Tay J.H. Rapid granulation of aerobic granular sludge: a mini review on operation strategies and comparative analysis Bioresour. Technol. Rep. 7 2019 100206 10.1016/J.BITEB.2019.100206
5 Miyake M. Hasebe Y. Furusawa K. Shiomi H. Inoue D. Ike M. Efficient aerobic granular sludge production in simultaneous feeding and drawing sequencing batch reactors fed with low-strength municipal wastewater under high organic loading rate conditions Biochem. Eng. J. 184 2022 108469 10.1016/j.bej.2022.108469
6 Tang R. Han X. Jin Y. Yu J. Do increased organic loading rates accelerate aerobic granulation in hypersaline environment? J. Environ. Chem. Eng. 10 6 2022 108775 10.1016/j.jece.2022.108775
7 Xiong W. Wang L. Zhou N. Fan A. Wang S. Su H. High-strength anaerobic digestion wastewater treatment by aerobic granular sludge in a step-by-step strategy J. Environ. Manag. 262 2020 110245 10.1016/j.jenvman.2020.110245
8 Hamza R.A. Sheng Z. Iorhemen O.T. Zaghloul M.S. Tay J.H. Impact of food-to-microorganisms ratio on the stability of aerobic granular sludge treating high-strength organic wastewater Water Res. 147 2018 287 298 10.1016/j.watres.2018.09.061 30317038
9 Ali N.S.A. Muda K. Mohd Amin M.F. Najib M.Z.M. Ezechi E.H. Darwish M.S. Initialization, enhancement and mechanisms of aerobic granulation in wastewater treatment Separ. Purif. Technol. 260 2021 118220 10.1016/j.seppur.2020.118220
10 Ai N. Yang Z. Lou B. Yang D. Wang Q. Ou D. Hu C. Impact of stepwisely reducing settling time on the formation and performance of aerobic granular sludge J. Water Proc. Eng. 60 2024 105117 10.1016/j.jwpe.2024.105117
11 Peng T. Wang Y. Wang J. Fang F. Yan P. Liu Z. Effect of different forms and components of EPS on sludge aggregation during granulation process of aerobic granular sludge Chemosphere 303 2022 135116 10.1016/j.chemosphere.2022.135116
12 APHA Standard Methods for the Examination of Water and Wastewater 23 ed. 2017 American Public Health Association Washington, D.C
13 Jang E. Min K.J. Lee E. Choi H. Park K.Y. Acceleration of aerobic granulation in sidestream treatment with exogenous autoinducer Water 15 12 2023 2173 10.3390/w15122173
14 Song W. Kim C. Han J. Lee J. Jiang Z. Kweon J. Application of acyl-homoserine lactones for regulating biofilm characteristics on PAO1 and multi-strains in membrane bioreactor Membr. Water Treat. 14 1 2023 35 45 10.12989/mwt.2023.14.1.035
15 Sarvajith M. Kiran Kumar Reddy G. Nancharaiah Y. Aerobic granular sludge for high-strength ammonium wastewater treatment: effect of COD/N ratios, long-term stability and nitrogen removal pathways Bioresour. Technol. 306 2020 123150 10.1016/j.biortech.2020.123150
16 Liu J. Li J. Piché-Choquette S. The combination of external conditioning and Ca2+ addition prior to the reintroduction of effluent sludge into SBR sharply accelerates the formation of aerobic granules J. Water Proc. Eng. 36 2020 101269 10.1016/j.jwpe.2020.101269
17 Geng M. You S. Guo H. Ma F. Xiao X. Zhang J. Impact of fungal pellets dosage on long-term stability of aerobic granular sludge Bioresour. Technol. 332 2021 125106 10.1016/j.biortech.2021.125106
18 Wang J.Y. Zhao B. An Q. Dan Q. Guo J.S. Chen Y.P. The acceleration of aerobic sludge granulation by alternating organic loading rate: performance and mechanism J. Environ. Manag. 347 2023 119047 10.1016/j.jenvman.2023.119047
19 Nancharaiah Y. Kiran Kumar Reddy G. Aerobic granular sludge technology: mechanisms of granulation and biotechnological applications Bioresour. Technol. 247 2017 1128 1143 10.1016/j.biortech.2017.09.131 28985995
20 Zou J. Pan J. Wu S. Qian M. He Z. Wang B. Li J. Rapid control of activated sludge bulking and simultaneous acceleration of aerobic granulation by adding intact aerobic granular sludge Sci. Total Environ. 674 2019 105 113 10.1016/j.scitotenv.2019.04.006 31004888
21 Liu X. Pei Q. Han H. Yin H. Chen M. Guo C. Li J. Qiu H. Functional analysis of extracellular polymeric substances (EPS) during the granulation of aerobic sludge: relationship among EPS, granulation and nutrients removal Environ. Res. 208 2022 10.1016/J.ENVRES.2022.112692
22 Chen H. Li A. Cui C. Ma F. Cui D. Zhao H. Wang Q. Ni B. Yang J. AHL-mediated quorum sensing regulates the variations of microbial community and sludge properties of aerobic granular sludge under low organic loading Environ. Int. 130 2019 104946 10.1016/j.envint.2019.104946
23 Adav S.S. Lee D. Lai J. Functional consortium from aerobic granules under high organic loading rates Bioresour. Technol. 100 14 2009 3465 3470 10.1016/j.biortech.2009.03.015 19345575
24 Zhu R. Fang F. Chen J. Zhang L. Performance and surface characteristics of sludge operated at increasing organic loads after aerobic granulation 2008 2nd International Conference on Bioinformatics and Biomedical Engineering 2008, May IEEE 3507 3512
25 Hong P. Noguchi M. Matsuura N. Honda R. Mechanism of biofouling enhancement in a membrane bioreactor under constant trans-membrane pressure operation J. Membr. Sci. 592 2019 117391 10.1016/j.memsci.2019.117391
26 Adav S.S. Lee D.J. Show K.Y. Tay J.H. Aerobic granular sludge: recent advances Biotechnol. Adv. 26 5 2008 411 423 10.1016/j.biotechadv.2008.05.002 18573633
27 Guo H. Felz S. Lin Y. Van Lier J.B. De Kreuk M. Structural extracellular polymeric substances determine the difference in digestibility between waste activated sludge and aerobic granules Water Res. 181 2020 115924 10.1016/j.watres.2020.115924
28 Qin L. Tay J. Liu Y. Selection pressure is a driving force of aerobic granulation in sequencing batch reactors Process Biochemistry 39 5 2004 579 584 10.1016/S0032-9592(03)00125-0
29 Wang H. Song Q. Wang J. Zhang H. He Q. Zhang W. Song J. Zhou J. Li H. Simultaneous nitrification, denitrification and phosphorus removal in an aerobic granular sludge sequencing batch reactor with high dissolved oxygen: effects of carbon to nitrogen ratios Sci. Total Environ. 642 2018 1145 1152 10.1016/j.scitotenv.2018.06.081 30045496
30 Li Z. Lin L. Liu X. Wan C. Lee D.J. Understanding the role of extracellular polymeric substances in the rheological properties of aerobic granular sludge Sci. Total Environ. 705 2020 135948 10.1016/j.scitotenv.2019.135948
31 Wu D. Zhao B. Zhang P. An Q. Insight into the effect of nitrate on AGS granulation: granular characteristics, microbial community and metabolomics response Water Res. 236 2023 119949 10.1016/j.watres.2023.119949
32 Liu Z. Zhang X. Zhang S. Qi H. Hou Y. Gao M. Wang J. Zhang A. Chen Y. Liu Y. A comparison between exogenous carriers enhanced aerobic granulation under low organic loading in the aspect of sludge characteristics, extracellular polymeric substances and microbial communities Bioresour. Technol. 346 2022 126567 10.1016/j.biortech.2021.126567
33 Wang L. Yu X. Xiong W. Li P. Wang S. Fan A. Su H. Enhancing robustness of aerobic granule sludge under low C/N ratios with addition of kitchen wastewater J. Environ. Manag. 265 2020 110503 10.1016/j.jenvman.2020.110503
34 Awang N.A. Shaaban M.G. Weng L.C. Wei B.C. Characterization of aerobic granular sludge developed under variable and low organic loading rate Sains Malays. 46 12 2017 2497 2506 10.17576/jsm-2017-4612-27
35 Olaya-Abril A. Hidalgo-Carrillo J. Luque-Almagro V.M. Fuentes-Almagro C. Urbano F.J. Moreno-Vivián C. Richardson D.J. Roldán M.D. Effect of pH on the denitrification proteome of the soil bacterium Paracoccus denitrificans PD1222 Sci. Rep. 11 1 2021 17276 10.1038/s41598-021-96559-2
36 Guo Y. Zhang B. Feng S. Wang D. Li J. Shi W. Unveiling significance of Ca2+ ion for start-up of aerobic granular sludge reactor by distinguishing its effects on physicochemical property and bioactivity of sludge Environ. Res. 212 2022 113299 10.1016/j.envres.2022.113299
