In this study, three sequencing batch biofilter granular reactors (SBBGRs) were employed to treat model lignin wastewater containing different lignin models (2,6-dimethoxyphenol, 4-methoxyphenol, and vanillin). After 40 days of cultivation, uniform-shaped aerobic granular sludge (AGS) was successfully developed through nutrient supplementation with synthetic wastewater. During the acclimation stage, the chemical oxygen demand (COD) reduction efficiencies of the three reactors showed a trend of initial decreasing (5–20%) and then recovering to a high reduction efficiency (exceeding 90%) in a short period of time. During the stable operation stage, all three reactors achieved COD reduction efficiencies exceeding 90%. These findings indicated the cultivated AGS's robust resistance to changes in lignin models in water. UV–Vis spectra analysis confirmed the effective degradation of the three lignin models. Microbiological analysis showed that Proteobacteria and Bacteroidetes were always the dominant phyla. At the genus level, while Acinetobacter (15.46%) dominated in the inoculation sludge, Kapabacteriales (7.93%), SBR1031 (11.77%), and Chlorobium (25.37%) were dominant in the three reactors (for 2,6-dimethoxyphenol, 4-methoxyphenol, and vanillin) after degradation, respectively. These findings demonstrate that AGS cultured with SBBGR effectively degrades lignin models, with different dominant strains observed for various lignin models.

  • The aerobic granular sludge cultivated in SBBGR was applied to treat lignin models and demonstrated excellent impact resistance.

  • The high sludge concentration and diverse microbial community enable effective lignin model degradation.

  • Different strains dominated the cultured AGS in three reactors that degraded 2,6-dimethoxyphenol, 4-methoxyphenol, and vanillin, respectively.

Lignin is a complex natural high molecular phenolic polymer. Due to the different polymeric monomers, lignin can be categorized into three types: syringyl lignin (S-lignin); guaiacyl lignin (G-lignin), and hydroxyphenyl lignin (H-lignin) (Cheng et al. 2017). Lignin is an important component of the secondary cell wall of higher terrestrial plants, which plays an important role in endowing plants with rigidity, assisting in water transport, and protecting plants from invasion by microorganisms (Manavalan et al. 2015; Vanholme et al. 2019).

The pulp and paper industry is closely related to human life and is an important part of the global economy (Young & Akhtar 1998). In the pulp and paper industry, lignin is a by-product of sulfate and alkali pulping processes. Approximately 90–95% of the lignin is dissolved in the cooking solution (Feng et al. 2021). Due to the difficult biodegradability of lignin, it is difficult to treat pulp and paper wastewater, which may pollute the environment if discharged at will (Lei & Li 2013). Therefore, the effective degradation of lignin is of great significance to improve the efficiency of papermaking wastewater treatment and reduce the pollution load.

Lignin degradation is a process in which industrial lignin is decomposed into small molecule products by physical, chemical, and biological methods. At present, available lignin degradation methods include physical and chemical methods as shown in Table 1. These methods have some disadvantages such as high cost, harsh reaction conditions, and easy pollution. Biological method has been widely concerned by researchers because of its characteristics of energy saving and environmental protection. Lignin can be degraded by a variety of microorganisms, such as white rot fungi, brown rot fungi, soft rot fungi, actinomyces, and so on (Andlar et al. 2018; Chio et al. 2019). The lignin peroxidase, laccase, and manganese peroxidase produced by microorganisms play important roles in the lignin degradation process (Rodríguez-Couto 2017). Chen et al. (2017a, 2017b) used corn straw as the fermentation substrate of Pleurotus ostreatus, and after 30 days, the lignin content of corn straw decreased from 18.45 to 8.35%, and the degradation rate reached 54.7%. Scanning electron microscopy showed that the surface of corn straw was gradually destroyed and formed a quasi-network structure. However, there is no evidence to date that any organism can use lignin as a food source for life. In addition, the long culture cycle of microorganisms, poor tolerance to extreme environments, and low enzyme production also limit the industrial application of microbial lignin degradation (Andlar et al. 2018).

Table 1

Advances in lignin degradation techniques

AuthorObjectMethodsResultReferences
Du et al. Softwood lignin Ozone oxidation pretreatment + pyrolysis 1. Some of the alkyl aryl ether bonds are broken.
2. The hydroxyl groups on the side chains are oxidized. 
Du et al. (2022)  
Chen et al. Poplar wood (NE222) lignin Acid-catalyzed p-TsOH can depolymerize lignin via ether bond cleavage. Chen et al. (2017a, 2017b
Deuss et al. Lignin Acid-catalyzed Effectively fracture the β-O-4 bond in lignin. Deuss et al. (2015)  
Duan et al. Alkali lignin Microwave-assisted acid pretreatment β-O-4 bond and aliphatic side chain, decrease in –OH groups, and
formation of C = O groups in pretreatment. 
Duan et al. (2018)  
AuthorObjectMethodsResultReferences
Du et al. Softwood lignin Ozone oxidation pretreatment + pyrolysis 1. Some of the alkyl aryl ether bonds are broken.
2. The hydroxyl groups on the side chains are oxidized. 
Du et al. (2022)  
Chen et al. Poplar wood (NE222) lignin Acid-catalyzed p-TsOH can depolymerize lignin via ether bond cleavage. Chen et al. (2017a, 2017b
Deuss et al. Lignin Acid-catalyzed Effectively fracture the β-O-4 bond in lignin. Deuss et al. (2015)  
Duan et al. Alkali lignin Microwave-assisted acid pretreatment β-O-4 bond and aliphatic side chain, decrease in –OH groups, and
formation of C = O groups in pretreatment. 
Duan et al. (2018)  

Sequencing batch biofilter granular reactor (SBBGR) is wastewater biological treatment technology that has been developed in recent years. It offers numerous advantages, including low sludge production and high sludge retention times (Altieri et al. 2023). Unlike the granules suspended in SBR, the granules in SBBGR remain in the pores produced by filling the reactors with filler materials, so more biomass can be obtained (Nancharaiah & Kiran 2018). Sun et al. (2017) used SBBGR technology to treat high-ammonia wastewater. Under the condition of loading nitrogen rate of 0.1 kg·N/(m3·d), the maximum removal efficiency of ammonia nitrogen and total nitrogen (TN) reached 96.08 and 84.86%, respectively. qPCR and high-throughput analysis confirmed the stable hierarchical community structure of space microorganisms. De Sanctis et al. (2020) employed SBBGR technology for treating sewage sourced from sewage treatment plants while concurrently recovering heat energy. They achieved impressive removal efficiency, with suspended solids, chemical biochemical oxygen demand, and ammonia reaching 90%, and the TN removal rate reaching 70%. In addition, the researchers also used SBBGR to treat dye wastewater (Xavier et al. 2023), leachate (Liu et al. 2022), and so on.

Although microorganisms cannot use lignin as a substrate for their growth, lignin can be effectively degraded through co-metabolism (Nzila 2013). Therefore, aerobic granular sludge (AGS) can be cultured with SBBGR and used to treat wastewater containing lignin models. At present, there is no study on the treatment of lignin wastewater with SBBGR. Therefore, in this study, three sequencing batch biofilter granular reactors were used to degrade model lignin wastewater containing 2,6-dimethoxyphenol (SBBGR1), 4-methoxyphenol (SBBGR2), and vanillin (SBBGR3), respectively. The three lignin models correspond to S-lignin, H-lignin, and G-lignin, respectively. The degradation of the lignin model was analyzed by COD and UV–Vis spectra of model lignin wastewater, and the microbial detection of the AGS before and after the treatment of the lignin model was analyzed by high-throughput sequencing.

Reactor and operation

The schematic diagram of the experimental device is shown in Figure 1. The primary structure of the reactor was a plexiglass cylinder with a height of 50 cm and an inner diameter of 5 cm. The lower section of the reactor was filled with a total of 200 polyethylene K1 carriers (Zhengjie Environmental Technology, Zhejiang, China). The diameter, height, and surface area of the carrier are 10 mm, 10 mm, and 980 m2/m3, respectively. The effective volume of the biological bed was 800 mL. The aeration stone connected to the air pump (Guangdong Haili Co., Ltd, Guangdong, China) provides oxygen to the reactor. The model lignin wastewater was continuously circulated in the reactor through the peristaltic pump (PR). The effluent pump (Pout) and the influent pump (Pin) were used to discharge the treated water sample and inject the model lignin wastewater to be treated, respectively.
Figure 1

Schematic diagram of SBBGR.

Figure 1

Schematic diagram of SBBGR.

Close modal

The operational cycle of SBBGR consisted of three consecutive stages: influent (3 min), reaction (354 min), and effluent (3 min). Each operational cycle included a water exchange rate of 50%, with a Hydraulic Residence Time (HRT) of 12 h. The aeration of the reactor and the automatic water inlet and outlet were regulated by time control switches (Delixi Group Co. Ltd, Zhejiang, China). The entire process of dissolved oxygen was kept in 4–6 mg/L, the reactor was operated at room temperature, and the pH value was kept in 6.8–7.2.

Synthetic medium and inoculation

The experimental procedure comprised three stages: culture, acclimation, and stable operation. The influent COD of the three reactors was maintained at about 600 mg/L, and the COD:N:P ratio was maintained at 100:5:1. The composition of model lignin wastewater was as follows: Sodium acetate 769 mg/L, 2,6-dimethoxyphenol 320.86 mg/L, 4-methoxyphenol 290.56 mg/L, vanillin 335.38 mg/L, NH4Cl 114.64 mg/L, KH2PO4 26.32 mg/L, MgSO4 10 mg/L, CaSO4 20 mg/L, NaHCO3 100 mg/L, and trace elements were 1 mL/L. The trace elements consisted of FeCl3·6H2O 3,600 mg/L, MnCl2·4H2O 360 mg/L, CuSO4·5H2O 80 mg/L, ZnSO4·7H2O 300 mg/L, and CoCl2·6H2O 360 mg/L. The carbon source in the culture stage was all provided by sodium acetate. Upon the formation of mature AGS and the stabilization of COD reduction efficiency in the reactor, the experiment transitioned into the acclimation stage. In the acclimation stage, the carbon source in the wastewater is provided by sodium acetate and lignin models. When the COD reduction efficiency tends to be stable, the proportion of lignin model in the carbon source in the simulated wastewater is increased until it enters the stable operation stage. In the stable operation stage, the carbon source was all provided by the lignin models (Table 2).

Table 2

Composition of carbon source in acclimation stage

Proportion of lignin model (%)Influent (1L)
Sodium acetate (COD = 600 mg/L)Lignin model (COD = 600 mg/L)
20 800 mL 200 mL 
40 600 mL 400 mL 
60 400 mL 600 mL 
80 200 mL 800 mL 
Proportion of lignin model (%)Influent (1L)
Sodium acetate (COD = 600 mg/L)Lignin model (COD = 600 mg/L)
20 800 mL 200 mL 
40 600 mL 400 mL 
60 400 mL 600 mL 
80 200 mL 800 mL 

The inoculated sludge was obtained from the secondary sedimentation tank of a sewage treatment plant in Guangzhou. The mixed liquid suspended solids (MLSS), mixed liquid volatile suspended solids (MLVSS), and sludge volume index (SVI30) of the inoculated sludge were measured as 3,850 mg/L, 1,850 mg/L, and 151.45 mL/g, respectively.

Analytical methods and procedures

COD, TN, total phosphorus (TP), MLSS, and MLVSS were determined according to standard methods (APHA 2005). COD was measured daily, while TN and TP were measured every 10 days. Measurements of MLSS, MLVSS, and SVI30 were carried out in the inoculated sludge and SBBGR1 at the conclusion of the cultivation stage.

After 60 days of stable operation, 0.45 μm aqueous polyether sulfone (PES) microporous filter membrane (Beekman Biotechnology Co., HuNan, China) were used to filter the influent and effluent of the three reactors. After that, the filtered samples were diluted 10 times, and then analyzed using a UV spectrophotometer (DR6000; Hach, USA) with a wavelength range of 200–500 nm.

Three parallel experiments were conducted for each of the above indicators.

DNA extraction and PCR amplification of partial bacterial 16S rRNA gene

A small amount of inoculated sludge and AGS obtained post-degradation of lignin models was collected. DNA extraction was conducted using the Magen Hipure soil DNA kit, and DNA concentration was quantified using the Qubit® dsDNA HS Assay Kit. Subsequently, polymerase chain reaction (PCR) was employed to amplify the V3 and V4 hypervariable regions of the 16S rRNA gene of bacteria. The sequencing library was constructed using a MetaVX Library Preparation Kit (GENEWIZ, Inc., South Plainfield, NJ, USA). PCR amplification was performed using 20–30 ng of DNA, with the forward primer sequence ‘CCTACGGRRBGCASCAGKVRVGAAT’ and reverse primer sequence ‘GGACTACNVGGGTWTCTAATCC’. The PCR mixture (25 uL) consisted of 2.5 uL TransStart buffer, 2 ul dNTPs, 1 uL of each primer, 0.5 uL TransStart Taq DNA polymerase, and 20 ng template DNA. The PCR program comprised an initial denaturation at 94 °C for 3 min, followed by 24 cycles of denaturation at 95 °C for 5 s, annealing at 57 °C for 90 s, elongation at 72 °C for 10 s, and a final extension at 72 °C for 5 min. Indexed adapters were introduced to the ends of the amplicons via limited cycle PCR. Finally, the library underwent purification with magnetic beads.

High-throughput sequencing and bioinformatics analysis

The DNA concentration was determined using a microplate reader (Tecan, Infinite 200 Pro), while the fragment size was assessed through 1.5% agarose gel electrophoresis, aiming for fragments of approximately 600 base pairs. Subsequent to this, next-generation sequencing was performed on an Illumina Miseq/Novaseq Platform (Illumina, San Diego, CA, USA) at Genewiz, Inc. (South Plainfield, NJ, USA). The sequencing process involved automated cluster generation and 250/300 paired-end sequencing with dual reads. Following sequencing, quality filtering was conducted, retaining sequences with a length greater than 200 base pairs and excluding those containing ambiguous bases (N). Chimeric sequences were then purified before undergoing operational taxonomic unit (OTU) clustering using VSEARCH clustering (version 1.9.6) with a sequence similarity threshold set at 97%. Subsequently, the RDP classifier (Ribosomal Database Program) Bayesian algorithm was utilized for taxonomic analysis of OTU representative sequences. Community composition statistics were generated at different taxonomic levels for each sample. Finally, alpha diversity indices including Shannon and Chao 1 were calculated based on the flat random sampling of sequences obtained from the OTU analysis results.

Cultivation of AGS

Figure 2(a) and 2(b) shows the change process of SBBGR biological bed and AGS morphology, respectively. When the reactor was just started, the sludge was suspended in the pores of the fillers and between the fillers. By the 15th day of cultivation, a yellow biofilm formed inside the filler. After 25 days of cultivation, many fillers exhibited the emergence of AGS characterized by small volume and uneven shape. The color of the biofilm was deepened, possibly because the sludge concentration in the reactor increased, forming part of the anaerobic area leading to the sludge blackening. With the growth and reproduction of microorganisms and bacteria, the thickness of the biofilm gradually increased, and the flocculent sludge in the pores gradually became compact. On the 40th day, the filler in the reactor could form AGS with relatively regular shape but small volume. It has been suggested that the shear force plays a certain role in the formation of particle morphology and the selection of aggregation strains (Lochmatter & Holliger 2014). With the progress of culture, the volume of aerobic particles in the reactor will further increase, resulting in an increase in shear force, and then the AGS will be separated from the carrier. Taking a random piece of the carrier and placing it into the water, it can be found that the biomass in the reactor was composed of two different parts: a biofilm attached to the carrier and a very dense granular sludge that spontaneously separates from the carrier. According to the research results of Di Iaconi et al., the formation of AGS can be divided into five stages: (1) forming a thin biofilm covering the carrier completely. (2) Sludge with poor settling performance is discharged from the reactor and further grows with good settling performance. (3) The thickness of biofilm continued to increase. (4) The attached biofilm breaks down, releasing biofilm particles. (5) The rearrangement of biofilm particles in smooth particles (Di Iaconi et al. 2005).
Figure 2

Schematic diagram of the sludge granulation process in SBBGR.

Figure 2

Schematic diagram of the sludge granulation process in SBBGR.

Close modal

After the completion of the culture stage, four carriers of SBBGR1 were taken (three parallel experiments) and the MLSS, MLVSS, and SVI of AGS were 31.38, 24.74 g/L, and 57.26 mL/g, respectively.

3.2. Culture and acclimation stage

Figure 3 shows the COD removal effects of the three reactors in the culture and acclimation stages. Figure 3(a) shows the removal of COD in the reactor for degradation of SBBGR1. The culture stage lasted for 77 days, and the reactor was in the adaptive state in the first 2 days after start-up, and the COD reduction efficiency was low (60.48 ± 15.21%). From the third day to the end of culture, the COD removal effect was relatively stable, the average COD in effluent was 53.41 ± 15.19 mg/L, and the average COD reduction efficiency was 91.42 ± 2.43%.
Figure 3

COD reduction efficiency in the culture and acclimation stages. (a) 2,6-dimethoxyphenol, (b) 4-methoxyphenol, and (c) vanillin.

Figure 3

COD reduction efficiency in the culture and acclimation stages. (a) 2,6-dimethoxyphenol, (b) 4-methoxyphenol, and (c) vanillin.

Close modal

After that, the reactor entered the acclimation stage, and the microorganisms in the reactor were adapted to the characteristics of the substrate by gradually increasing the proportion of 2,6-dimethoxyphenol in the water. The average COD of effluent was 51.79 ± 12.59, 60.88 ± 12.21, 56.21 ± 10.08, and 74.14 ± 32.00 mg/L, respectively, during the acclimation stage when 2,6-dimethoxyphenol accounted for 20, 40, 60, and 80%, respectively. The average COD reduction efficiency reached 91.71 ± 2.02, 90.22 ± 1.98, 90.96 ± 1.61, and 88.16 ± 5.01%, respectively, and the average COD reduction efficiency in the whole acclimation stage was 90.32 ± 3.15%.

Figure 3(b) shows the reduction of COD in a reactor treating SBBGR2. The culture stage lasted for 72 days, and the first 2 days after the reactor was started were in the adaptive state, and the COD reduction efficiency was low (60.92 ± 11.84%). From the third day to the end of culture, the COD reduction efficiency was relatively stable, the average effluent COD was 49.23 ± 14.99 mg/L, and the average COD reduction efficiency was 92.09 ± 2.40%.

After that, the reactor entered the acclimation stage, and the addition of 4-methoxyphenol in the acclimation stage was the same as that of 2,6-dimethoxyphenol. In the acclimation stage where 4-methoxyphenol accounted for 20, 40, 60, and 80%, the average COD of effluent was 88.28 ± 47.19, 69.78 ± 14.85, 66.88 ± 16.74, and 61.85 ± 10.25 mg/L, respectively. The average COD reduction efficiency was 85.76 ± 7.59, 88.76 ± 2.36, 89.22 ± 2.68, and 89.96 ± 1.69%, respectively, and the average COD reduction efficiency in the whole acclimation stage was 88.27 ± 4.77.

Figure 3(c) shows the removal effect of SBBGR3 on COD at the acclimation stage. The culture stage lasted for 79 days, the average COD of the final effluent was 54.63 ± 16.89 mg/L, and the average COD reduction efficiency was 91.04 ± 2.78%.

After that, the reactor enters the acclimation stage. In the acclimation stage when vanillin accounted for 20, 40, 60, and 80%, the average COD of effluent was 78.74 ± 46.42, 59.33 ± 15.56, 58.27 ± 15.43, and 57.46 ± 13.68 mg/L, respectively. The average COD reduction efficiency was 86.85 ± 7.75, 90.54 ± 2.49, 90.62 ± 2.40, and 90.77 ± 2.22%, respectively. The average COD reduction efficiency in the whole acclimation stage was 90.64 ± 2.37%.

As can be seen from Figure 3, there was a common point in the acclimation stage of wastewater simulated by the degradation of three lignin models by SBBGR, that was, the COD reduction efficiency of each acclimation stage shows a trend of first decreasing (almost 5–20%) and then recovering to a high reduction efficiency (exceeding 90%) in a short period of time. This indicates that the microorganisms in SBBGR have a strong impact resistance to the changes of organic compounds in water, and can recover to a higher degradation and removal effect in a short time. In addition, according to the average COD reduction efficiency of the three lignin models in the model lignin wastewater during the four acclimation stages, the increasing proportion of lignin models in the water did not affect the degradation effect of SBBGR on organic matter. On the one hand, SBBGR can effectively degrade S-, H-, and G-type lignin models. On the other hand, these three lignin models have no significant inhibitory effect on microbial activity in the reactor.

Stable operation stage

In the stable operation stage, the carbon source in the model lignin wastewater was all provided by the corresponding lignin model. Figure 4(a) shows the COD removal effect treated by SBBGR1. The treatment stage lasted for 89 days, with an average COD of 49.06 ± 8.98 mg/L and an average COD reduction efficiency of 92.06 ± 1.42%. Figure 4(b) shows the COD removal effect treated by SBBGR2. The treatment period lasts for 78 days, the average COD of effluent was 48.49 ± 9.33 mg/L, and the average COD reduction efficiency was 92.06 ± 1.57%. Figure 4(c) shows the COD removal effect treated by SBBGR3. The treatment period lasts for 71 days, the average COD of effluent was 45.01 ± 8.19 mg/L, and the average COD reduction efficiency reached 92.67 ± 1.32%. Table 3 shows COD reduction efficiency of the three reactors in the whole process.
Table 3

COD reduction efficiency across different experimental stages

Reduction efficiency at different stagesSBBGR1SBBGR2SBBGR3
Culture stage 91.42 ± 2.43% 92.09 ± 2.40% 91.04 ± 2.78% 
Acclimation stage (20%) 91.71 ± 2.02% 85.76 ± 7.59% 86.85 ± 7.75% 
Acclimation stage (40%) 90.22 ± 1.98% 88.76 ± 2.36% 90.54 ± 2.49% 
Acclimation stage (60%) 90.96 ± 1.61% 89.22 ± 2.68% 90.62 ± 2.40% 
Acclimation stage (80%) 88.16 ± 5.01% 89.96 ± 1.69% 90.77 ± 2.22% 
Stable operation stage 92.06 ± 1.42% 92.06 ± 1.57% 92.67 ± 1.32% 
Reduction efficiency at different stagesSBBGR1SBBGR2SBBGR3
Culture stage 91.42 ± 2.43% 92.09 ± 2.40% 91.04 ± 2.78% 
Acclimation stage (20%) 91.71 ± 2.02% 85.76 ± 7.59% 86.85 ± 7.75% 
Acclimation stage (40%) 90.22 ± 1.98% 88.76 ± 2.36% 90.54 ± 2.49% 
Acclimation stage (60%) 90.96 ± 1.61% 89.22 ± 2.68% 90.62 ± 2.40% 
Acclimation stage (80%) 88.16 ± 5.01% 89.96 ± 1.69% 90.77 ± 2.22% 
Stable operation stage 92.06 ± 1.42% 92.06 ± 1.57% 92.67 ± 1.32% 
Figure 4

COD reduction efficiency in the stable operation stage. (a) 2,6-dimethoxyphenol, (b) 4-methoxyphenol, and (c) vanillin.

Figure 4

COD reduction efficiency in the stable operation stage. (a) 2,6-dimethoxyphenol, (b) 4-methoxyphenol, and (c) vanillin.

Close modal

In Figure 4, SBBGR has an excellent degradation effect on these three lignin models, and the COD removal effect has been very stable and efficient during a long treatment cycle. This can be attributed to the fact that the three reactors have experienced a long period of acclimation, and the internal microorganisms exhibited robust environmental adaptability and transitioned to utilizing the lignin model as a substrate. Vashi et al. (2018) applied AGS cultured in SBR to treat pulping wastewater and studied the removal of tannin and lignin. It was found that at the concentration of tannin and lignin of 50 mg/L, the reduction efficiency of AGS was 97%. The reduction efficiency of 60% was achieved at 100 mg/L tannin and lignin concentration. In contrast, AGS cultured in SBBGR has more advantages for lignin degradation, possibly because the concentration of AGS in SBBGR was higher and the microbial flora was abundant. In addition, the selected lignin model structure was relatively simple was also one of the important reasons.

Figure 5(a) shows the TN reduction efficiency of the three reactors. The mean TN of the effluent from the reactors treating the model lignin wastewater of 2,6-dimethoxyphenol, 4-methoxyphenol, and vanillin was 5.96 ± 1.52, 7.47 ± 1.14, and 5.58 ± 0.98 mg/L, respectively. The average reduction efficiency of TN was 80.15 ± 4.84, 75.10 ± 3.79, and 81.42 ± 3.28%, respectively. Figure 5(b) shows the TP removal effect of the three reactors. The mean TP of the reactor effluent treating the model lignin wastewater of 2,6-dimethoxyphenol, 4-methoxyphenol, and vanillin was 2.68 ± 0.26, 2.73 ± 0.26, and 2.65 ± 0.31 mg/L, respectively. The average reduction efficiency of TP was 55.32 ± 2.33, 54.54 ± 4.38, and 55.87 ± 5.13%, respectively.
Figure 5

The reduction efficiency of TN and TP in the treatment stage. (a) TN and (b) TP.

Figure 5

The reduction efficiency of TN and TP in the treatment stage. (a) TN and (b) TP.

Close modal

As can be seen from Figure 5, SBBGR has a good removal effect on TN and TP of model lignin wastewater, with reduction efficiency of 71.67–85.67% and 48.00–65.33%, respectively. This may be because AGS has aerobic zone, anoxic zone, and anaerobic zone at the same time, and microorganisms such as nitrifying bacteria, denitrifying bacteria, and phosphorus accumulating bacteria can multiply in large numbers, and TN and TP can be effectively removed through nitrifying – denitrification and bioenhanced phosphorus removal (McCarty 2018). Chen et al. (2022) studied the granular sludge with three different particle sizes of 0.5–1.5 mm granules (GS), 1.5–3.0 mm granules (GS), and 3.0–5.0 mm granules (GL), and found that the activities of GM dehydrogenase and nitrogen invertase were 1.32–3.09 times that of GS and GL. It has high decarbonization and nitrogen removal capacity.

The aromatic compounds have strong absorption of ultraviolet light, so the ultraviolet absorption spectra are determined during the stable operation stage. 255–300 nm is the characteristic absorption band of the benzene ring, and the absorption near 300–400 nm is generated by the conjugated carbonyl group or conjugated double bond on the side chain of the benzene ring. The water inlet and outlet of the reactor were extracted, the UV absorption spectra of the water samples were measured, and the change rule of absorbance was analyzed to study the change of lignin model structure during stable operation. Figure 6(a) shows the ultraviolet spectra treated by SBBGR1. The absorption peak of 2,6-dimethoxylphenol was at 267 nm, and the absorbance at 267 nm was reduced by 95.48% after SBBGR treatment. Figure 6(b) shows the ultraviolet spectra treated by SBBGR2. The absorption peak of 4-methoxyphenol was at 221 and 288 nm. After SBBGR treatment, the absorbance at 220 and 288 nm was reduced by 74.54 and 98.69%, respectively. Figure 6(c) shows the ultraviolet spectra of inlet and effluent treated by SBBGR3. The absorption peaks of vanillin were at 226, 281, and 316 nm. After SBBGR treatment, the absorbance was reduced by 96.61, 98.82, and 99.26%, respectively.
Figure 6

UV–Vis spectra of simulant wastewater in the treatment stage. (a) 2,6-dimethoxyphenol, (b) 4-methoxyphenol, and (c) vanillin.

Figure 6

UV–Vis spectra of simulant wastewater in the treatment stage. (a) 2,6-dimethoxyphenol, (b) 4-methoxyphenol, and (c) vanillin.

Close modal

In Figure 6, after SBBGR treatment, the maximum UV characteristic absorption peaks of the three lignin model substances disappeared, indicating that the benzene ring structure was destroyed and the lignin model substances were effectively degraded. Han et al. (2019) selected the four most commonly used low-cost catalysts, ilmenite (FeTiO3), bentonite (Al–SiOH), activated carbon (AC), and red mud (RM), to catalyze the rapid pyrolysis of lignin in a modified fixed bed reactor. The results indicate that only AC can effectively promote the generation of single ring aromatic hydrocarbons (MAHs). The results show that bentonite, RM, and AC can effectively promote the dehydration reaction due to the presence of strong acidic sites, making it the main way of deoxygenation during pyrolysis. In contrast, SBBGR was more economical and environmentally friendly in degrading lignin models, and can run for a long time and maintain high removal efficiency. Studies have shown that chlorobium is a photoactive organic autotrophic bacteria that grows in anaerobic and luminous waters. In photosynthesis without releasing oxygen, chlorobium can fix sulfur and nitrogen through the consumption of reducing arsenic and hydrogen sulfide in organic compounds.

Microbial community structure

To analyze the changes of microbial community in the reactor during the simulated wastewater treatment process of lignin models, the inoculated sludge and the AGS treated with lignin models were respectively taken for microbial detection and analysis. The microbial richness and diversity index of different sludge samples are shown in Table 4. The Ace and Chao 1 indices represent the richness of the flora. After the lignin model material was treated in the three reactors, these two indices all increase, indicating that the flora species in the reactors have increased after the lignin model material was degraded. The increase in richness can be attributed to the transformation of microorganisms in the reactor from sodium acetate to lignin model material, and the internal microbial community enhanced species richness through evolution, thereby facilitating the degradation of lignin model material by SBBGR. The Shannon and Simpson indices represent microbial diversity, which was a comprehensive index of species richness and evenness, and there was no uniform rule in the three reactors. After SBBGR treatment of 4-methoxyphenol and vanillin model lignin wastewater, bacterial diversity decreased slightly. After SBBGR treatment with 2,6-dimethoxyphenol, bacterial diversity increased. This may be because the sludge concentration in SBBGR was very high, and there were a variety of microorganisms that could degrade 2,6-dimethoxyphenol, so bacterial diversity increased.

Table 4

Microbial richness and diversity of different sludge samples

SampleAceChao 1ShannonSimpsonFraction of coverage
Inoculated sludge 111.437 114.000 5.608 0.961 1.000 
After 2,6-dimethoxylphenol treatment 160.776 160.167 5.870 0.969 1.000 
After 4-methoxyphenol treatment 132.719 133.600 5.332 0.958 1.000 
After vanillin treatment 136.097 135.200 5.237 0.922 1.000 
SampleAceChao 1ShannonSimpsonFraction of coverage
Inoculated sludge 111.437 114.000 5.608 0.961 1.000 
After 2,6-dimethoxylphenol treatment 160.776 160.167 5.870 0.969 1.000 
After 4-methoxyphenol treatment 132.719 133.600 5.332 0.958 1.000 
After vanillin treatment 136.097 135.200 5.237 0.922 1.000 

The microbial analysis of AGS treated with three kinds of lignin models wastewater was compared with that of inoculated sludge. Figure 7 shows the relative abundance of microbial communities at the phylum level. At the phylum level, the dominant phyla did not change, and they were Proteobacteria and Bacteroidota. Both phylum have been reported to be related to nitrogen removal (Connan et al. 2016). The inoculated sludge accounted for 54.12 and 22.88%, respectively. The proportions of 2,6-dimethoxyphenol were 31.89 and 37.76%, respectively. The proportions of 4-methoxyphenol were 39.94 and 22.90%, respectively. The proportions of vanillin and vanillin were 30.96 and 46.51%, respectively. On the whole, the proportion of Proteobacteria in the three AGS decreased, while the proportion of Bacteroidota increased.
Figure 7

Relative abundance of microbial communities before and after treatment of model lignin wastewater at the phylum level. (a) Inoculated sludge, (b) after 2,6-dimethoxylphenol treatment, (c) after 4-methoxyphenol treatment, and (d) after vanillin treatment.

Figure 7

Relative abundance of microbial communities before and after treatment of model lignin wastewater at the phylum level. (a) Inoculated sludge, (b) after 2,6-dimethoxylphenol treatment, (c) after 4-methoxyphenol treatment, and (d) after vanillin treatment.

Close modal

The subdominant phyla were obviously different. The secondary dominant phyla in the inoculated sludge were Chloroflexi (7.19%) and Firmicutes (5.09%). After treatment with 2,6-dimethoxylphenol, Myxococcota (5.52%) and Acidobacteriota (4.48%) were the secondary dominant phyla. After treatment with 4-methoxyphenol, Chloroflexi (12.54%) and Acidobacteriota (12.49%) were the secondary dominant phyla. Desulfobacterota (7.14%) and Acidobacteriota (4.74%) were the secondary dominant phyla in vanillin treatment.

Figure 8 shows the relative abundance of microbial communities at the genus level. At the genus level, the dominant genus of inoculated sludge was Acinetobacter, accounting for 15.46%. The dominant genus species treated with 2,6-dimethoxyphenol were Kapabacteriales and Chlorobaculum, accounting for 7.97 and 7.38%, respectively. The dominant strain was SBR1031, accounting for 11.77 and 11.77%, respectively. Chlorobium was the dominant bacterium after vanillin treatment, accounting for 25.37%.
Figure 8

Relative abundance of microbial communities before and after treatment of model lignin wastewater at the genus level. (a) Inoculated sludge, (b) after 2,6-dimethoxylphenol treatment, (c) after 4-methoxyphenol treatment, and (d) after vanillin treatment.

Figure 8

Relative abundance of microbial communities before and after treatment of model lignin wastewater at the genus level. (a) Inoculated sludge, (b) after 2,6-dimethoxylphenol treatment, (c) after 4-methoxyphenol treatment, and (d) after vanillin treatment.

Close modal

Bdellovibrio (3.77%), f__Xanthobacteraceae_Unclassified (3.55%), and Hyphomicrobium (3.12%) were the predominant genus treated with 2,6-dioxylphenol. The subdominant genus treated with 4-methoxyphenol were f__Blastocatellaceae_Unclassified (8.19%) and f__Comamonadaceae_Unclassified (7.77%). The subdominant genus after vanillin treatment were Thauera (4.91%), Denitratisoma (4.59%), and Azohydromonas (4.08%).

Wang et al. treated synthetic wastewater with SBR technology, and the dominant bacteria in the final reactor also included Kapabacteriales (Wang et al. 2021). Studies have shown that Chlorobium is a photoactive organic autotrophic bacteria that grows in anaerobic and luminous waters. In photosynthesis without releasing oxygen, Chlorobium can fix sulfur and nitrogen through the consumption of reducing arsenic and hydrogen sulfide in organic compounds (Seviour et al. 2011).

Based on the microbial community changes after the treatment of the lignin model in the above three reactors, Proteobacteria and Bacteroidota were always the dominant bacteria. It can be seen that these two types of bacteria play a key role in the formation of aerobic particulate sludge and the degradation of lignin model. Both have the ability to oxidize and degrade organic carbon into CO2. Heinz et al. (2017) conducted high-throughput DNA sequencing of paper mill sludge, and found that Proteobacteria and Bacteroidota were the main microbial communities. At the same time, these two types of bacteria were also the dominant bacteria in the treatment of various organic wastewater, such as pharmaceutical wastewater and petrochemical wastewater (Yang et al. 2015; Ouyang et al. 2019). In addition, subdominant bacteria have also played a supporting role in the degradation process of lignin model materials. For example, Cyanobacteria can degrade lignin by secreting lignin decomposing enzymes and antioxidant enzymes (Chamkha et al. 2001; Saha et al. 2010), Desulfobacterota contains a variety of sulfate-reducing bacteria. Capable of using sulfate as an electron acceptor and degrading aromatic compounds, some genera of Firmicutes were not only degraders of cellulose and hemicellulose, but also participate in lignin degradation (Chamkha et al. 2001). Acidobacteriota also accounts for a certain proportion in sewage treatment. Acidobacterta are abundant and possess the potential of polyphosphate and glycogen accumulation, nitrate reduction and fermentation (Kristensen et al. 2021).

At the genus level, significant changes were observed in the three reactors following the treatment of model lignin wastewater. These changes could be attributed to evolution among bacteria within the reactors, enhancing their biological diversity. Various microorganisms assumed distinct roles in maintaining the stability of AGS and facilitating the degradation of lignin models. For instance, Thauera demonstrated competence in the degradation of aromatic, compounds such as quinoline and benzodiazepines (Mechichi et al. 2002).

The AGS in SBBGR demonstrated robust impact and effectively degraded S-type, H-type, and G-type lignin models. The high sludge concentration and diverse microbial communities within SBBGR contributed to its effective degradation capabilities. Proteobacteria and Bacteroidota were consistently dominant phyla, crucial for lignin model degradation. After treatment with lignin models, significant changes occurred at the genus level, with dominant bacteria (e.g., Acinetobacter, 15.46% initially) declining or disappearing entirely (≤0.01%).

This work was supported by the Guangdong Basic and Applied Basic Research Foundation under Grant [2024A1515011586], the National Foreign Expert Project under Grant [G2023163008L], the Science and Technology Planning Project of Guangdong Province under Grant [2021A1515010645], and the Key Project of Research and Development Plan of Guangdong Province under Grant [2022B0202020002].

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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