N, P and C removal simultaneously and microbial population numbers in a cyclic activated sludge system treating village and township domestic wastewater by altering the cycle times

Under natural conditions, the process of nutrient overload in lakes occurs extremely slowly. Liu et al. (2021a) showed that, the most common cause of eutrophication is the excessive input of inorganic nitrogen (N) and inorganic phosphorus (P) caused by human activities. The current method commonly used to remove N and P from wastewater is biological nutrient removal (BNR) technology. The cyclic activated sludge system (CASS), also known as the cyclic activated sludge technology (CAST), as a variant of the sequencing batch reactor (SBR) process, is also part of the BNR technologies. This process is widely used in domestic wastewater and industrial wastewater treatment because of its simple composition, stable operation, low infrastructure costs, etc.

The CASS process has already seen successful applications. He & Hu (2022) employed the ‘anaerobic bioreactor-CASS process’ to treat wastewater from an eel processing plant, achieving removal rates of over 90% for major pollutants. Su & Zhang (2020) utilized a combined process of composite hydrolytic acidification and CASS to treat high-proportion dyeing wastewater. However, the study lacks investigation into the impact of key parameters of the CASS reactor on operational efficiency which calls for further attention and research. The wastewater enters the reactor generally by continuous or intermittent feed. Liang et al. (2015) examined the effect of two types of feeding water on N₂O emissions from a CASS system. The entry of the carbon source in the continuous feed increases the TN removal rate and the amount of N₂O produced by the process of denitrification is lower. High-throughput 16S rRNA gene sequencing also revealed a higher abundance of denitrifying bacteria in continuous feeding water compared to intermittent feeding water. Juan et al. (2010) used a computer program to detect oxidation reduction potential (ORP) and pH in water in real-time and to control the CAST reactor staged feeding water. This provides better resistance to water quality fluctuations in the influent, and the effluent TN concentration is lower than 2 mg L⁻¹. The TN removal rate is about 98% and the TP removal rate is higher than 90%. The appropriate temperature is often considered to be the key to obtaining good treatment results in the CASS process. Wang et al. (2010) evaluated the effects of temperature and dissolved oxygen (DO) on nitrogen removal performance in wastewater treatment plants (WWTPs) using the CAST process in different seasons. The results showed that at temperatures below 15°C, the biological activity was inhibited and the specific oxygen uptake rate (SOUR) was quite low, about 1.2 O₂ g SS⁻¹·h⁻¹ (15°C; SS is a volatile fraction). Even if DO increased from 0.7 to 3.0 mg L⁻¹, the N removal rate could not be effectively increased. However, this does not indicate that DO has no effect on simultaneous nitrogen and phosphorus removal. Yadav et al. (2014) studied the changes in microbial communities under different DO conditions and concluded that the maximum bacterial diversity was observed at a DO concentration of 2 mg L⁻¹. The effects of DO and COD/N on pollutant removal by the CASS process in highland areas were also investigated by Xu et al. (2019). It indicates that DO has an effect on the removal of pollutants when temperature is not a controlling condition. The pollutant removal effect is best when the DO concentration is 2–2.5 mg L⁻¹, or the COD/N ratio is 7:1. The population structure of the colonies under different conditions could explain the cause of this result. It has also been investigated to improve the CASS reactor by casting fillers. Araujo et al. (2013) used a new biomass carrier to reduce sludge production with improved performance of the CASS reactor for COD and TSS removal. Kee et al. (2021) analyzed the removal rate of volatile fatty acids (VFA) in SBR at different hydraulic retention times (HRTs). The SBR operation achieved a removal rate of 85.4 ± 1.8% at 14 days HRT. Tao et al. (2023) optimized simultaneous nitrification and denitrification-sequential batch reactor (SND-SBR). The optimal conditions were determined by statistical modeling to be 6.8 h HRT (anaerobic/aerobic/anoxic: 1.77 h/2.77 h/2.27 h) by referring to the research of Tao et al. (2023). Ding et al. (2020) suggested that extending HRT during CASS could remove antibiotic resistance genes and antibiotic-resistant bacteria more extensively from industrial WWTPs. It can be seen that the improvement and optimization of the CASS reactor can improve the removal of pollutants and also reduce the production of other emissions. Compared to previous studies investigating the influence of hydraulic retention time on CASS reactors, the focus was solely on removal rate, neglecting the variation in microbial community structure during different time periods. However, the microbial activities driving the removal of organic substances are crucial for the proper functioning of the reactor. In this study, the effect of different HRTs on simultaneous denitrification and phosphorus removal in the CASS system was investigated by adjusting the timing of anaerobic, aerobic and anoxic phases. Microbial communities during this process were also been studied which will result in the best pollutant removal rate.

In this experiment, simulated wastewater was used as the feed water of the reactor, and the concentrations of the main pollutants chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP) and ammonia nitrogen were 300–330, 38–42, 2.5–3.5 and 28–32 mg L⁻¹, respectively. Feed water pH is adjusted to neutral by HCl and NaOH. The simulated effluent formula is (g L⁻¹): 0.2572 glucose (Tianjin Kemiou Chemical Reagent Co., Ltd), 0.0319 anhydrous sodium acetate (Tianjin Kemiou Chemical Reagent Co., Ltd), 0.125 sodium bicarbonate (Tianjin Kemiou Chemical Reagent Co., Ltd), 0.0042 potassium chloride (Tianjin Zhiyuan Reagent Co., Ltd), 0.0025 Calcium Chloride (Sinopharm Chemical Reagent Co., Ltd), 0.1108 Ammonium Chloride (Tianjin Kemiou Chemical Reagent Co., Ltd), 0.0132 Potassium Dihydrogen Phosphate (Guangdong Guanghua Sci-Tech Co., Ltd), 0.0275 Magnesium Sulfate Heptahydrate (Guangdong Guanghua Sci-Tech Co., Ltd), 0.0072 Potassium Nitrate (Tianjin Kemiou Chemical Reagent Co., Ltd), 0.0429 Urea (Shanghai Macklin Biochemical Co., Ltd). 0.12 mL of nutrient solution is added per liter of simulated effluent to replenish various trace elements required by the sludge. The return sludge from the secondary sedimentation tank of Zheng Dong New District (Zhengzhou, Henan Province) was used as the seed sludge for this experiment. After the sludge was domesticated by aeration, the mixed liquor suspended solids (MLSS) concentration was 4.028 g L⁻¹, and the mixed liquor volatile suspended solids (MLVSS) concentration was 3.156 g L⁻¹. To ensure the stability of this CASS reactor, about 100–200 mL of residual sludge was discharged from the reactor every day during operation. Since the reactor operating cycle varies for each operating condition, it has different sludge retention times, ranging from 24 to 16 days. At the end of the investigation under one condition, sludge samples were obtained from the reactor for further analysis of the sludge microbial community.

In this study, the inlet and outlet water samples of the CASS reactor were measured daily on the same day according to the standard method. The water samples needed to be centrifuged at 4,000 r min⁻¹ for 5 min before measurement. Among them, the total nitrogen was dissolved by ultraviolet spectrophotometry with potassium persulfate, the ammonia nitrogen was dissolved by Nessler's reagent spectrophotometry, the total phosphorus was dissolved by ammonium molybdate spectrophotometry, and the COD was dissolved by rapid digestion method.). Standard Methods for the Examination of Water and Wastewater, 21st ed., Washington, DC, USA. Prevent sludge precipitation from increasing the turbidity of the solution and affecting the spectrophotometric detection results. Sludge samples were collected from the reactor and the supernatant was removed by centrifugation for storage at −20°C and kept until final analysis. The main instruments used in this study were the Intelligent Dissolution Instrument 5B-1F (V8) (Beijing Lianhua Yongxing Technology Development Co., Ltd), UV–Vis spectrophotometer N5000 (Shanghai Uco Instruments Co., Ltd), portable dissolved oxygen meter JPB-607A (INESA Scientific Instruments Co., Ltd) and portable pH meter PHBJ-260 (INESA Scientific Instruments Co., Ltd).

The sludge samples were uniformly sent to Bioengineering (Shanghai) Co., Ltd for Miseq library preparation and Miseq high-throughput sequencing. The main processes include quality control of genomic DNA, design and synthesis of primer junctions, PCR amplification and product purification, PCR product quantification and homogenization, and finally, Miseq high-throughput sequencing and bioinformatics analysis. Depending on the type of activated sludge sample, genomic DNA was accurately quantified using the Qubit 3.0 DNA Assay Kit to determine the amount of DNA that should be added for PCR amplification. The PCR primer design was then performed and the library was constructed using a two-step PCR amplification method. The primers used for the first round of PCR have been fused with the V3–V4 universal primers of the Miseq sequencing platform, as shown in Table 1. The second round of amplification introduced Illumina bridge PCR compatible primers. The two rounds of PCR reaction conditions are shown in Tables 2 and 3.

After the second round of PCR amplification, the products were recovered by 2% agarose gel electrophoresis and the recovered products were quantified by PCR. Samples were sequenced at high throughput and Operational Taxonomic Units (OTUs) were clustered on the sequences. Bioinformatic statistical analysis was performed at an OTUs similarity level of 97%. Representative sequences of OTUs were species annotated by the Mothur software, and the confidence threshold was set to 0.6. The validity of the sequencing results was analyzed by dilution curves with coverage. The number of species and diversity of species in microbial communities were analyzed by Chao1, ACE, Shannon and Simpson indices.

The COD influent concentration, effluent concentration and removal rate for different operating cycles of the CASS system are given in Figure 3(a). The average COD removal rates for the four stages were 78.53, 87.69, 88.83 and 88.70%, respectively. The COD removal effect was better with the extension of the cycle period. It is obvious from the figure that the removal effect is also more stable when the cycle time is longer. The COD removal rate gradually increased from 70% and finally stabilized at about 90% during the increase of cycle time from 6 to 12 h. With the HRT of 6 h, the too short cycle time failed to provide sufficient time for microorganisms to grow and metabolize. Therefore, the treatment effect was poor, and the effluent concentration fluctuated greatly. As the cycle time was extended to 8 and 12 h, the effluent COD concentration gradually decreased to about 30 mg L⁻¹ and stabilized. When the carbon source was added to the anoxic section in the fourth stage, the effluent COD concentration did not increase and the COD removal rate was stable at 90%. It means that the carbon source added in the anoxic section was all decomposed by denitrifying bacteria and used in the denitrification reaction to remove nitrate from water. The COD removal loading rates of stages T1–T4 were 1.061, 0.829, 0.580 and 0.874 g L⁻¹ d⁻¹, respectively. The COD removal loading rate of activated sludge showed a decreasing trend with increasing cycle time. Combined with Table 4 and Figure 3(a), the COD removal rates for T3 and T4 show a minimal difference, indicating a slight increase compared to T2. This suggests that increasing HRT and introducing an anoxic phase with additional carbon sources can enhance COD removal rates and reduce the concentration of pollutants in the water. The TP influent concentration, effluent concentration and removal rate for different operation cycles of the CASS system are shown in Figure 3(b). The average TP removal rates in stages T1–T4 were 97.53, 98.38, 97.53 and 98.21%, respectively. It can be seen from the figure that the TP removal effect was very stable in this experiment, and the TP effluent concentration was lower than 0.3 mg L⁻¹ in all four conditions. The TP effluent concentration increased slightly during T3, probably because the anoxic period was longer and the re-release of phosphorus from the anoxic section was about to occur. Brown et al. (2011) came to a similar conclusion that TP removal decreased after anaerobic HRTs of more than 2 h. During T4, a carbon source was artificially added in order to reduce the effluent concentration of TN. However, at this time, there was no competition between denitrification and phosphorus removal bacteria resulting in a decrease in TP removal. Begum & Batista (2013) studied that carbon source dosing may cause polyphosphate accumulating organism (PAO) to utilize excess carbon source in the aerobic zone instead of their polyhydroxyalkanoic acid (PHA) reserves, which leads to a reduction in phosphorus removal. This indicates that adding this concentration of carbon source did not negatively affect TP removal.

The influent concentrations, effluent concentrations and removal rates of and TN at different operating cycles of the CASS system are given in Figure 3(c) and 3(d). The average removal rates for the four stages were 98.72, 98.60, 99.20 and 98.53%, respectively. The operation cycle has a low effect on the effluent concentration, and each operation mode has a good treatment effect on ⁠. Even for the 6 h operation cycle of the T1 stage, its aerobic period of 1 h 50 min degraded almost all the 20 mg L⁻¹ ammonia nitrogen.

The average TN removal rates in stages T1–T4 were 56.68, 72.99, 65.64 and 82.51%, respectively. It can be seen that the operation cycle has a great influence on the TN, and there are significant differences in the TN effluent concentration under different cycles. The effluent TN was about 20 mg L⁻¹ at a cycle period of 6 h, indicating that the cycle period of 6 h was not enough to treat all the nitrogen in the water. From the removal effect, it is clear that the aerobic section CASS system has converted almost all in the effluent to nitrate nitrogen. However, the anoxic stage was not long enough for the denitrification reaction time to treat the nitrate nitrogen. The TN effluent concentration was reduced for both the HRT of 8 and 12 h. At this time, the denitrification time in the anoxic stage was sufficient, and the controlling factor affecting the effect of TN treatment in the CASS reactor changed from time to carbon source. Generally speaking, most denitrifying bacteria are heterotrophic and therefore need organic carbon source for cell growth and nitrate reduction. Therefore, the carbon source is added in the anoxic section of the fourth stage, which makes the effluent TN concentration even lower and the effluent concentration can reach about 5 mg L⁻¹. The anoxic period in T3 is longer than the anoxic period in T2, however, the TN concentration of the effluent from the 12 h cycle increases in both T2 and T3 stages without the carbon source. It may be due to the lower organic loading rate of the whole system when the hydraulic retention time is longer. The endogenous respiration of microorganisms intensifies, which affects microbial activity. This is similar to the findings of Kundu et al. (2013) that microorganisms at higher organic loading rate (OLR) and shorter HRT can show better performance. This eventually leads to the reduction of TN removal rate. As can be seen from Table 4, the TN removal loading rates of T1–T4 stages were 0.099, 0.085, 0.051 and 0.110 g L⁻¹ d⁻¹, respectively. Without the addition of carbon source, the TN removal compliance rate decreases with the increase of cycle time and the difference is large. It shows that too high TN loading rate will exceed the tolerance of microorganisms and lead to high TN effluent concentration. And too low TN loading rate is also not conducive to the treatment of TN.

Glucose and sodium acetate, which both meet the effluent quality standards when used as carbon sources, are more effective and have higher TN removal rates compared to sodium acetate. Sodium acetate, glucose and methanol are ranked in descending order of effectiveness without considering economic costs. However, in actual use, economic feasibility needs to be considered. The organic carbon source by a market price the price from high to low is: sodium acetate, methanol and glucose. Therefore, the combination of glucose and sodium acetate is chosen as the carbon source to meet the emission requirements and reduce the cost.

According to Figure 4, no matter what type of carbon source was chosen, there was no significant effect on the removal rate of and TP, which were always maintained at a high level. The removal process of and TP were completed before the anoxic section, so the carbon source added in the anoxic section had little effect on them.

In order to investigate the effect of different cycle times on the succession pattern of microbial community in the CASS reactor, sludge after 7 days of operation with 6 h cycle time (T1), sludge after 7 days of operation with 8 h cycle time (T2), sludge after 7 days of operation with 12 h cycle time (T3) and sludge after 7 days of operation with 8 h cycle time and carbon source injection in the anoxic section (T4) were taken as samples in this experiment. The samples were extracted for high-throughput sequencing analysis and microbial DNA extraction. The sequencing information and diversity indices of the four samples at a similarity level of 97% are shown in Table 5.

The distribution of microbial communities at the phylum level is shown in Figure 6(b). In addition to unclassified species, Gammaproteobacteria, Sphingobacteriia, Betaproteobacteria, Alphaproteobacteria and Deltaproteobacteria were the dominant populations in four periods. Liu et al. (2021b) showed that Gammaproteobacteria and Betaproteobacteria, as important denitrifying bacteria, could improve the NO_x-N anoxic removal rate and enhance the denitrification of the system (2021). Weissbrodt et al. (2014) showed that Sphingobacteriia plays an important role in promoting the accumulation of glycogen and is a necessary bacterium in its process (2014). Planctomycetia was abundant in the T1 stage and gradually decreased with the increase of HRT, which was consistent with the findings of Su et al. (2019).

The distribution of the microbial community at the genus level is shown in Figure 6(c). Saccharibacteria_genera_ncertae_sedis, Buttiauxella, Terrimonas, Ignavibacter-ium, etc., clearly grew as dominant genera at the T2–T4 stages. The Saccharibacter-ia_gene-ra_incertae_sedis is part of the phylum Candidatus Saccharibacteria and is widely distributed in the environment. The dominant functions of other major genera are not known, but their enrichment may facilitate the good functioning of the CASS system. The microbial community was characterized by an active response to C, N and P removal by the CASS system. Optimal cycling cycle conditions benefited from the enrichment of denitrifying bacterial populations, PAOs and GAOs in a stable CASS system, improving the simultaneous C, N and P removal rate.

In terms of metabolism, genes related to energy production and conversion, amino acid transport and metabolism, nucleotide transport and metabolism, carbohydrate transport and metabolism, lipid transport and metabolism and secondary metabolite biosynthesis, transport and chaperones showed similar phenomena in the four periods, with the greatest functional abundance in T1, followed by T3 and the least in T2.

The maximum abundance value appeared in the T1 period, but the treatment effect did not reach the standard at this time, which may be related to the reactor just starting to start. When the reactor is just started and the HRT is short, the CASS pool has a low amount of microorganisms but the environment maintains a nutrient overload phase, so the microorganisms in the pool have the fastest metabolism rate. At this time, although the metabolic rate is the fastest but still can not meet the treatment requirements. The abundance values of the remaining stages were highly correlated with the results of contaminant metabolism. In the three stages of T2–T4, the highest abundance value is T3 stage, and the difference between T4 stage and T3 stage is small. This indicates that the HRT of 8 h and the anoxic section with the carbon source are suitable for the treatment of the CASS process.

Genes involved in translation, translation, ribosomal structure and biogenesis, transcription, replication, recombination and repair, cell wall/membrane/envelope biogenesis, cell motility, signal transduction mechanisms, intracellular trafficking, secretion and vesicular transport did not show a clear trend across cycle time conditions.

The results indicated that the expression of functional genes was related to various factors, and the gene abundance values were higher when the treatment effect was effective.

As a variant of the SBR process, the CASS was a low-cost and efficient technology of township domestic wastewater treatment. Different cycle periods were established to improve the removal of the main pollutants from the wastewater in the CASS system. The optimum cycle time was obtained as 8 h. The highest removal rates of COD, TN, and TP were 87.69, 72.99, 98.60 and 98.38%, respectively. Increasing the HRT leads to an increase in COD removal rate. For TP and ⁠, changing the HRT has almost no impact on their treatment effectiveness, as the removal rate of TP and remains stable. Altering the HRT results in noticeable variations in the effluent TN concentration. The TN removal rate could be increased to 82.51% after the addition of carbon source. The dominant phyla in activated sludge were Proteobacteria, Bacteroidetes and Candidatus Saccharibacteria which contribute to good performance in the CASS system.

This work was financially supported by the Science and Technology Department of Henan Province (161100310700) and the Key Research and Extension Project of Henan Province (222102320291).

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

The authors declare there is no conflict.