Batch Reactor Process Research Articles

Comparative analysis and application of soft sensor models in domestic wastewater treatment for advancing sustainability

ABSTRACT This study focuses on the development and evaluation of soft sensor models for predicting NH3-N values in a wastewater treatment process. The study compares the performance of linear regression (LR), neural networks (NN) and random forest regression (RFR) models. The proposed methodology involves optimizing the sequencing batch reactor process using artificial intelligence and an automatic control system. Real-time NH3-N values are obtained by inputting data from electronic conductivity and temperature sensors into the prediction models. Once the predicted NH3-N value falls below the effluent standard, the cycle ends, improving energy efficiency and sustainability by cutting down the agitator and aerator. The research results demonstrate that the RNN-based NH3-N soft sensor built in this study exhibits the best performance, which is promising for wastewater treatment process optimization and evaluation. The results show that sensor model NNR[0.5Y]H exhibits exceptional performance, utilizing recurrent neural network with 5-step input delays. Sensor NNR[0.5Y]H exhibits an R2 of 0.921, an RMSE of 6.110, and an MAE of 4.558. Based on the findings, recurrent neural network (RNN) variants emerge as the most effective modeling technique due to their ability to capture temporal dependencies and handle variable-length sequences. This study provides satisfied performance results for the NNR[0.5Y]H soft sensor model in NH3-N monitoring and process optimization in wastewater treatment, highlighting the effectiveness of recurrent neural networks and their contribution to improving interpretability, accuracy, and adaptability of soft sensor models.

XRL-FlexSBR: Multi-agent reinforcement learning-driven flexible SBR control with explainable performance guarantee under diverse influent conditions

The sequencing batch reactor (SBR) process stands out for its small footprint and operational flexibility. However, the SBR process is highly nonlinear and subject to influent disturbances. In this study, we suggested an explainable multi-agent reinforcement learning (XRL) approach coupled with multi-agent reinforcement learning (MARL) and explainable AI (XAI); then, an XRL-driven flexible SBR control (XRL-FlexSBR) system was developed to conduct multivariate control the SBR process autonomously. Influent big datasets including biochemical oxygen demand (BOD) and total nitrogen (TN) were collected from the wastewater treatment plants (WWTPs) of South Korea. Then, the Gaussian mixture model was utilized to cluster the diverse influent conditions and the SBR mechanistic model was developed. A game abstraction method based on a two-stage attention network (G2ANET), one of MARL algorithms, was employed to manipulate dissolved oxygen (DO) and extra carbon injection (EC) controllers in the SBR process; furthermore, layer-wise relevance propagation (LRP) of explainable AI (XAI) technique was utilized to evaluate a control performance guarantee by G2ANET. The results verified that XRL-FlexSBR can control the DO and EC controllers in the SBR process while reducing the energy consumption by 4.93 % on average and maintaining effluent quality criteria across the diverse influent conditions. Furthermore, XAI explained that the improved control performance of XRL-FlexSBR agents is attributed to their understanding of the mechanism underlying SBR operations without human intervention. Hence the proposed XRL-FlexSBR can flexibly control the SBR to improve sustainability and profitability under varying influent conditions.

Effects of rice husk biochar attachment biofilm with microorganisms on nitrogen removal of digested swine wastewater

Nitrogen in digested swine wastewater is currently difficult to directly degrade by an activated sludge process in a sequencing batch reactor (SBR), with resulting failure of the effluent to meet emission standards. In this study, rice husk biochar was optionally added into SBR to enhance biochemical properties for digested swine wastewater, especially for nitrogen degradation. The relative nitrogen removal mechanism for microbial community was probed by means of high-throughput sequencing. The results indicated that chemical oxygen demand (COD), ammonia (NH4+-N), and total nitrogen (TN) removal efficiency of digested swine wastewater was separately at 85.3%, 81.3%, and 65.2% using rice husk biochar with biofilm, which was 3.5%, 24.4%, and 14.7% higher than that of activated sludge, under influent of 2609 mg·L-1 COD, 337.0 mg·L-1 NH4+-N, 344 mg/L TN, and 7.77 C/N. High-throughput sequencing revealed that rice husk biochar with biofilm contained Proteobacteria, Thauera, Comamonas, Acinetobacter, Pseudomonas, Flavobacterium, and Corynebacterium to enhance nitrogen removal of digested swine wastewater. The results not only provide theoretical support for biochar with biofilm to improve digested piggery wastewater treatment, but also have great significance in resource utilization of agricultural waste and eco-environmental protection.

Safety Design Criteria for the Emergency Discharge of Hazardous Substances in Small and Medium-Sized Polystyrene Polymerization Batch Reactor Processes: Case Study of the South Korean Chemical Industry

In small and medium-sized chemical plants, explosions constantly occur owing to runaway reactions because of equipment defects or human errors and so on. Accordingly, in this study, based on a case study of an explosion accident in a polystyrene reactor in South Korea, the dis-charge capacity of hazardous substances during a runaway reaction is reviewed and a method for safely disposing of hazardous substances is proposed. Using an acceleration rate calorimeter, the maximum temperature rise rate during the polystyrene reaction was determined, and it was determined that 355,643 kg/h can flow during a runaway reaction. A 30-inch header size was then selected to consider maximum flow rate, and two 81.4 m2 heat exchangers were selected to completely condense the hazardous substances. As a result, the facilities at the workplace were configured to condense all hazardous substances and discharge them into the atmosphere. If this method is used, it is believed that the lives of workers can be protected by preventing fires and explosions in small and medium-sized chemical plants in which runaway reactions may occur.

Continuous-flow synthesis of di-(2-ethylhexyl) peroxydicarbonate in a packed-bed microreactor: Process optimization and kinetic modeling

Di-(2-ethylhexyl) peroxydicarbonate (EHP) is a low-temperature liquid organic peroxide commonly used as an initiator for polymerization of vinyl chloride and ethylene. The exothermic nature of peroxidation and the instability of this peroxide product pose safety challenges during synthesis. Therefore, batch reaction processes for synthesizing such products often prioritize safety over efficiency. In this work, an efficient and safe protocol was proposed for EHP production with the use of a packed-bed microreactor. Response surface methodology was applied to optimize critical process parameters, resulting in a remarkable yield of 95.48% in a residence time of 23.8 min. It proves that the efficiency was significantly improved by the packed-bed microreactor compared with batch reactors. Additionally, an operational window was established to guide the process development for synthesizing EHP in flow. Finally, a kinetic model was established, which was of crucial theoretical significance and practical value for better understanding peroxidation processes and parameter optimization.

N2O Emission Factors from Wastewater Treatment Plants Based on Literature Statistics and Model Fitting

The emission of nitrous oxide （N2O） during wastewater treatment cannot be ignored. The analysis of statistical data from literature based on 126 empirical studies revealed that the geographical factors of wastewater treatment plants （WWTPs） had a significant impact on N2O emission factors. However, the N2O emission factors of WWTPs in all regions of the world were generally lower than the Intergovernmental Panel on Climate Change （IPCC） recommended values. In China, the N2O emission factors （in N2O-N/Ninfluent） of WWTPs were approximately 0.000 35-0.065 20 kg·kg-1. Meanwhile, the N2O emission factors of different wastewater treatment processes were also significantly different, especially since the sequencing batch reactor （SBR） process had higher emissions. The use of uniform default emission factors for accounting was prone to overestimate N2O emissions, and it is recommended that countries conduct actual monitoring or modeling studies to develop categorical emission factors suitable for local conditions. In addition, the N2O emission factor based on total nitrogen （TN） removal was weakly negatively correlated with TN removal in 126 empirical data, which was more in line with bioprocessing stoichiometry and could provide an accurate accounting method for N2O. To this end, a digital twin model was developed to dynamically simulate a case anaerobic-anoxic-aerobic （AAO） WWTP to comprehensively quantify the dynamic emission behavior of N2O, which demonstrated that N2O emissions had significant seasonal and daily variability and were only equivalent to 11% of the calculated value of the emission factor based on the IPCC recommendation. Comparing the scatter linear fitting and categorical mean exponential fitting methods, it was found that the latter could more accurately reflect the negative correlation between the N2O emission factors and the TN removal rate, and an exponential regression equation between the average N2O emission factor based on the amount of TN removed and the TN removal rate was further developed to predict the N2O emission. The dynamic simulation and categorical index fitting methods provided in this study are important references for the accurate accounting of N2O emissions in similar WWTPs and provide help for understanding and responding to the N2O emission problems.

A stochastic approach for the solution of single and multi–objective optimisation problems of biological processes in sequencing batch reactor

This paper investigates the impact of implementing single and multi-optimisation solutions on the biological treatment process in a sequencing batch reactor (SBR). The research is based on a case study of the water resource recovery facility (WRRF) in Swarzewo, Northern Poland. The paper introduces the adaptive extremum seeking control (ESC) method for dissolved oxygen (DO) concentration control and places it in a layered control structure. Further, it presents the introduction of an optimisation layer for the structure and parameters of the SBR cycle, through the synthesis of stochastic methods: single-objective optimisation (SOO) using a genetic algorithm (GA) and multi-objective optimisation (MOO) using the NSGA-II algorithm. The results were compared to a classical approach with fixed cycle parameters. The paper shows the advantages of optimising cycle parameters, including the number of phases as well as the DO value, on the process flow. These control structures underwent simulation tests in the MATLAB environment with the Simba package. The biochemical processes occurring in the reactor are based on the Activated Sludge Model No. 2d (ASM2d). The optimising control system demonstrates tangible improvements in operational efficiency and significant reductions in electrical energy consumption, highlighting the effectiveness of the proposed methodologies. © 2017 Elsevier Inc. All rights reserved.

Facile Synthesis of WS2/WO3 Materials in a Batch Reactor for the Hydrogen Evolution Reaction

In this study, a new and facile process was developed for the preparation of composite catalysts based on tungsten oxide (WO3) by batch reactor routes. The structures, morphologies, compositions, and characteristics of synthesized materials were investigated and confirmed. Using batch reactor processes, WO3 nanorods (WO3 NR), heterostructures of WS2/WO3 nanobricks (WS2/WO3 NB), and WS2/WO3 nanorods (WS2/WO3 NR) were successfully prepared. The prepared materials were then employed for hydrogen evolution reaction (HER) to investigate their catalytic performance. The results indicated that the electrocatalytic activities of WS2/WO3 NR are significantly improved compared to those of WO3 NR and WS2/WO3 NB. This improvement could be attributed to the formation of heterostructure between WS2 and WO3 elements in highly uniform materials, which could create the synergistic effect and further improve the catalytic activities of the catalyst. The data shows that the Tafel slope of WS2/WO3 NR (82.7 mV dec−1) is significantly lower than that of WO3 NR (112.5 mV dec−1) and WS2/WO3 NB (195.5 mV dec−1). Furthermore, the resistance of WS2/WO3 NR (397.7 Ω) is markedly decreased compared to those of WO3 NR (1816 Ω) and WS2/WO3 NB (3597 Ω). The results indicate that WS2/WO3 NR could be a great catalyst for electrochemical applications.

Математическое моделирование пиролиза резиновых отходов в горизонтальном цилиндрическом реакторе

Recycling of cushioned rubber products is an important environmental and technical-economic issue. Among the various methods of processing such waste, one of the most effective is the pyrolysis process, since it allows us to obtain fuel and energy, and provides the possibility of secondary use of carbon black and metal. Mathematical modeling of this process is necessary to solve problems of optimization and automated control. Thus, the purpose of this study is to simulate the pyrolysis process in a horizontal cylindrical batch reactor, which is currently becoming increasingly widespread. To mathematically describe the process, a model with distributed parameters is used in the form of a two-dimensional thermal conductivity equation and a system of equations of chemical kinetics of polymer thermal destruction reactions. The problem is solved numerically using the finite element method. As a result of the numerical solution of the equations of the mathematical model, non-stationary distributions of temperature and degree of conversion over the cross section of the reactor with non-uniform filling have been obtained. The authors have studied the kinetics of the reaction of polymer thermal destruction in reactors of different diameters. The results obtained can be used to predict the kinetics of material destruction under given reactor heating conditions, which can be useful when we design reactors and automate pyrolysis process control.

Phosphate recovery from urban sewage by the biofilm sequencing batch reactor process: Key factors in biofilm formation and related mechanisms

The biofilm sequencing batch reactor (BSBR) technique has been deployed in the laboratory to enrich phosphorus from simulated wastewater, but it is still not clear what its performance will be when real world sewage is used. In this work, the effluent from the multi-stage anoxic-oxic (AO) activated sludge process at a sewage plant was used as the feed water for a BSBR pilot system, which had three reactors operating at different levels of dissolved oxygen (DO). The phosphorus adsorption and release, the biofilm growth, and the extracellular polymeric substances (EPS) components and contents were examined. The microbial communities and the signaling molecules N-acyl-l-homoserine lactones (AHLs) were also analyzed. Gratifyingly, the BSBR process successfully processed the treated sewage, and the biofilm developed phosphorus accumulation capability within 40 days. After entering stable operation, the system concentrated phosphate from 2.59 ± 0.77 mg/L in the influent to as much as 81.64 mg/L in the recovery liquid. Sludge discharge had profound impacts on all aspects of BSBR, and it was carried out successfully when the phosphorus absorption capacity of the biofilm alone was comparable to that of the reactor containing the activated sludge. Shortly after the sludge discharge, the phosphate concentration of the recovery liquid surged from 50 to 140 mg/L, the biofilm thickness grew from 20.56 to 67.32 μm, and the diversity of the microbial population plunged. Sludge discharge stimulated Candidatus competibacter to produce a large amount of AHLs, which was key in culturing the biofilm. Among the AHLs, both C10-HSL and 3OC12-HSL were significantly positively correlated with EPS and the abundance of Candidatus competibacter. The current results demonstrated BSBR as a viable option to enrich phosphorus from real world sewage with low phosphorus content and fluctuating chemistry. The mechanistic explorations also provided theoretical guidance for cultivating phosphorus-accumulating biofilms.

Cultivation of phosphate-accumulating biofilm: Study of the effects of acyl-homoserine lactones (AHLs) and cyclic dimeric guanosine monophosphate (c-di-GMP) on the formation of biofilm and the enhancement of phosphate metabolism capacity

This study investigated the mechanisms of microbial growth and metabolism during biofilm cultivation in the biofilm sequencing batch reactor (BSBR) process for phosphate (P) enrichment. The results showed that the sludge discharge was key to biofilm growth, as it terminated the competition for carbon (C) source between the nascent biofilm and the activated sludge. For the tested reactor, after the sludge discharge on 18 d, P metabolism and C source utilization improved significantly, and the biofilm grew rapidly. The P concentration of the recovery liquid reached up to 157.08 mg/L, which was sufficient for further P recovery via mineralization. Meta-omics methods were used to analyze metabolic pathways and functional genes in microbial growth during biofilm cultivation. It appeared that the sludge discharge activated the key genes of P metabolism and inhibited the key genes of C metabolism, which strengthened the polyphosphate-accumulating metabolism (PAM) as a result. The sludge discharge not only changed the types of polyphosphate-accumulating organisms (PAOs) but also promoted the growth of dominant PAOs. Before the sludge discharge, the necessary metabolic abilities that were spread among different microorganisms gradually concentrated into a small number of PAOs, and after the sludge discharge, they further concentrated into Candidatus_Contendobacter (P3) and Candidatus_Accumulibacter (P17). The messenger molecule C-di-GMP, produced mostly by P3 and P17, facilitated P enrichment by regulating cellular P and C metabolism. The glycogen-accumulating organism (GAO) Candidatus_Competibacter secreted N-Acyl homoserine lactones (AHLs), which stimulated the secretion of protein in extracellular polymeric substances (EPS), thus promoting the adhesion of microorganisms to biofilm and improving P metabolism via EPS-based P adsorption. Under the combined action of the dominant GAOs and PAOs, AHLs and C-di-GMP mediated QS to promote biofilm development and P enrichment. The research provides theoretical support for the cultivation of biofilm and its wider application.

Kinetic verification and Comsol modeling of the Diels-Alder reaction of conjugated pentadiene with maleic anhydride in a continuous flow capillary reactor

Synthesis of 3/4-methyltetrahydrophthalic anhydride was carried out by the Diels-Alder reaction in a continuous flow capillary reactor. The efficient liquid–liquid reaction of pentadiene with molten maleic anhydride provided a theoretical basis for replacing the conventional batch reaction process. Different inner diameter sizes of the channel tubes were adjusted in the range of 0.50 ∼ 2.00 mm to find the optimal size to match the strong exothermic reaction. Under the capillary channel size of 0.8 mm, the conversion rate of C5 and MA reached 100 % when nC5: nMA = 1.08:1 at 65 °C for 8 min. The D-A reaction process is accompanied by the autopolymerization of diolefin in the batch reactor. Our results showed that choosing a continuous flow capillary reactor of appropriate size can directly improve the selectivity of the reaction and the quality of the product. The accurate reaction rate constant and activation energy were obtained by establishing a kinetic model, and the effects of temperature, reaction time and pipe diameter were designed using Comsol software.

Assessment of nitrification process in a sequencing batch reactor: Modelling and genomic approach

Nitrification of ammoniacal nitrogen (N–NH4+) to nitrate (N–NO3-) was investigated in a lab-scale sequencing batch reactor (SBR) to evaluate its efficiency. During the nitrification process the removal of N–NH4+ reached 96%, resulting in 73% formation of N–NO3-. A lineal correlation (r2 = 0.9978) was obtained between the concentration of volatile suspended solids (VSS) and the maximal N–NO3- concentration at the end of each batch cycle under stationary state. The bacterial taxons in the initial inoculum were identified, revealing a complex diverse community mainly in the two major bacterial phyla Proteobacteria and Actinobacteria. The FAPROTAX algorithm predicted the presence in the inoculum of taxa involved in relevant processes of the nitrogen metabolism, highlighting the bacterial genera Nitrospira and Nitrosomonas that are both involved in the nitrification process. A kinetic model was formulated for predicting and validating the transformation of N–NH4+, N–NO2- and N–NO3- and the removal of organic and inorganic carbon (TOC and IC, respectively). The results showed how the increase in biomass concentration slowed down the transformation to oxidised forms of nitrogen and increased denitrification in the settling and filling stages under free aeration conditions.

Total phosphorus and total Kjeldahl nitrogen removal using an aerobic granular sludge process. Case studies ANN and RSM modeling

Removing nutrients from wastewater is essential because high concentrations in aquatic systems lead to severe eutrophication problems, the most common impairment of surface waters such as lakes and oceans. Total phosphorus (TP) and total Kjeldahl nitrogen (TKN) were removed from mixed wastewater using an aerobic granular sludge process in a sequencing batch reactor (AGS-SBR). An artificial neural network (ANN) and response surface methodology (RSM) were applied to evaluate the main parameters of the process. For TKN removal, only cycle time (CT) (0.0475) was a significant variable, achieving removal efficiencies of up to 81%. In TP case removal, two parameters, VER and AR, were substantial for this process, completing elimination efficiencies of around 40%. On comparing the models with statistical indices, ANN coupled with the moth-flame optimization algorithm (ANN-MFO) demonstrated higher performance with an adjusted R2 (0.9866) for the case of TP removal and (0.9519) for TKN removal.

Optimization of the Product Yields of the Pyrolysis of Palm Kernel Shell in a Fixed-Bed Reactor Using Response Surface Methodology (RSM)

Pyrolysis is a method used for the thermochemical conversion of biomass and agro wastes into three major by-products namely, biochar, bio-oil, and biogas in the absence of oxygen. Global waste generation is increasing at an alarming rate. Palm kernel shell (PKS) is among the palm wastes accumulating in many palm oil mills around the globe with the attendant problems in waste management. The utilization of coal for energy generation is more expensive and not environmentally friendly. Bio-oil refineries and industries require the utilization of minimum resources (input) to achieve optimal response (output) in the production process. However, more than 30% of the energy content derivation from the pyrolysis process is wasted due to nonoptimization of the process parameters. This study investigated the optimization of the product yields of the pyrolysis of PKS in a fixed-bed batch reactor using response surface methodology (RSM). Masses of 1 kg, 2 kg, and 3 kg were pyrolyzed in batches at process temperature variations of 200 OC, 300 OC, 400 OC, and 500 OC. Design Expert 12 software (Version 12.0.3.0 Stat-Ease Inc. MN, USA) and Analysis of Variance (ANOVA) were used for the statistical analysis. Lack-of-fit, adjusted, and predicted multiple correlation coefficients and coefficient of variation of the different polynomial models were compared to select the best-fitting polynomial model. The optimal feedstock parameters were 2.66 kg of PKS and 410.0 OC process temperature. The predicted results were 0.986 kg of biochar, 1.205 kg of bio-oil, 0.481 kg of biogas, 1116.5 cm3 of bio-oil, and 140.6 minutes. The experimental results were 0.894 kg of biochar, 1.316 kg of bio-oil, 0.498 kg of biogas, 1208.9 cm3 of bio-oil, and at 162.8 minutes through validation. The validated quadratic model was suitable for the optimization and RSM is a numerical, statistical, and mathematical tool for modeling and optimization of the pyrolysis process in a fixed-bed batch reactor.

Neural Network-Based Hammerstein Model Identification of a Lab-Scale Batch Reactor.

This paper focuses on two types of neural network-based Hammerstein model identification methods for the acrylamide polymerization reaction of a batch reactor process. The first neural-based identification type formulates the weights of the multilayer network directly as parameters of the nonlinear static and linear dynamic blocks of the Hammerstein model and trains the weights using a gradient-based backpropagation algorithm. In the second identification type, the nonlinear static block of the Hammerstein model is framed as a single hidden-layer feedforward network and both nonlinear and linear block parameters are trained using an extreme learning machine, where the training procedure is exempted from gradient calculation. The primary focus of the paper is neural-based model identification of a complex nonlinear system, which facilitates ease of linear/nonlinear controller design with good learning speed and less computations. A future work toward the machine learning-based nonlinear model predictive controller implementation using the Jetson Orin Nano board is also described.

Characterization of simultaneous ammonium and nitrate removal and microbial communities in airlift reactor using 3-hydroxybutyrate-co-3-hydroxyvalerate (PHBV) as carbon source and biofilm carrier

As a novel trend, solid carbon sources are applied to act as electron donors and biofilm carrier in biological denitrification process. In this study, simultaneous nitrate and ammonium removal process in an airlift sequencing batch reactor using 3-hydroxybutyrate-co-3-hydroxyvalerate (PHBV) as carbon source and biofilm carrier under intermittent aeration conditions was established to treat effluent of synthetic marine recirculating aquaculture system. The results showed that maximum nitrate and ammonia nitrogen removal rates of 0.45 and 0.09 kg m−3 d−1 were achieved. No significant nitrite accumulation was found during 200-day operation, while effluent dissolved organic carbon accumulation and particle size reduction significantly increased. Microbial community analysis and batch tests illuminate that the generated sludge and attached biofilm played important roles in nitrogen removal. This study demonstrates the potential mechanism for the nitrogen removal process mediated by 3-hydroxybutyrate-co-3-hydroxyvalerate and provide a new idea for the alternative solutions of solid carbon sources.

Effect of Salinity on Performance and Microbial Community during Granulation Process in a Sequencing Batch Reactor

This study focused on the secretion of extracellular polymeric substances (EPSs), reactor nutrient removal performance and the microbial community under varying concentrations of NaCl (0, 10, 20, 30 and 40 g/L) during a granulation process in a sequencing batch reactor (SBR). The microorganisms tended to secrete higher levels of protein (PN) and polysaccharide (PS) as a protective mechanism under saline conditions, with tightly bound EPS (TB-EPS) playing a crucial role in stabilizing granules. An overall high removal rate of chemical oxygen demand (COD) throughout operation was observed. However, the removal rate of total nitrogen (TN) progressively decreased with the stepwise increase in salinity from 85.59% at 10 g/L to 64.18% at 40 g/L. The low total phosphorus (TP) removal efficiency during the operation process is due to the loss of sludge biomass and inhibition of phosphorus-accumulating bacteria activity. Moreover, salinity caused the changes in microbial community structure. Paracoccus, Thauera and unclassified_f_Rhodobacteraceae were dominant genera at 10 g, 20 g/L and 30 g/L salinity, respectively, while Azoarcus, Halomonas, unclassified_f_Flavobacteriaceaeand Vibrio replaced them at 40 g/L salinity.

Occurrence, removal, and risk assessment of emerging contaminants in aquatic products processing sewage treatment plants.

Emerging contaminants (ECs) in aquatic environments have attracted attention due to their wide distribution and potential ecotoxicities. Sewage treatment plants (STPs) are proven to be the major source of ECs in the aquatic environment, while there remains insufficient understanding of the removal and risk assessment of ECs in STPs. Here, we clarified the degradation and risk impact of 13 ECs in two aquatic product processing sewage treatment plants (APPSTPs) along the southeast coast of China. The concentrations of ECs followed the order: endocrine-disrupting chemicals (1877.85-15,398.02ng/L in influent, 3.37-44.47ng/L in effluent) > > sulfonamide antibiotics (SAs, 75.14-906.19ng/L in influent, 1.14-15.33ng/L in effluent) > pharmaceutical and personal care products (PPCPs, 44.47-589.93ng/L in influent, 2.54-34.16ng/L in effluent) ≈ fluoroquinolone antibiotic (54.76-434.83ng/L in influent, 10.75-32.82ng/L in effluent) > other antibiotics (16.21-51.96ng/L in influent, 0.68-6.17ng/L in effluent). Moreover, the concentrations of PPCPs (decreased by 55.33-87.65% in peak fishing season) and antibiotics (increased by 44.99% in peak fishing season) were affected by fishing activities. In particular, the sequencing batch reactor (SBR) process had a better removal effect than the anaerobic-anoxic-oxic (A2/O) process on the treatment of some contaminants (e.g., norfloxacin and nonylphenol). Risk evaluations of ECs demonstrated that nonylphenol and SAs were at high- and low-risk states, respectively. Overall, our results provide important information for the degradation treatment of ECs, which is essential for pollutant management policy formulation.

Metagenomics, metatranscriptomics, and proteomics reveal the metabolic mechanism of biofilm sequencing batch reactor with higher phosphate enrichment capacity under low phosphorus load

The biofilm sequencing batch reactor (BSBR) process has higher phosphate recovery efficiency and enrichment multiple when the phosphorus load is lower, but the mechanism of phosphate enrichment at low phosphorus load remains unclear. In this study, we operated two BSBR operating under low and high phosphorus load (0.012 and 0.032 kg/(m3·d)) respectively, and used metagenomic, metatranscriptomic, and proteomics methods to analyze the community structure of the phosphorus accumulating organisms (PAOs) in the biofilm, the transcription and protein expression of key functional genes and enzymes, and the metabolism of intracellular polymers. Compared with at high phosphorus load, the BSBR at low phosphorus load have different PAOs and fewer types of PAOs, but in both cases the PAOs must have the PHA, PPX, Pst, and acs genes to become dominant. Some key differences in the metabolism of PAOs from the BSBR with different phosphorus load can be identified as follows. When the phosphorus load is low, the adenosine triphosphoric acid (ATP) and NAD(P)H in the anaerobic stage come from the TCA cycle and the second half of the EMP pathway. The key genes that are upregulated include GAPDH, PGK, ENO, ppdk in the EMP pathway, actP in acetate metabolism, phnB in polyhydroxybutyrate (PHB) synthesis, and aceA, mdh, sdhA, and IDH1 in the TCA cycle. In the meantime, the ccr gene in the PHV pathway is inhibited. As a result, the metabolism of the PAOs features low glycogen with high PHB, Pupt, Prel, and low PHV. That is, more ATP and NAD(P)H flow to phosphorus enrichment metabolism, thus allowing the highly efficient enrichment of phosphorus from low concentration phosphate thanks to the higher abundance of PAOs. The current results provide theoretical support and a new technical option for the enrichment and recovery of low concentrations of phosphate from wastewater by the BSBR process.