Enhanced Wastewater Treatment with an AnF-AAO System for Improved Internal Carbon Source Utilization.

The main challenge in removing nutrients from municipal wastewater in China is the lack of available carbon sources. While hydrolysis acidification tanks can improve wastewater biodegradability by effectively utilizing internal carbon sources, high sludge concentrations are difficult to control in traditional tank variants. In this study, an innovative anaerobic filter (AnF) hydrolysis acidification reactor composed of a continuously stirred tank reactor (CSTR) and cloth media filter was designed to regulate and maintain high sludge concentrations in the hydrolysis acidifier. The reactor was used as a pretreatment unit for the anaerobic/anoxic/oxic (AAO) units and combined into an AnF-AAO system to explore the effectiveness of internal carbon source utilization in wastewater. The results indicate that as the sludge concentration in the hydrolysis acidifier increased, the hydrolysis and acidification processes became more efficient. The optimal sludge concentration was 40 g/L, which significantly increased the production of soluble chemical oxygen demand and volatile fatty acids. Above this concentration, the efficiency decreased. Compared to traditional AAO processes, the AnF-AAO system achieved superior total nitrogen and phosphorus removal with shorter hydraulic retention times and reduced sludge production by a significant amount of 35%. Due to its capacity for enhancing internal carbon source utilization, the AnF-AAO system constitutes a promising approach for sustainable urban wastewater treatment.

Effectiveness of cloth media filters on mitigating membrane fouling in anaerobic filter membrane bioreactors.

Membrane fouling is a persistent challenge that has impeded the broader application of anaerobic membrane bioreactors (AnMBRs). To mitigate membrane fouling, between the outlet of the UASB anaerobic bioreactor and the PVDF membrane to form the anaerobic filter membrane bioreactor (AnFMBR) system. Through comprehensive experiments, the optimal pore size for cloth filters was determined to be 50 µm. A comprehensive assessment over 140 days of operation shows that the novel AnFMBR had significantly greater resistance to membrane pollution than the traditional AnMBR. The AnFMBR system membrane tank exhibited lower mixed liquor suspended solid and mixed liquor volatile suspended solid concentrations, smaller sludge particle sizes, increased hydrophilicity of sludge flocs, and optimized microbial community distribution compared to those of conventional AnMBRs. The total solids foulant accumulation rate in the AnMBR was 5.1 g/m2/day, while in the AnFMBR, the rate was 2.4 g/m2/day, marking a 53.7 % decrease in fouling rate for the AnFMBR compared with the AnMBR. This decrease indicates that integrating the filtration assembly significantly lowered the rate of solid foulant accumulation on the membrane surface, primarily by controlling the buildup of solid foulants in the cake layer, thereby alleviating membrane fouling. AnFMBR compared to AnMBR, the membrane fouling rate halved, effectively doubled the interval between membrane cleaning from seven days, as observed in the AnMBR system, to fourteen days. These findings underscore the potential of integrating cloth media filters into AnMBRs to improve operational efficiency, economic viability, and sustainability.

Analyzing greenhouse gas emissions and influencing factors of 247 actual wastewater treatment plants in China using emission factor and operational data integrated methods (ODIM).

In response to China's policies on pollution control and carbon emission (CE) reductions, more stringent regulations have been implemented to evaluate CE in wastewater treatment facilities. In this study, we have analyzed CE from China's wastewater treatment plants (WWTPs) and influencing factor. Emission factor (EF) and operational data integrated methods (ODIM) were utilized to measure emissions, using data collected from 247 WWTPs over a 1-year period across seven regions in China. The average CE intensity was 0.45 kgCO2-eq/m3, affected by region, season, influent water quality, treatment processes, effluent discharge standards, and facilities. The scale effect was obvious only in the range of 2 × 105 m3/day. Underground WWTPs exhibited significantly higher CE compared to aboveground WWTPs. In summary, the assessment of CE in 247 actual WWTPs not only identifies emission reduction potential but also provides a scientific basis for formulating targeted emission reduction measures.

Exploratory study on the metabolic similarity of denitrifying carbon sources.

Mixed carbon sources have been developed for denitrification to eliminate the "carbon dependency" problem of single carbon. The metabolic correlation between different carbon sources is significant as guidance for the development of novel mixed carbon sources. In this study, to explore the metabolic similarity of denitrifying carbon sources, we selected alcohols (methanol, ethanol, and glycerol) and saccharide carbon sources (glucose, sucrose, and starch). Batch denitrification experiments revealed that methanol-acclimated sludge improved the denitrification rate of both methanol (14.42 mg-N/gMLVSS*h) and ethanol (9.65 mg-N/gMLVSS*h), whereas ethanol-acclimated sludge improved the denitrification rate of both methanol (7.80 mg-N/gMLVSS*h) and ethanol (22.23 mg-N/gMLVSS*h). In addition, the glucose-acclimated sludge and sucrose-acclimated sludge possibly improved the denitrification rate of glucose and sucrose, and the glycerol-acclimated sludge improved the denitrification rate of volatile fatty acids (VFAs), alcohols, and saccharide carbon sources. Functional gene analysis revealed that methanol, ethanol, and glycerol exhibited active alcohol oxidation and glyoxylate metabolism, and glycerol, glucose, and sucrose exhibited active glycolysis metabolism. This indicated that the similarity in the denitrification metabolism of these carbon sources was based on functional gene similarity, and glycerol-acclimated sludge exhibited the most diverse metabolism, which ensured its good denitrification effect with other carbon sources.

A new approach to optimizing aeration using XGB-Bi-LSTM via the online monitoring of oxygen transfer efficiency and oxygen uptake rate.

In wastewater treatment plants (WWTPs), aeration is vital for microbial oxygen needs. To achieve carbon neutrality, optimizing aeration for energy and emissions reduction is imperative. Machine learning (ML) is used in wastewater treatment to reveal complex rules in large data sets has become a trend. In this vein, the present paper proposes an aeration optimization approach based on the extreme gradient boosting-bidirectional long short-term memory (XGB-Bi-LSTM) model via the online monitoring of oxygen transfer efficiency (OTE) and oxygen uptake rate (OUR), thus allowing WWTPs to conserve energy and reduce indirect carbon emissions. The approach uses gain algorithm of XGB to calculate the importance of features and identify important parameters, and then uses Bi-LSTM to predict the target with important parameters as features. Operational data from a WWTP in Suzhou, China, is employed to train and test the approach, the performance of which is compared with ML models suitable for regression prediction tasks (XGB, random forest, light gradient boosting machine, gradient boosting and LSTM). Experimental results show the approach requires only a small number of input parameters to achieve good performance and outperforms other machine-learning models. When OTE and dissolved oxygen (DO) are used as features to predict the alpha factor (αF; since diffusers were used, multiply by the pollution factor F), the R-squared (R2) is 0.9977, the root mean square error (RMSE) is 0.0043, the mean absolute percentage error (MAPE) is 0.0069 and the median absolute error (MedAE) is 0.0032. When the predicted αF and the OUR are used as features to predict the air flow rate of an aeration unit, the R2 is 0.9901, the RMSE is 3.6150, the MAPE is 0.0209 and the MedAE is 1.5472. Using our optimized aeration approach, the energy consumption can be reduced by 23%.

Optimization on structure and operation parameters of biofilter for decentralized sewage treatment.

Aiming for treating decentralized domestic wastewater in rural China, this study evaluates the effects of ceramsite size and structure, and water recirculation parameters, upon the performance of recirculating biofilter (RBF). RBF shows stable capability of chemical oxygen demand (COD) remediation and ammonia nitrification. In addition, the microbial flora and structures of the various layers in the system are analyzed via high-throughput sequencing in order to study the microbial diversity. The results indicate that while the ceramic particle size has no significant influence on the COD remediation capacity, the ceramics with smaller particle sizes exhibit better ammonia nitrogen (NH4+-N) removal ability, with a first-order linear relationship between the influent ammonia nitrogen load and the effluent NH4+-N concentration in RBF (R2 > 0.64). An increased hydraulic load and intermittent operation are shown to deteriorate the water quality with respect to NH4+-N, while an increased recirculation ratio increases the removal rate of NH4+-N from the effluent. Further, the water distribution time has a stronger effect upon the NH4+-N concentration in the effluent than does the recirculation ratio. Moreover, the microbial structure of the multi-layer recirculating trickle biofilter varies significantly during the process. The results indicate that a high recirculation ratio, long water distribution time, and multi-layer structure will be beneficial for improving the pollutant treatment capacity of RBF.