Search Results (4)

Submerged membrane bioreactors (SMBRs) are a promising technology for municipal sewage treatment, but membrane fouling has limited their development. In this study, biochar (BC), which has a certain adsorption capacity, was added to an SMBR to investigate its potential in treating municipal sewage and alleviating membrane fouling. The results showed that the average removal rates of ammonia nitrogen (NH₄⁺-N), total nitrogen (TN), total phosphorus (TP) and chemical oxygen demand (COD) were 94.38%, 59.01%, 44.15% and 83.70%, respectively. After BC was added and operation was stable, the ratio of mixed liquor volatile suspended solids to mixed liquor suspended solids (MLVSS/MLSS) was maintained between 0.78 and 0.81. The concentrations of soluble microbial products (SMPs) and extracellular polymeric substances (EPSs) were stabilized between 63.05 ± 8.49 mg/L and 67.12 ± 1.54 mg/L. Trans-membrane pressure (TMP) and scanning electron microscopy (SEM) analyses showed that BC reduced the TMP by reducing the thickness and compactness of the cake layer on the membrane surface. The high-throughput sequencing results showed that the microorganisms associated with biofilm formation (proteobacteria, γ-proteobacteria and α-proteobacteria) were significantly reduced in the BC-enhanced SMBR system. BC promoted the enrichment of functional microorganisms such as Chloroflexi, Acidobacteriota, Anaerolineae and Planctomycetes. Compared with traditional anti-fouling methods, the results of this study may provide a low-cost membrane fouling mitigation method for industrial applications of SMBRs. Full article

Based on the improved high-efficiency sewage treatment performance of submerged membrane bioreactors (SMBRs), we focused on how to adjust the C/N ratio of the influent water during reactor start-up to prevent an excessive C/N ratio from causing membrane fouling. In this study, an experimental method of gradually adjusting the influent C/N ratio to quickly start the reactor was proposed, and the results showed that biofilm formation in R1 (SMBR, three influent C/N ratios of 5, 10, and 20) was approximately completed in 32 days, shorter than that (40 days) required in R2 (SMBR, influent C/N ratio of 20). Higher removal efficiencies of 76.4% for TN, 70.1% for COD, and 79.2% for NH₃-N were obtained in R1 than in R2. The high-throughput sequencing results indicated that after 150 days of operation, the Shannon index of bacteria in R1 increased from 2.97 to 4.41 and the growth of Nakamurella, Ferruginibacter, and Rhodanobacter was promoted in the reactor, which indicated substantial microbial diversity in the biofilm. Therefore, gradually adjusting the influent C/N ratio could effectively enhance the nitrogen removal performance of denitrification microbial communities in SMBRs. This study offers a reliable approach for starting the SMBR-enhanced biological nutrient removal process in wastewater treatment plants by gradually adjusting the influent C/N ratio. Full article

In this study, paper-mill wastewater was treated using the Submerged Membrane Bioreactor (SMBR) process. In particular, the ozone oxidation treatment process is applied after SMBR to remove the fluorescent whitening agent, which is a trace pollutant and non-biodegradable. Fluorescent whitening agent concentration was indirectly measured by UV scanning and COD concentration. The concentration of COD before SMBR and ozone oxidation was 449.3 mg/L, and the concentration of treated water was 100.3 mg/ℓ. The COD removal efficiency of paper-mill wastewater through SMBR and the ozone oxidation process was about 77.68%. The optimized amount of ozone was required for the removal of the fluorescent whitening agent after SMBR was 95 mg·O₃/ℓ calculated by UV scan results. Additionally, the optimized amount of required ozone to remove COD was calculated to 0.126 mg·COD/mg·O₃. Full article

This paper presents a design of a data-driven-based neural network internal model control for a submerged membrane bioreactor (SMBR) with hollow fiber for microfiltration. The experiment design is performed for measurement of physical parameters from an actuator input (permeate pump voltage), which gives the information (outputs) of permeate flux and trans-membrane pressure (TMP). The palm oil mill effluent is used as an influent preparation to depict fouling phenomenon in the membrane filtration process. From the experiment, membrane fouling potential is observed from flux decline pattern, with a rapid increment of TMP (above 200 mbar). Membrane fouling is a complex process and the available models in literature are not designed for control system (filtration performance). Therefore, this work proposes an aeration fouling control strategy to measure the filtration performance. The artificial neural networks (Feed-Forward Neural Network—FFNN, Radial Basis Function Neural Network—RBFNN and Nonlinear Autoregressive Exogenous Neural Network—NARXNN) are used to model dynamic behaviour of flux and TMP. In this case, only flux is used in closed loop control application, whereby the TMP effect is used for monitoring. The simulation results show that reliable prediction of membrane fouling potential is obtained. It can be observed that almost all the artificial neural network (ANN) models have similar shape with the actual data set, with the highest accuracy of more than 90% for both RBFNN and NARXN. The RBFNN is preferable due to simple structure of the network. In the control system, the RBFNN IMC depicts the highest closed loop performance with only 3.75 s (settling time) for setpoint changes when compared with other controllers. In addition, it showed fast performance in disturbance rejection with less overshoot. In conclusion, among the different neural network tested configurations the one based on radial basis function provides the best performance with respect to prediction as well as control performance. Full article