Modeling of transitional pore blockage to cake filtration and modified fouling index – Dynamical surface phenomena in membrane filtration

Optimization of MBRs through integrated modelling: A state of the art

The optimization of integrated membrane bioreactors (MBRs) models is of paramount importance in view of reducing the costs, greenhouse gas emissions or enhancing the water quality. On this behalf, this paper, produced by the International Water Association (IWA) Task Group on Membrane modelling and control, reviews the current state-of-the-art regarding the control and optimization of integrated MBR models. Whether aerobic or anaerobic, such modelling allows the consideration of specific functioning conditions and optimization problems together with the estimation and monitoring of Performance Index (PIs). This paper reviews the diversity of those problems criteria used in performance assessment. Dividing issues that can be addressed either off-line or online, it is shown that integrated models have attained an important degree of maturity. Several recommendations for mainstreaming the optimization of MBRs using such integrated models. The key findings of this work show that there is room for improving and optimizing the functioning of MBRs using integrated modelling and that this integrated modelling approach is necessary to link functioning conditions together with PI estimation and monitoring.

Removal of pesticides from secondary treated urban wastewater by reverse osmosis

The residues of pesticides that reach water resources from agricultural activities in several ways contaminate drinking water resources and threaten aquatic life. This study aimed to investigate the performance of three reverse osmosis (RO) membranes (BW30-LE, SW30-XLE, and GE-AD) in rejecting four different pesticides (tributyl phosphate, flutriafol, dicofol, and irgarol) from secondary treated urban wastewater and also to elucidate the mechanisms underlying the rejection of these pesticides. RO experiments were conducted using pesticide-spiked wastewater samples under 10 and 20 bar transmembrane pressures (TMP) and membrane performances were evaluated. Overall, all the membranes tested exhibited over 95% rejection performances for all pesticides at both TMPs. The highest rejections for tributyl phosphate (99.0%) and irgarol (98.3%) were obtained with the BW30-LE membrane, while for flutriafol (99.9%) and dicofol (99.1%) with the GE-AD membrane. The increase in TMP from 10 to 20 bar did not significantly affect the rejections of all pesticides. The rejection performances of RO membranes were found to be governed by projection area as well as molecular weight and hydrophobicity/hydrophilicity of pesticides. Among the membranes tested, the SW30-XLE membrane was the most prone to fouling due to the higher roughness.

Deep learning model for simulating influence of natural organic matter in nanofiltration

Controlling membrane fouling in a membrane filtration system is critical to ensure high filtration performance. A forecast of membrane fouling could enable preliminary actions to relieve the development of membrane fouling. Therefore, we established a long short-term memory (LSTM) model to investigate the variations in filtration performance and fouling growth. For data acquisition, we first conducted lab-scale membrane fouling experiments to identify the diverse fouling mechanisms of natural organic matter (NOM) in nanofiltration (NF) systems. Four types of NOMs were considered as model foulants: humic acid, bovine-serum-albumin, sodium alginate, and tannic acid. In addition, real-time 2D images were acquired via optical coherence tomography (OCT) to quantify the cake layer formed on the membrane. Subsequently, experimental data were used to train the LSTM model to predict permeate flux and fouling layer thickness as output variables. The model performance exhibited root mean square errors of <1 L/m²/h for permeate flux and <10 µm for fouling layer thickness in both the training and validation steps. In this study, we demonstrated that deep learning can be used to simulate the influence of NOMs on the NF system and also be applied to simulate other membrane processes.

Filtration of Elastic Polymers and Spherical Gels through a Silica-Deposited Layer on a Porous Membrane

A 120-nm silica suspension was permeated through a porous polyethylene (PE) hollow-fiber membrane, as was a solution of deformable elastic particles of poly(N-isopropylacrylamide) (PNIPAM) gel and dextran. The amount adsorbed and flux of permeation were analyzed with ordinary differential equations to obtain adsorption coefficients, maximum amounts adsorbed, and pore-narrowing factors. The thickness of the “silica-deposited layer” on the membrane was 1 μm. In a batch adsorption mode, 5.0 mg of PNIPAM gel and 30 mg of dextran were adsorbed on the PE membrane, with no adsorption on the silica. The PE membrane pores were narrowed by a secondary layer of adsorbed PNIPAM gel. When filtered through the silica-deposited layer, PNIPAM gel occupies gaps, resulting in a reduced permeation flux. Dextran passed through the silica-deposited layer and was partially adsorbed on the PE membrane. The modified membrane can control adsorption, filtration, and flux permeation, which leads to dynamic membrane separations.

A new approach for modeling flux variation in membrane filtration and experimental verification

It is important to model flux variation during the membrane filtration process, particularly in the early stage of filtration where severe fouling causes rapid flux decay in a short period of time. The objective of this study was to develop a combined fouling mathematical model based on energy head loss principle for prediction of flux variation in the membrane filtration. The complete-cake model was employed in the model in order to describe the loss of membrane available area due to pore clogging, while, the classical cake model was used for cake filtration. A new dimensionless parameter, namely the filter number (FN) was proposed in this study to account for the unmeasurable properties of the membrane in the model. The application of the proposed model was tested and compared with the existing models using experimental data for the filtration of wastewater sludge, microalgae suspension and sodium alginate solution with different membranes and pressures. The results showed that the flux calculated values of the new model had good agreements with the experimental data under different conditions. According to statistical analyses, the model improved the representing accuracy of flux variation in the early stage of filtration. In addition, the model provides better performance and efficiency in comparison to the existing models for high flux operations which is more conventionally applied in the industry and is expected to be more in the future.

Bentonite Modified by Allylamine Polymer for Adsorption of Amido Black 10B

The main object of this work is to remove Amido black 10B using a new type of bentonite-based adsorbent with cationic groups by the modification of polyallyl amines between the interlayers of bentonite. Fourier transform infrared, X-ray diffraction, thermogravimetric analysis, and scanning electron microscopy were used to characterize the functionalized bentonite. A series of batch adsorption experiments were performed. The maximum adsorption amount was 144.08 mg g⁻¹ when the pH was 2 and the contact time was 120 min. In addition, the equilibrium isotherm data were analyzed using Langmuir and Freundlich isotherm models, while only the Langmuir model could provide a high correlation. Therefore, this study provided a new functionalized bentonite as a low-cost adsorbent for dye removal from water.