The leachate originated from Solid Waste Landfill Facilities (SWLF) is the wastewater which is the most difficult to treat, because of its very high COD, TKN, TDS and color parameters, and contains significant amounts of primary pollutants and microplastics. In this presentation, Membrane Technologies will be discussed, which has become an increasingly common treatment technology option in the treatment of solid waste SWL leachate. In this context, the application limits of MBR ± NF and Direct RO technologies by using performances of the full-scale facilities and the main problems will be evaluated. In addition, different concentrate management options in MRF ± NF and Direct RO applications, together with their economic dimensions, will be discussed.

Like all other sectors, the water sector is also undergoing rapid digitalisation providing new opportunities for improved, more efficient and economical services. Digital tools can efficiently contribute to membrane applications, and an increasing number of research and applications are reported.
Modelling of the membrane processes has been the traditional approach to using digital tools in the membrane processes. They were used to optimise the flux and predict and reduce fouling. The recent models also contribute to the optimisation of membrane structures.
The use of ANN, machine learning and fuzzy logic in process control has significantly increased in recent years; Flux estimation of dynamic ultrafiltration using machine learning is an example. The use of advanced process control to optimise combined systems, such as pre-coagulation and ultrafiltration, has improved process efficiency and economics. Successful applications of novel approaches to predict and optimise the flux, fouling and cleaning processes are documented, although they may are still in the pilot scales.
Using virtual and hybrid sensors in water quality measurements also contributes to improved process control in membrane processes. Surrogate parameters can contribute to understanding and control of fouling. The application of spectroscopic fingerprints, including fluorescence excitation-emission matrix (EEM) coupled with parallel factor analysis (PARAFAC) are promising examples.
The Digital Twins are developed for several unit processes and combined processes. The development of Digital Twins in membrane processes has also become a reality with the development of models, surveillance and control systems.
This presentation will give an overview of the State-of-the-Art use of digital tools in membrane processes and discuss some research trends.

Aerobic membrane bioreactor (AeMBR) has been widely adopted for wastewater treatment for the last 2 decades particularly for water reuse. Recently, anaerobic MBR (AnMBR) has gained much attraction for wastewater treatment and energy recovery. A vibrating AeMBR (VMBR) and an anaerobic vibrating MBR (VAnMBR) have been established for effective fouling control for wastewater treatment. The VAnMBR also enhanced biogas recovery resulting from minimized dissolved methane. Quorum quenching (QQ) to control membrane fouling in AnMBRs was also studied. A facultative QQ consortium for AI-2-based quorum sensing (QS) disruption (FQQ2) prolonged an AnMBR operation by an average of 3.72 times.

This lecture discusses the incipient development of the first artificial water channels systems. We include only systems that integrate synthetic elements in their water selective translocation unit. Therefore, we exclude peptide channels because their sequences derive from the proteins in natural channels. We review many of the natural systems involved in water and related proton transport processes. We describe how these systems can fit within our primary goal of maintaining natural function within bio-assisted artificial systems. In the last part, we present several inspiring breakthroughs from the last decade in the field of biomimetic artificial water channels. All these examples demonstrate how the novel interactive water-channels can parallel biomolecular systems. At the same time these simpler artificial water channels offer a means of understanding water structures useful to understanding many biological scenarios. Moreover, they can be used for the preparation of highly selective membranes for desalination.

The efficiency of water treatment systems in virus removal is affected by viruses’ propensity to attach to or leave surfaces such as membranes, biofilms, and suspended matter. Thus, understanding virus adhesion is important for effective virus detection – the task of paramount importance for public safety. The challenge is especially acute in “viral reservoir” environments such as water reuse facilities. The presentation will summarize results from several recent studies aimed at elucidating physicochemical bases of virus adhesion onto archetypal surfaces including polymers (e. g. polymers used to make membrane filters and masks) and various fomites (e. g. ceramics and passivated metals). Adhesion of human viruses and bacteriophages is explored using a combination of XDLVO modeling, adhesion tests based on QCM-D measurements, and membrane separation experiments. The results are interpreted based on physicochemical properties of viruses and target surfaces, which are typified on the basis of their surface energy components. We show that hydrophobic and electrostatic interactions govern virus attachment while van der Waals interactions play a relatively minor role. In higher ionic strength solutions, the extent of virus attachment correlates with the free energy of virus-surface interfacial interaction. The information on the efficiency of virus attachment to materials as a function of their surface energy components can guide screening and selection of materials for virus removal and detection applications. More broadly, the proposed methodology can help design anti-adhesive surfaces, develop surface cleaning solutions and protocols, and inform transport and fate models for viruses in environments such as water reuse facilities and other settings of critical importance for public health.