Recent Developments in Nanomaterials-Modified Membranes for Improved Membrane Distillation Performance.

Membrane distillation (MD) is a thermally induced membrane separation process that utilizes vapor pressure variance to permeate the more volatile constituent, typically water as vapor, across a hydrophobic membrane and rejects the less volatile components of the feed. Permeate flux decline, membrane fouling, and wetting are some serious challenges faced in MD operations. Thus, in recent years, various studies have been carried out on the modification of these MD membranes by incorporating nanomaterials to overcome these challenges and significantly improve the performance of these membranes. This review provides a comprehensive evaluation of the incorporation of new generation nanomaterials such as quantum dots, metalloids and metal oxide-based nanoparticles, metal organic frameworks (MOFs), and carbon-based nanomaterials in the MD membrane. The desired characteristics of the membrane for MD operations, such as a higher liquid entry pressure (LEPw), permeability, porosity, hydrophobicity, chemical stability, thermal conductivity, and mechanical strength, have been thoroughly discussed. Additionally, methodologies adopted for the incorporation of nanomaterials in these membranes, including surface grafting, plasma polymerization, interfacial polymerization, dip coating, and the efficacy of these modified membranes in various MD operations along with their applications are addressed. Further, the current challenges in modifying MD membranes using nanomaterials along with prominent future aspects have been systematically elaborated.

The Influence of COD Fraction Forms and Molecules Size on Hydrolysis Process Developed by Comparative OUR Studies in Activated Sludge Modelling.

The activated sludge models (ASMs) commonly used by the International Water Association (IWA) task group are based on chemical oxygen demand (COD) fractionations. However, the proper evaluation of COD fractions, which is crucial for modelling and especially oxygen uptake rate (OUR) predictions, is still under debate. The biodegradation of particulate COD is initiated by the hydrolysis process, which is an integral part of an ASM. This concept has remained in use for over 30 years. The aim of this study was to verify an alternative, more complex, modified (Activated Sludge Model No 2d) ASM2d for modelling the OUR variations and novel procedure for the estimation of a particulate COD fraction through the implementation of the GPS-X software (Hydromantis Environmental Software Solutions, Inc., Hamilton, ON, Canada) in advanced computer simulations. In comparison to the original ASM2d, the modified model more accurately predicted the OUR behavior of real settled wastewater (SWW) samples and SWW after coagulation-flocculation (C-F). The mean absolute relative deviations (MARDs) in OUR were 11.3-29.5% and 18.9-45.8% (original ASM2d) vs. 9.7-15.8% and 11.8-30.3% (modified ASM2d) for the SWW and the C-F samples, respectively. Moreover, the impact of the COD fraction forms and molecules size on the hydrolysis process rate was developed by integrated OUR batch tests in activated sludge modelling.

Design and analysis for the removal of active pharmaceutical residues from synthetic wastewater stream.

The removal of three over-the-counter pharmaceuticals from aqueous solution using four different adsorbents was analyzed. To study the effect of infused pharmaceutical and adsorbent on the adsorption system, both the concentration of drug and adsorbent dosage were varied, with constant temperature and pressure at different contact time. Adsorption kinetics, isotherm models, and ANOVA allegorized a generic trend for pharmaceutical removal efficiency of the adsorbents that varied as follows: activated carbon > fly ash > bentonite > sugar cane bagasse ash. The Tempkin model appears to fit the isotherm data better than Freundlich and Langmuir. Correspondingly, the kinetic studies implied a pseudo-second-order fit, to understand the mechanism by which the solute accumulates on the surface of a solid and gets adsorbed to the surface via intra-particle diffusion. Furthermore, some special cases of removal tendencies were noted based on sorbate-sorbent interaction. Effectively, it was observed that at an adsorbent loading of 2 g and initial concentration of 0.2 mmol L-1, bentonite, fly ash, and activated carbon were able to strip more than 80% of all pharmaceuticals from urine. A framework for the highest significance of the experiments was obtained using response surface methodology by the combination of ciprofloxacin-bentonite followed by paracetamol-activated carbon and ibuprofen-activated carbon. Quasi-Newton and Bayesian regression methods were implemented on Langmuir isotherm by designing the neural network for the batch adsorption experiments. Based on the numerical calculations and graphical representations, the proposed model leads to the result that error is minimized and the values are optimized for different pharmaceuticals such as paracetamol, ibuprofen, ciprofloxacin that can be removed from wastewater streams by locally available adsorbents. Graphical abstract.