Computational Simulation for Transport of Priority Organic Pollutants through Nanoporous Membranes

Catalytic Activity of Rare Earth Elements (REEs) in Advanced Oxidation Processes of Wastewater Pollutants: A Review

In recent years, sewage treatment plants did not effectively remove emerging water pollutants, leaving potential threats to human health and the environment. Advanced oxidation processes (AOPs) have emerged as a promising technology for the treatment of contaminated wastewater, and the addition of catalysts such as heavy metals has been shown to enhance their effectiveness. This review focuses on the use of rare earth elements (REEs) as catalysts in the AOP process for the degradation of organic pollutants. Cerium and La are the most studied REEs, and their mechanism of action is based on the oxygen vacancies and REE ion concentration in the catalysts. Metal oxide surfaces improve the decomposition of hydrogen peroxide to form hydroxide species, which degrade the organics. The review discusses the targets of AOPs, including pharmaceuticals, dyes, and other molecules such as alkaloids, herbicides, and phenols. The current state-of-the-art advances of REEs-based AOPs, including Fenton-like oxidation and photocatalytic oxidation, are also discussed, with an emphasis on their catalytic performance and mechanism. Additionally, factors affecting water chemistry, such as pH, temperature, dissolved oxygen, inorganic species, and natural organic matter, are analyzed. REEs have great potential for enhancing the removal of dangerous organics from aqueous solutions, and further research is needed to explore the photoFenton-like activity of REEs and their ideal implementation for wastewater treatment.

Neural-based modeling adsorption capacity of metal organic framework materials with application in wastewater treatment

We developed a computational-based model for simulating adsorption capacity of a novel layered double hydroxide (LDH) and metal organic framework (MOF) nanocomposite in separation of ions including Pb(II) and Cd(II) from aqueous solutions. The simulated adsorbent was a composite of UiO-66-(Zr)-(COOH)2 MOF grown onto the surface of functionalized Ni50-Co50-LDH sheets. This novel adsorbent showed high surface area for adsorption capacity, and was chosen to develop the model for study of ions removal using this adsorbent. A number of measured data was collected and used in the simulations via the artificial intelligence technique. Artificial neural network (ANN) technique was used for simulation of the data in which ion type and initial concentration of the ions in the feed was selected as the input variables to the neural network. The neural network was trained using the input data for simulation of the adsorption capacity. Two hidden layers with activation functions in form of linear and non-linear were designed for the construction of artificial neural network. The model's training and validation revealed high accuracy with statistical parameters of R2 equal to 0.99 for the fitting data. The trained ANN modeling showed that increasing the initial content of Pb(II) and Cd(II) ions led to a significant increment in the adsorption capacity (Qe) and Cd(II) had higher adsorption due to its strong interaction with the adsorbent surface. The neural model indicated superior predictive capability in simulation of the obtained data for removal of Pb(II) and Cd(II) from an aqueous solution.

Process Design of Ammonia Separation for Nitrification Control in Aeration Basins at an IKORC's Oily Wastewater Treatment Unit

In the current decades, water shortage is well understood as one of the main limiting factors for oil industry development all over the world. One of the available and reasonable solutions is reusing wastewater. The oily wastewater treatment unit of the IKORC oil refinery provides a portion of the makeup water for cooling towers, applying physical, biological, and chemical treatments. Ammonia shocks are the only crisis that disrupts the nitrification process. This condition eventuates in destroying the microorganisms of aeration basins and leads to a high ammonia containing effluent. In order to protect the aeration process, it is mandatory to apply a suitable system for removing excess ammonia. In this study, at first, ammonia removal history is reviewed. Then quantity and quality of the oily sewer are investigated. Because of high volatility of ammonia contamination and high TDS, a stripping tower with air is selected among diverse solutions. Taking into account the principles of project econometrics, operating parameters such as stripping factor, pressure drop, tower volumetric flow rate, and number of towers are determined. Then, the process is designed and its environmental survey is conducted. Finally, calculating indices proved that this project is economically profitable in addition to its environmental benefits.

Numerical simulation of reactive extraction of benzoic acid from wastewater via membrane contactors

Membrane-based non-dispersive solvent extraction is used in many chemical processes due to its significant benefits such as straightforward scale-up and low energy consumption. A mechanistic model was developed to predict recovery of benzoic acid (BA) from wastewater using membrane contactors. Model equations were derived for benzoic acid transport in the membrane module, and solved using FEM. The model findings were compared with experimental results, and an average deviation of 4% was observed between experimental and simulation results. Simulations showed that change in organic phase flowrate and initial concentration of BA does not have considerable effect on the removal efficiency of benzoic acid. In addition, increasing feed flowrate leads to the enhancement of convective mass transfer flux in the tube side of membrane contactor which decreases removal efficiency of benzoic acid.

Synthesis and characterization of polyurethane/poly(vinylpyridine) composite membranes for desulfurization of gasoline

Polyurethane/poly(vinylpyridine) (PU/PVP) composite membranes for desulfurizing gasoline were prepared.