Toxic organic dye removal from the textile wastewater is a serious concern. It is difficult to choose a single or a combination of treatment techniques between various available options; each with certain advantages and drawbacks. Six different techniques were applied on the same textile wastewater to evaluate the most effective in terms of treatment efficiency. The three most important textile wastewater quality parameters of chemical oxygen demand (COD), total suspended solids (TSS) and color were made the basis of the comparison of different treatment techniques. Other critical parameters such as treatment time, ease of operation and chemical cost employed were also considered. No single biological or physico-chemical treatment technique was found capable of removing up to 80% of the influent COD, TSS and color simultaneously from the textile wastewater. The conventional activated sludge (CAS) treatment followed by effluent polishing with the sand filtration (SF) and activated carbon adsorption columns was proved to be the most promising with COD, TSS and color removal efficiencies of 81.6%, 88.5% and 94.5% respectively. Moreover this combination of techniques enjoys lower chemical cost, medium operation time and fewer difficulties in the process control. Hence, the combination is recommended for the treatment of the textile effluents

The separation and capture of CO₂ have become an urgent and important agenda because of the CO₂-induced global warming and the requirement of industrial products. Membrane-based technologies have proven to be a promising alternative for CO₂ separations. To make the gas-separation membrane process more competitive, productive membrane with high gas permeability and high selectivity is crucial. Herein, we developed new cellulose triacetate (CTA) and cellulose diacetate (CDA) blended membranes for CO₂ separations. The CTA and CDA blends were chosen because they have similar chemical structures, good separation performance, and its economical and green nature. The best position in Robeson’s upper bound curve at 5 bar was obtained with the membrane containing 80 wt.% CTA and 20 wt.% CDA, which shows the CO₂ permeability of 17.32 barrer and CO₂/CH₄ selectivity of 18.55. The membrane exhibits 98% enhancement in CO₂/CH₄ selectivity compared to neat membrane with only a slight reduction in CO₂ permeability. The optimal membrane displays a plasticization pressure of 10.48 bar. The newly developed blended membranes show great potential for CO₂ separations in the natural gas industry.

Natural gas demand has increased rapidly across the globe in the last decade, and it is set to play an important role in meeting future energy requirements. Natural gas is mainly produced from fossil fuel and is a side product of crude oil produced beneath the earth’s crust. Materials hazardous to the environment, like CO₂, H₂S, and C₂H₄, are present in raw natural gas. Therefore, purification of the gaseous mixture is required for use in different industrial applications. A comprehensive computational fluid dynamics (CFD) model was proposed to perform the separation of natural gas from other gases using membrane modules. The CFD technique was utilized to estimate gas flow variations in membrane modules for gas separation. CFD was applied to different membrane modules to study gas transport through the membrane and flux, and to separate the binary gas mixtures. The different parameters of membrane modules, like feed and permeate pressure, module length, and membrane thickness, have been investigated successfully. CFD allows changing the specifications of membrane modules to better configure the simulation results. It was concluded that in a membrane module with increasing feed pressure, the pressure gradient also increased, which resulted in higher flux, higher permeation, and maximum purity of the permeate. Due to the high purity of the gaseous product in the permeate, the concentration polarization effect was determined to be negligible. The results obtained from the proposed CFD approach were verified by comparing with the values available in the literature.

The Claus process is one of the promising technologies for acid gas processing and sulfur recovery. Hydrogen sulfide primarily exists as a byproduct in the gas processing unit. It must be removed from natural gas. The Environmental Protection Agency (EPA) notices that increasing SO₂ and CO₂ in the air harms the environment. Sulfur generally has an elemental content of 0.1–6 wt % in crude oil, but the value could be higher than 14% for some crude oils and asphalts. It produces SO₂ and CO₂ gases, which damage the environment and atmosphere of the earth, called primary pollutants. When SO₂ gas is reacted with water in the atmosphere, it causes sulphur and nitric acid, called a secondary pollutant. The world countries started desulphurization in 1962 to reduce the amount of sulfur in petroleum products. In this research, the Claus process was modeled in Aspen Plus software (AspenTech, Bedford, MA, USA) and industrial data validated it. The Peng–Robinson method is used for the simulation of hydrocarbon components. The influence of oxygen gas concentration, furnace temperature, the temperature of the first catalytic reactor, and temperature of the second catalytic reactor on the Claus process were studied. The first objective of the research is process modeling and simulation of a chemical process. The second objective is optimizing the process. The optimization tool in the Aspen Plus is used to obtain the best operating parameters. The optimization results show that sulfur recovery increased to 18%. Parametric analysis is studied regarding operating parameters and design parameters for increased production of sulfur. Due to pinch analysis on the Claus process, the operating cost of the heat exchangers is reduced to 40%. The third objective is the cost analysis of the process. Before optimization, it is shown that the production of sulfur recovery increased. In addition, the recovery of sulfur from hydrogen sulfide gas also increased. After optimizing the process, it is shown that the cost of heating and cooling utilities is reduced. In addition, the size of equipment is reduced. The optimization causes 2.5% of the profit on cost analysis.

There is an enormous need in the health welfare sector to manufacture inexpensive dialyzer membranes with minimum dialysis duration. In order to optimize the dialysis cost and time, an in-depth analysis of the effect of dialyzer design and process parameters on toxins (ranging from tiny to large size molecules) clearance rate is required. Mathematical analysis and enhanced computational power of computers can translate the transport phenomena occurring inside the dialyzer while minimizing the development cost. In this paper, the steady-state mass transport in blood and dialysate compartment and across the membrane is investigated with convection-diffusion equations and tortuous pore diffusion model (TPDM), respectively. The two-dimensional, axisymmetric CFD model was simulated by using a solver based on the finite element method (COMSOL Multiphysics 5.4). The effect of design and process parameters is analyzed by solving model equations for varying values of design and process parameters. It is found that by introducing tortuosity in the pore diffusion model, the clearance rate of small size molecules increases, but the clearance rate of large size molecules is reduced. When the fiber aspect ratio (db/L) varies from 900 to 2300, the clearance rate increases 37.71% of its initial value. The results also show that when the pore diameter increases from 10 nm to 20 nm, the clearance rate of urea and glucose also increases by 2.09% and 7.93%, respectively, with tolerated transport of albumin molecules.