Photocatalytic Removal of Methylbenzene Vapors by MnO2/Al2O3/Fe2O3 Nano composite

Methyl benzene, which has carcinogenic effects, is a volatile organic compound that is widely used in various industries. Nano composites of Mno2/Al203/Fe203, which is a new photocatalyst, have not been applied to remove contaminants from air streams. Therefore, the aim of the present study was to investigate the photocatalytic removal of ethyl benzene by using this nano composite activated by visible light. Morphological characteristics of the synthesized Nano composite in a sol-gel method are determined through XRD, FTIR, and SEM. Through the photocatalyst process and by the use of visible light radiation, the synthesized Nano composite is used to degrade ethyl benzene in the gas phase. In order to estimate the main effects and interaction ones and to optimize the experiment numbers, the response surface method was used. Operational parameters investigated in the study are the initial concentration of contaminants, relative humidity, and the residence time, which were considered in three levels; further, the experiments were designed by Design Expert version 9 software. The results show the Nano composite particle sizes were less than 82 nanometers. The findings also indicate that relative humidity and residence time were effective parameters in removal efficiency of ethyl benzene. This Nano composite, at the optimal conditions, was capable of removing 98.72% of the pollutants, with an initial content of 300 ppm. MnO2/Al2O3/Fe2O3 Nano composite is a suitable catalyst to remove ethyl benzene from air streams. Among the features of the Nano composite are reaction at room temperature and lower production dangerous byproducts, which are the main advantages of this Nano composite as compared with other nano composites

Photocatalytic Removal of Methylbenzene Vapors by MnO2/Al2O3/Fe2O3 Nano composite

Methyl benzene, which has carcinogenic effects, is a volatile organic compound that is widely used in various industries. Nano composites of Mno2/Al203/Fe203, which is a new photocatalyst, have not been applied to remove contaminants from air streams. Therefore, the aim of the present study was to investigate the photocatalytic removal of ethyl benzene by using this nano composite activated by visible light. Morphological characteristics of the synthesized Nano composite in a sol-gel method are determined through XRD, FTIR, and SEM. Through the photocatalyst process and by the use of visible light radiation, the synthesized Nano composite is used to degrade ethyl benzene in the gas phase. In order to estimate the main effects and interaction ones and to optimize the experiment numbers, the response surface method was used. Operational parameters investigated in the study are the initial concentration of contaminants, relative humidity, and the residence time, which were considered in three levels; further, the experiments were designed by Design Expert version 9 software. The results show the Nano composite particle sizes were less than 82 nanometers. The findings also indicate that relative humidity and residence time were effective parameters in removal efficiency of ethyl benzene. This Nano composite, at the optimal conditions, was capable of removing 98.72% of the pollutants, with an initial content of 300 ppm. MnO2/Al2O3/Fe2O3 Nano composite is a suitable catalyst to remove ethyl benzene from air streams. Among the features of the Nano composite are reaction at room temperature and lower production dangerous byproducts, which are the main advantages of this Nano composite as compared with other nano composites

Photocatalytic Removal of Methylbenzene Vapors by MnO2/Al2O3/Fe2O3 Nano composite

Methyl benzene, which has carcinogenic effects, is a volatile organic compound that is widely used in various industries. Nano composites of Mno2/Al203/Fe203, which is a new photocatalyst, have not been applied to remove contaminants from air streams. Therefore, the aim of the present study was to investigate the photocatalytic removal of ethyl benzene by using this nano composite activated by visible light. Morphological characteristics of the synthesized Nano composite in a sol-gel method are determined through XRD, FTIR, and SEM. Through the photocatalyst process and by the use of visible light radiation, the synthesized Nano composite is used to degrade ethyl benzene in the gas phase. In order to estimate the main effects and interaction ones and to optimize the experiment numbers, the response surface method was used. Operational parameters investigated in the study are the initial concentration of contaminants, relative humidity, and the residence time, which were considered in three levels; further, the experiments were designed by Design Expert version 9 software. The results show the Nano composite particle sizes were less than 82 nanometers. The findings also indicate that relative humidity and residence time were effective parameters in removal efficiency of ethyl benzene. This Nano composite, at the optimal conditions, was capable of removing 98.72% of the pollutants, with an initial content of 300 ppm. MnO2/Al2O3/Fe2O3 Nano composite is a suitable catalyst to remove ethyl benzene from air streams. Among the features of the Nano composite are reaction at room temperature and lower production dangerous byproducts, which are the main advantages of this Nano composite as compared with other nano composites

Providing an approach to analyze the risk of central oxygen tanks in hospitals during the COVID-19 pandemic

The central oxygen unit of hospitals is considered a high-risk unit, requiring high safety standards to maintain the integrity of the system during the COVID-19 pandemic. The linear reasoning assumption of conventional risk analysis methods cannot adequately describe these modern systems, which are characterized by tight connections and complex interactions between technical, human, and organizational aspects. Therefore, this study presents a new and comprehensive approach to oxygen tanks in hospitals during the COVID-19 pandemic. In this study, trapezoidal fuzzy numbers were used to calculate failure rates. After determining the probability of basic events (BEs), intermediate events (IE), and top event (TE) with fuzzy logic and transferring it into Bayesian Network (BN), deductive and inductive reasoning, and sensitivity analysis were performed using RoV in GeNIe software. The results of the case study showed that the IE of “Human Error” had the highest probability of fuzzy fault tree (FFT) and the probability of oxygen leakage was lower using FBN than FFT. According to the results, BE16 (failure to use standard and updated instructions) and BE12 (defects in the inspection and testing program of tank devices) had the highest posterior probability, while based on the FFT results, BE4 (defects in the external coating system of the tank) and, BE3 (Corrosive environment (acidity state)) had the least probability. According to the sensitivity analysis, basic events 10, 11, and 16 were the most important in the oxygen leakage event with a very small difference, which was almost in line with the results of posterior FBN (FBNPO). Updating the existing guidelines, fixing defects in the inspection of all types of tank gauges, and testing related equipment can greatly help the reliability of these tanks. Root cause analysis of these events provides opportunities for prevention and emergency response in critical situations, such as the COVID-19 pandemic