Predicting Carbon Monoxide Concentrations in the Air of Pardis City,Iran, Using an Artificial Neural Network

To date, several methods have been proposed to explain the complex process of air pollution prediction. One of these methods uses neural networks. Artificial neural networks (ANN) are a branch of artificial intelligence, and because of their nonlinear mathematical structures and ability to provide acceptable forecasts, they have gained popularity among researchers. The goal of our study as documented in this article was to compare the abilities of two different ANNs, the multilayer perceptron (MLP) and radial basis function (RBF) neural networks, to predict carbon monoxide (CO) concentrations in the air of Pardis City, Iran. For the study, we used data collected hourly on temperature, wind speed, and humidity as inputs to train the networks. The MLP neural network had two hidden layers that contained 13 neurons in the first layer and 25 neurons in the second layer and reached a mean bias error (MBE) of 0.06. The coefficient of determination (R²), index of agreement (IA), and the Nash–Scutcliffe efficiency (E) between the observed and predicted data using the MLP neural network were 0.96, 0.9057, and 0.957, respectively. The RBF neural network with a hidden layer containing 130 neurons reached an MBE of 0.04. The R², IA, and E between the observed and predicted data using the RBF neural network were 0.981, 0.954, and 0.979, respectively. The results provided by the RBF neural network had greater acceptable accuracy than was the case with the MLP neural network. Finally, the results of a sensitivity analysis using the MLP neural network indicated that temperature is the primary factor in the prediction of CO concentrations and that wind speed and humidity are factors of second and third importance when forecasting CO levels.     

Insights to the oxidative desulfurization process of fossil fuels over organic and inorganic heterogeneous catalysts: advantages and issues

Environmental Science and Pollution Research - Strict environmental laws have been put in place around the world to reduce the amount of sulfur in the fuel to reduce the emissions of harmful gases...     

Forecast optimal fluoride concentration data in drinking water according to the ambient temperature in Golestan,Iran

Controlling fluoride concentrations in drinking water at optimal levels could be effective in preventing certain negative health effects in humans. This study investigated optimal fluoride concentrations in potable water in Golestan province, according the ambient temperatures in the province. The study used data on fluoride concentrations in drinking water supplied by the Water and Wastewater Company of Golestan Province. The annual mean maximum temperatures were extracted from a website that recorded daily ambient temperature. The optimal value of fluoride in drinking water for each county of Golestan province was calculated by the Galgan and Vermillion formula. The results show that all of the counties should contain fluoride concentrations ranging from 0.73 to 0.766 milligrams per liter (mg/L) according to the calculation formula, while fluoride concentrations were instead reported to range between 0.23 and 0.53 mg/L by the Water and Wastewater company. In addition, according to World Health Organization (WHO) recommendations, the concentrations of fluoride in potable in all of the cities in Golestan province fall below the WHO standard. In conclusion, we suggest that the fluoride concentrations in Golestan province's drinking water should be taken into account by the appropriate authorities and that optimal fluoride concentrations in drinking water according to ambient temperatures be set to avoiding negative health impacts.     

Optimized Removal of Acid Blue 62 from Textile Waste Water by SBA-15/PAMAM Dendrimer Hybrid Using Response Surface Methodology

SBA-15/PAMAM Nano adsorbent was synthesized by the proficiency of SBA-15 as an original compound, 3-chloropropyltrimethoxysilane as a bridge chemical compound and polyamidoamine dendrimer (PAMAM) in the role of a multifunctional amine end group for adsorption of acid blue 62 (AB62) from aqueous media. The synthesized adsorbent was characterized by transmission electron microscope, field emission scanning electron microscope and Fourier-transform infrared spectroscope. A response surface methodology was employed to evaluate the simple and amalgamated factors of the operating variables subtending initial pH (2–12), adsorbent dosage(0.01–0.03 g), contact time (5–120 min), initial dye concentration (40–600 ppm) and temperature (25–45?°C) to optimize the operating statues of the treatment method. These parameters were altered at five levels pursuant to the central composite design to appraise their effects on AB62 removal through analysis of variance. Analysis of variance represented a high coefficient of definition amount (R²?=?0.9999) and acceptable prediction quadratic polynomial model was concluded which ascertain the suitability of the model and a high correlation among the predicted and empirical amounts. Utmost color removal efficiency was auspicated and empirically accredited. The optimum conditions relied on acquired results for AB62 removal were at an initial pH of 2, adsorbent dosage of 0.03 g SBA-15/PAMAM, dye concentration of 40 mg l^?1, time contact of 60 min and temperature of 25?°C.     

A systematic review of emerging human coronavirus (SARS-CoV-2) outbreak: focus on disinfection methods,environmental survival,and control and prevention strategies

Recently, an outbreak of a novel human coronavirus which is referred to as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (COVID-19) by the World Health Organization (WHO) was identified in Wuhan, China. To help combat the pandemic, a systematic review (SR) was performed to collect all available studies concerning inactivation methods, environmental survival, and control and prevention strategies. A comprehensive literature survey yielded 42 eligible studies which included in the SR. The results confirmed that the WHO recommended two alcohol-based hand rub formulations (ethanol 70–95% and 2-propanol 70–100%) had an efficient virucidal activity in less than 60 s by more and equal 4 log₁₀ (≥ 99.99) approximately and could be used for disinfection in public health and health-care facilities. The findings indicated that SARS-CoV-1 and SARS-CoV-2 can survive under different environmental conditions between 4 and 72 h approximately. The results also demonstrate that temperature and relative humidity are important factors in the survival of SARS-CoV-2. The main strategies recommended by the WHO to avoid contracting SARS-CoV-2 are hand washing several times in the day and maintaining social distancing with others. It is important to note that the more studies require addressing, the more possible airborne transmission due to the survival of SARS-CoV-2 in aerosols for 3 h approximately. We hope that the results of the present SR can help researchers, health decision-makers, policy-makers, and people for understanding and taking the proper behavior to control and prevent further spread of SARS-CoV-2.

     

Preliminary assessment of cement kiln dust in solidification and stabilization of mercury containing waste from a chlor-alkali unit

Journal of Material Cycles and Waste Management - A low-level mercury containing hazardous waste with a mercury concentration of 22.0 ± 5.00 ppm generated at a...     

Optimizing stabilization of waste-activated sludge using Fered-Fenton process and artificial neural network modeling (KSOFM,MLP)

Sludge management is a fundamental activity in accordance with wastewater treatment aims. Sludge stabilization is always considered as a significant step of wastewater sludge handling. There has been a progressive development observed in the approach to the novel solutions in this regard. In this research, based on own initially experimental results in lab-scale regarding Fered-Fenton processes in view of organic loading (volatile-suspended solids, VSS) removal efficiency, a combination of both methods towards proper improving of excess biological sludge stabilization was investigated. Firstly, VSS removal efficiency has been experimentally studied in lab-scale under different operational conditions taking into consideration pH [Fe²⁺]/[H₂O₂], detention time [H₂O₂], and current density parameters. Therefore, the correlations of the same parameters have been determined by utilizing Kohonen self-organizing feature maps (KSOFM). In addition, multi-layer perceptron (MLP) has been employed afterwards for a comprehensive evaluation of investigating parameters correlation and prediction aims. The findings indicated that the best proportion of iron to hydrogen peroxide and the optimum pH were 0.58 and 3.1, respectively. Furthermore, maximum retention time about 6 h with a hydrogen peroxide concentration of 1,568 mg/l and a current density of 650–750 mA results to the optimum VSS removal (efficiency equals to 81 %). The performance of KSOFM and MLP models is found to be magnificent, with correlation ranging (R) from 0.873 to 0.998 for the process simulation and prediction. Finally, it can be concluded that the Fered-Fenton reactor is a suitable efficient process to reduce considerably sludge organic load and mathematical modeling tools as artificial neural networks are impressive methods of process simulation and prediction accordingly.