COVID-19 and beliefs about tobacco use: an online cross-sectional study in Iran

Environmental Science and Pollution Research - There is mixed evidence surrounding the relationship between tobacco use and COVID-19 infection/progression. The current study investigates beliefs...     

Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.     

Markers of oxidative stress and toxicant exposure among young waterpipe smokers in the USA

Waterpipe (aka hookah) tobacco smokers are exposed to toxicants that can lead to oxidative DNA and RNA damage, a precursor to chronic disease formation. This study assessed toxicant exposure and biomarkers of DNA [8-oxo-7, 8-dihydro-2′-deoxyguanosine (8-oxodG)] and RNA [8-oxo-7,8-dihydroguanosine (8-oxoGuo)] oxidative damage during smoking of flavored and non-flavored waterpipe tobacco. Thirty waterpipe smokers completed two counterbalanced 2-h lab waterpipe smoking sessions (flavored vs. non-flavored waterpipe tobacco). Urinary concentrations of 8-oxodG and 8-oxoGuo and expired carbon monoxide (eCO) were measured before and after the smoking sessions. A significant increase in the urinary concentrations of 8-oxodG (from 2.12 ± 0.83 to 2.35 ± 0.91 ng/mg creatinine, p = 0.024) and 8-oxoGuo (from 2.96 ± 0.84 to 3.45 ± 0.76 ng/mg creatinine, p = 0.003) were observed after smoking the non-flavored and flavored waterpipe tobacco, respectively. Our results also showed that the mean ± SD of eCO increased significantly after smoking the flavored (from 1.3 ± 1.1 to 20.3 ± 23.6 ppm, p < 0.001) and non-flavored waterpipe tobacco (from 1.8 ± 1.2 to 24.5 ± 26.1 ppm, p < 0.001). There were no significant differences in the means of 8-oxodG (p = 0.576), 8-oxoGuo (p = 0.108), and eCO (p = 0.170) between the flavored and non-flavored tobacco sessions. Smoking non-flavored and flavored waterpipe tobacco leads to oxidative stress and toxicant exposure. Our findings add to the existing evidence about the adverse effects of waterpipe tobacco smoking (WTS) and the need for strong policies to inform and protect young people from the risks of WTS.

     

Minimizing the cost of translocation failure with decision‐tree models that predict species’ behavioral response in translocation sites

The high number of failures is one reason why translocation is often not recommended. Considering how behavior changes during translocations may improve translocation success. To derive decision‐tree models for species’ translocation, we used data on the short‐term responses of an endangered Australian skink in 5 simulated translocations with different release conditions. We used 4 different decision‐tree algorithms (decision tree, decision‐tree parallel, decision stump, and random forest) with 4 different criteria (gain ratio, information gain, gini index, and accuracy) to investigate how environmental and behavioral parameters may affect the success of a translocation. We assumed behavioral changes that increased dispersal away from a release site would reduce translocation success. The trees became more complex when we included all behavioral parameters as attributes, but these trees yielded more detailed information about why and how dispersal occurred. According to these complex trees, there were positive associations between some behavioral parameters, such as fight and dispersal, that showed there was a higher chance, for example, of dispersal among lizards that fought than among those that did not fight. Decision trees based on parameters related to release conditions were easier to understand and could be used by managers to make translocation decisions under different circumstances. Minimizar el Costo del Fracaso de la Reubicación con Modelos de Árboles de Decisión que Predigan la Respuesta Conductual de la Especie en los Sitios de Reubicación     

New analytical formulations for calculation of dispersion parameters of Gaussian model using parallel CFD

New analytical formulations are presented for calculation of most effective parameters in the Gaussian plume dispersion model; the standard deviations of concentration for horizontal and vertical dispersion in neutral atmosphere conditions. Employing parallel Computational Fluid Dynamics (CFD) as a powerful tool, some well-known analytical generations of Pasquill–Gifford–Turner experimental data are modified. To achieve this aim, CFD simulations are carried out for single stack dispersion on flat terrain surface and ground level concentrations are determined in different distances. An inverse procedure in Gaussian plume dispersion model is then applied and standard deviations of horizontal and vertical dispersions are obtained. The values are compared with those of the well-known methods of Doury, Briggs and Hanna in two cases: the experimental data for release of krypton-85 from 100 m high and pollution dispersion from three 28 m high stacks of Besat power plant near Tehran. The comparison indicates that new formulations for plume dispersion are more accurate than other well-known formulations.     

Improved power density and Cr/Pb removal using ozone in a microbial desalination cell

Environmental Chemistry Letters - Microbial desalination cells are promising bio-electrochemical technologies for water desalination, treating wastewater and bioelectricity production. In this...     

Seasonal trend and source identification of polycyclic aromatic hydrocarbons associated with fine particulate matters (PM2.5) in Isfahan City,Iran, using diagnostic ratio and PMF model

Environmental Science and Pollution Research - Particulate matters (PMs) and their associated chemical compounds such as polycyclic aromatic hydrocarbons (PAHs) are important factors to evaluate...     

Effects of cimetidine and N-acetylcysteine on paraquat-induced acute lung injury in rats: a preliminary study

Abstract

Lung injury in rats challenged with paraquat at 20?mg kg^?1 body weight was histopathologically evident by inflammation, hemorrhage, and vascular congestion. Increased levels of reactive oxygen species and lipid peroxidation, decreased glutathione content, and lower tissue antioxidant capacity was found. The effects of N-acetylcysteine and cimetidine, a well-known potent inhibitor for organic cation transport, were examined. Lung injury was attenuated by N-acetylcysteine but not by cimetidine. The findings are consistent with the assumption that beneficial effects of N-acetylcysteine administration in paraquat-challenged animals might be linked to its ability for preserving the cellular redox environment and preventing oxidative stress, while cimetidine might even hasten paraquat-induced lung injury. On the other hand, the effects of cimetidine on paraquat-induced lung injury underline the importance of future studies on the role of transporters in this complication.     

Fish Bone as a Low-Cost Adsorbent for Dye Removal from Wastewater: Response Surface Methodology and Classical Method

This research studied the application of fish bone as a low-cost adsorbent for the removal of two basic dyes (C.I. Basic Blue 41 and C.I. Basic Yellow 28) from textile wastewaters. The surface morphology and functional groups of the fish bone was studied by scanning electron microscopy and Fourier transform infrared, respectively. The experiments were designed in two methods: classical method and response surface methodology (RSM). The effect of operating parameters including pH, initial dye concentration, adsorbent dosage, and inorganic salts was investigated by both methods. The optimum conditions to satisfy 75 % of dye removal for both dyes were predicted by RSM method and the results were very close to the experimental values. So, it was concluded that the fish bone can be used as a low-cost adsorbent for dye removal from effluents.     

Spatiotemporal analysis of COVID-19, air pollution,climate, and meteorological conditions in a metropolitan region of Iran

The COVID-19 pandemic has a close relationship with local environmental conditions. This study explores the effects of climate characteristics and air pollution on COVID-19 in Isfahan province, Iran. A number of COVID-19 positive cases, main air pollutants, air quality index (AQI), and climatic variables were received from March 1, 2020, to January 19, 2021. Moreover, CO, NO₂, and O₃ tropospheric levels were collected using Sentinel-5P satellite data. The spatial distribution of variables was estimated by the ordinary Kriging and inverse weighted distance (IDW) models. A generalized linear model (GLM) was used to analyze the relationship between environmental variables and COVID-19. The seasonal trend of nitrogen dioxide (NO₂), wind speed, solar energy, and rainfall like COVID-19 was upward in spring and summer. The high and low temperatures increased from April to August. All variables had a spatial autocorrelation and clustered pattern except AQI. Furthermore, COVID-19 showed a significant association with month, climate, solar energy, and NO₂. Suitable policy implications are recommended to be performed for improving people’s healthcare and control of the COVID-19 pandemic. This study could survey the local spread of COVID-19, with consideration of the effect of environmental variables, and provides helpful information to health ministry decisions for mitigating harmful effects of environmental change. By means of the proposed approach, probably the COVID-19 spread can be recognized by knowing the regional climate in major cities. The present study also finds that COVID-19 may have an effect on climatic condition and air pollutants.