Health risk assessment and source apportionment of heavy metals in atmospheric dustfall in a city of Khuzestan Province, Iran.

The heavy metals in the atmospheric particulate matters are now considered a risk for humans and the environment. The purpose of this study was to assess the concentration, source apportionment, and health risk of heavy metals in atmospheric dustfall in Dezful City of Khuzestan Province, Iran. The dustfall samples were collected from five locations every month for one year (2018-2019). The heavy metals ( lead (Pb), cadmium (Cd), chromium (Cr), iron (Fe), and nickel (Ni)) contents of dustfall samples were determined by ICP-OES. The monthly mean of dustfall for five sampling locations was 22.81 ± 21.9 ton.km- 2.month- 1. The mean concentrations of the examined heavy metals were assessed as Fe > Cr > Ni > Pb > Cd. The highest enrichment level belonged to Cd (59.35 ± 128.18) and all heavy metals had enrichment levels beyond 10. The HI (Hazard Index) values were less than one and there was no significant non-carcinogenic risk due to these heavy metals. For children, Ni showed the most HI with a value of 0.205. The calculations demonstrate that the obtained values of cancer risk in both groups are less than the acceptable range (10- 6 to 10- 4). The PMF (Positive Matrix Factorization) results indicated four main sources of pollutants, namely, vehicular exhaust, industrial, road dust, and nonferrous smelting. The results of the study revealed that industrial activities and traffic play crucial roles in increasing the heavy metals contamination of dustfall in Dezful City.

Awareness and Performance towards Proper Use of Disinfectants to Prevent COVID-19: The Case of Iran.

This study aimed to assess the awareness and performance of Qom citizens towards using disinfectants and compared its relationship with geographical distribution of COVID-19 outbreak in Qom, Iran. The study was conducted by a researcher-made questionnaire during April and May, 2020. COVID-19 incidence data for each district of city was obtained from health department of Qom province. Data were analyzed using Excel, SPSS and ArcView (GIS) softwares. It was found that the highest level of citizens' awareness (52%) was in the weak range while their performance (56%) was in the good range. According to Spearman's correlation analysis, there was a strong correlation (rho 0.95) between the total mean of awareness and performance (p < 0.01). The highest incidence rate of COVID-19 was in district 7 which had the lowest mean score in both awareness and performance. In addition, the results of ANOVA (LSD-least significant difference) showed that there was a significant difference (p < 0.05) between district 7-with lower mean scores in awareness and performance-and other districts. Overall, it is concluded that citizens' awareness level was lower than that of their performance. This conclusion not only calls for more training programs to be implemented in public places, schools, universities and governmental offices, but it also necessitates maintaining a proper and timely training about using disinfectants.

Aerosolized SARS-CoV-2 exposure assessment: dispersion modeling with AERMOD.

COVID-19 is now a pandemic and the knowledge gap on SARS-CoV-2, i.e., the COVID-19 disease agent, dispersion persists. The US Centers for Disease Control and Prevention suggests fomites may not be the main route through which the novel coronavirus spreads. Supporting the same view, the latest the World Health Organization report recommends wearing masks for every individual in public, highlighting the transmission through the air. In the current study AERMOD, one of the most validated and tested models suggested by the USEPA, is used to model SARS-CoV-2-laden PM10 in a hypothetical outdoor environment. Multiple scenarios including particle size, wind speed, source height variations as well as and combined scenarios were modeled to estimated how exposure risk changes with the above-mentioned variables. The results reveal that wind speed majorly narrows infectious plume rather than transferring the peak concentration. The particle size variation indicated that small particles, i.e.,0.01 - 2.5 µm, could reach more than 9 m away from the source in concentration range of 10 - 20 (µg/m 3). On the other hand, source height contributes to peak plume shift rather than dispersing the infected particles. This idea was further studies by using combined scenarios which indicated height difference can impact peak plume displacement rather than wind speed. In the worst-case scenario, the results indicate that the virus-laden particles can travel outdoors more than 8 m away from an infected source. The video output of the model results clearly shows the dynamic of viral peak shifts in several scenarios. The results also indicate that in specific conditions the airborne SARS-CoV-2 can be transported to 9 m away from the source. These findings can be useful for individuals as well as decision-makers to mitigated exposure risk in real-world conditions. Supplementary Information: The online version contains supplementary material available at 10.1007/s40201-020-00602-9.

A wavelet-based random forest approach for indoor BTEX spatiotemporal modeling and health risk assessment.

This study reports on BTEX concentrations in one of the largest parking garages in Iran with a peak traffic flow reaching up to ~9300 vehicles in the last few days of the Nowruz holidays. Samples were obtained on different days of the week at three main locations in the Zaer Parking Garage. A novel wavelet-based random forest model (WRF) was trained to estimate BTEX concentrations by decomposing temperature, day of the week, sampling location, and relative humidity data with a maximal overlap discrete wavelet transform (MODWT) function and subsequently inputted into the WRF model. The results suggested that the WRF model can reasonably estimate BTEX trends and variations based on high R2 values of 0.96, 0.95, and 0.98 for training, validation, and test data subsets, respectively. The carcinogenic (LTCR) and non-carcinogenic health risk (HI) assessment results indicated a definite carcinogenic risk of benzene (LTCR = 2.22 × 10-4) and high non-carcinogenic risk (HI = 4.51) of BTEX emissions. The results of this study point to the importance of BTEX accumulation in poorly ventilated areas and the utility of machine learning in forecasting air pollution in diverse airsheds such as parking garages.

Bidirectional association between COVID-19 and the environment: A systematic review.

The global crisis caused by SARS-CoV-2 (COVID-19) affected economics, social affairs, and the environment, not to mention public health. It is estimated that near 82% of the SARS-CoV-2 genome is similar to the severe acute respiratory syndrome. The purpose of the review is to highlight how the virus is impacted by the environment and how the virus has impacted the environment. This review was based on an electronic search of the literature in the Scopus, Science Direct, and PubMed database published from December 2019 to July 2020 using combinations of the following keywords: SARS-CoV-2 transmission, COVID-19 transmission, coronavirus transmission, waterborne, wastewater, airborne, solid waste, fomites, and fecal-oral transmission. Studies suggest the thermal properties of ambient air, as well as relative humidity, may affect the transmissibility and viability of the virus. Samples taken from the wastewater collection network were detected contaminated with the novel coronavirus; consequently, there is a concern of its transmission via an urban sewer system. There are concerns about the efficacy of the wastewater treatment plant disinfection process as the last chance to inactivate the virus. Handling solid waste also requires an utmost caution as it may contain infectious masks, etc. Following the PRISMA approach, among all reviewed studies, more than 36% of them were directly or indirectly related to the indoor and outdoor environment, 16% to meteorological factors, 11% to wastewater, 14% to fomites, 8% to water, 9% to solid waste, and 6% to the secondary environment. The still growing body of literature on COVID-19 and air, suggests the importance of SARS-CoV-2 transmission via air and indoor air quality, especially during lockdown interventions. Environmental conditions are found to be a factor in transmitting the virus beyond geographical borders. Accordingly, countries need to pay extra attention to sustainable development themes and goals.

Novel magnetic graphene oxide functionalized cyanopropyl nanocomposite as an adsorbent for the removal of Pb(II) ions from aqueous media: equilibrium and kinetic studies.

This work presents the synthesis of the novel silica-cyanopropyl functionalized magnetic graphene oxide (MGO/SiO2-CN) hybrid nanomaterial derived by sol-gel method as a cheap efficient magnetic sorbent for the removal of extremely hazardous lead ions from aqueous media. The integration of the magnetic property, the carbon substrate, and the nitrile (-C ≡ N) containing organic grafted silica matrix promoted the adsorption capability against lead ions along with its simple synthesis recovery and low cost. The prepared nanocomposite was comprehensively characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. Adsorption of lead was found to be pH dependent because of the charged nature of both analyte and adsorbent surface. Adsorption experiments were conducted under the optimum conditions, and the obtained experimental data from atomic absorption spectroscopy were analyzed using the popular isothermal models namely Langmuir, Freundlich, and Dubinin-Radushkevich isotherms as well as kinetically studied and evaluated for adsorption standard free energy (E). The experimental results have demonstrated the enhanced adsorption capability of the proposed sorbent nanocomposite for lead ion removal with the maximum adsorption capacity of 111.11 mg/g at pH 5.0. The proposed mechanism of lead adsorption was mainly attributed to the complexation of lead positive ions with the grafted -C ≡ N bond. The synergistic effect of the combination of three components (i.e., the magnetic graphene oxide matrix, the triple bond containing organic moiety, and the inorganic porous silica framework) excelled the adsorption capability and proved to be a good candidate as adsorbent for the removal of lead ions.