Chemical degradation-based methods including oxidation have shown great promise for controlling benzene, toluene, ethylbenzeneandxylene isomers (BTEX) in waste gas. This study presents an approach in which the emission of BTEX compounds in a bituminous waterproofing (BW) production unit located in the city of Delijan, Iran has been controlled through process modification. The process is modified by introducing a thermal oxidation unit using an incinerator design. The process simulation has been performed with Aspen Hysys software and, key parameters in the oxidation process are identifiedandoptimized. Finally, the environmentalandeconomic performances of the incinerator were assessed to provide a decision support tool for the selection of this approach. Finally, the environmentalandeconomic performances of the incinerator have been assessed to provide a decision support tool for the selection of this approach. The results indicated that the formation of the oxidation unit had prevented the release of BTEX pollutants up to 98.5%. Moreover, the economic analysis illustrated that the rate of return on investment in the proposed project is 0.27. Thus, the potential for attracting capital will have positive impacts on the environmentalandeconomic indicators of the region.

In this study, a multitude of statistical tools were used to examine PM10 concentration trends and their seasonal behavior from 2015 to 2021 in Tehran. The results of the integrated analysis have led to a better understanding of current PM10 trends which may be useful for future management policies. The Kruskal – Wallis test indicated the significant impact of atmospheric phenomena on the seasonal fluctuations of PM10. The seasonal decomposition of PM10 time series was conducted for better analysis of trends and seasonal oscillations. The seasonal Mann-Kendall test illustrated the significant possibility of a monotonic seasonal trend of PM10 (p = 0.026) while showing its negative slope simultaneously (Sen = -1.496). The forecasting procedure of PM10 until 2024 comprised 15 time series models which were validated by means of 8 statistical criteria. The model validation results indicated that ARIMA (0,1,2) was the most satisfactory case for predicting the future trend of PM10. This model estimated the concentration of PM10 to reach approximately 79.04 (µg/m3) by the end of 2023 with a 95% confidence interval of 51.38 – 107.42 (µg/m3). Overall, it was concluded that the use of the aforementioned analytical tools may help decision-makers gain a better insight into future forecasts of ambient airborne particulate matter.

This research aims to investigate the effect of virtual education during the COVID-19 outbreak on air pollution indicators in Tehran. The study uses quantitative methods, including One-Way ANOVA, to analyze the air pollution indicators before and during the COVID-19 pandemic. Data on air pollution indicators in Tehran from 2018, 2019, and 2020 were collected from Tehran Air Control Company and compared using statistical tests. The year 2019 represents virtual education, while 2018 and 2020 represent face-to-face education. The examined indicators include particulate matters with a diameter less or equal than 2.5μ (PM2.5), SO2, NOX (i.e., NO2 and NO), O3, and CO. The results of variance analysis show significant differences in the PM2.5and NOX indices between virtual and face-to-face training days. Follow-up tests by Toki and Scheffé indicate that in 2019, when education was fully virtual, the levels of these pollutants were lower compared to 2018 and 2020. However, there were no significant differences in the SO2, O3, and CO indices during the days of virtual education compared to the years before and after. This suggests that virtual education during the COVID-19 outbreak contributed to pollution reduction by reducing traffic to educational organizations and its indirect effects.