Time series analysis and spatial distribution map of aggregate risk index due to tropospheric NO₂ and O₃ based on...

A high increase in human activities has led to more emission of air pollutants in metropolises and industrial areas. Recently, remotely sensed data of tropospheric pollutants is used for environmental management and decision-making on large scale. The purpose of this study was a time series analysis of nitrogen dioxide Vertical Column Density (NO₂ VCD) and Ozone (O₃) using Ozone Monitoring Instrument (OMI) from 2005 to 2016 by Mann-Kendall test. Also, the aggregate risk index (ARI) was calculated to estimate the overall impact of exposure to tropospheric NO₂ and O₃ concentrations at the national scale in 2016. To estimate the surface NO₂ related drivers, The Radial Basis Function (RBF) neural network modeling was performed for different months of 2016. Results of Mann-Kendall test showed that tropospheric ozone concentration had an increasing trend in all parts of Iran and this increasing trend was significantly higher in the southern region of Iran and lower in the northern parts of Iran. NO₂ VCD in most parts of Iran had a significant increasing trend. The result of sensitivity analysis showed that NO₂ VCD (1.25), the distance to the industrial area, (1.20) and wind speed (1.07) were the most important variables for the estimation of surface NO₂ concentration. Spatial ARI with the highest risks is mainly located in the Northern half of Iran, especially in Tehran, Alborz, and Khorasan-e- Razavi provinces, where NO₂ and O₃ concentrations are very severe. In northern Iran and central cities, the ARI values are calculated from 1.5 to 2.08, indicating the highest human health risks in these regions. The human health risks based on OMI observation were obtained higher in comparison to AQM data because the satellite data coverage is larger than AQM station and monitors transmitted air pollution by the wind in addition to local pollution. Based on this research, using satellite observation for air quality monitoring is a suitable tool for environmental management on a national scale.