Spatiotemporal Analysis of NO2 Production Using TROPOMI Time-Series Images and Google Earth Engine in a Middle Eastern Country

Like many developing countries, Iran faces air pollution, especially in its metropolises and industrial cities. Nitrogen dioxide (NO2) is one of the significant pollutants; therefore, this study aims to investigate spatiotemporal variability NO2 using Tropospheric Monitoring Instrument (TROPOMI) sensor mounted on Sentinel-5P (S5P) satellite Google Earth Engine (GEE) platform over Iran. In addition, we used ground truth data assess correlation between acquired by stations. The results show that there a strong products TROPOMI provided Air Quality Organization also display coefficient (R) varies range 0.4 0.92, three years. Over an annual period (2018 2021) wide area, these can become valuable points reference for monitoring. proved tropospheric concentrations are generally located northern part According time season, concentration column shows higher values during winter than summertime. while some southern central parts country more be seen This indicates urban areas highly polluted, which proves impact pollutants such as people living there. other words, small classified high very polluted areas, but primary location pollution We provide code repository allows analysis estimation time-series images within GEE. method applied regions interest mapping.