<p>The high rate of urbanization, vegetation destruction, and high vehicle congestion in Tehran Metropolitan Area, Iran are speeding up the accumulation rate of air pollutants. Although several studies on air pollution, a comprehensive study on daily temporal and clustering pattern in urban districts’ pollutants for sustainability remains missing. We aim to fill this research gap by analyzing pollutants in place and time in the urban districts of Tehran. This study’s novelty lies in its approach to understanding of the air pollution dynamics using Sentinel-5P satellite data and the application of advanced spatial statistical techniques. Using coding in the GEE environment, concentrations of 2022 pollutants such as CO, NO₂, SO₂, O₃, and AI (aerosol index) were extracted from the satellite. For the first time, the daily temporal patterns of the main pollutants in Tehran were examined to identify the causes of one of the most polluted years. High values of CO and NO₂ prevail in the first and last quarters of the year due to increased traffic as schools reopen. In addition, Moran’s I associated with global autocorrelation analysis from all pollutant values was above 0.9, indicating a cluster-like spatial distribution pattern. The LISA analysis identified the locations of clustering pollutants at urban area level. Of all the pollutants studied in Tehran, particulate matter had the highest number of clusters, 282 HH clusters, amounting to a total of 483. A knowledge of these hotspots of pollution and the potential sources of emissions will capable urban planners in taking appropriate actions.</p> Graphical Abstract <p></p>