Spatiotemporal Pattern Dynamics of Air Pollution in Ulaanbaatar Using Sentinel 5P Satellite Data

Abstract

Ulaanbaatar is characterized by severe air pollution during the winter season due to meteorological and geographical conditions such as frequent temperature inversions, low wind speeds, and its basin-shaped topography, which favors the accumulation of pollutants. In addition, emissions from household coal combustion, thermal power plants, and increasing vehicle traffic significantly affect the city’s air quality. Therefore, a comprehensive assessment of the spatial distribution and temporal variability of major air pollutants is essential for effective air quality management. In this study, Sentinel-5P (TROPOMI) satellite observations from the winter seasons (November–February) of 2018–2024 were used to evaluate the spatial distribution and temporal dynamics of nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), and the Absorbing Aerosol Index in Ulaanbaatar. Daily satellite products were processed using temporal averaging to generate monthly mean raster datasets. The spatial patterns of air pollutants were analyzed through spatial mapping and statistical methods, including boxplot analysis. The results indicate that NO₂, CO, and the Aerosol Index exhibit high concentrations in central urban districts, densely populated ger areas, around thermal power plants, and along major transportation corridors. In contrast, ozone (O₃) concentrations remain relatively low and stable during winter due to reduced photochemical activity. Furthermore, a temporary decrease in pollutant concentrations was observed during the COVID-19 lockdown period, followed by an increasing trend after economic activities resumed. This study demonstrates that satellite-based observations provide valuable information for developing spatial air pollution monitoring systems, identifying pollution hotspots, and supporting evidence-based urban air quality management and policy development in Ulaanbaatar.