Tracking Urban Atmospheric Pollutants using Sentinel-5P Satellite Data
Researchers have developed a satellite-based method to track urban nitrogen dioxide pollution using data from the Sentinel-5P satellite. This framework focuses on distributional metrics like median and upper-tail percentiles to characterize pollution patterns and localized extremes at the canton level in Ecuador. By employing unsupervised K-means clustering on multi-year observations, the study identified distinct pollution regimes, revealing that highly urbanized areas consistently show elevated extreme NO2 values and greater variability compared to less urbanized regions. The approach offers a scalable tool for air quality assessment in data-scarce areas, with the implementation available on GitHub. AI
IMPACT Provides a novel, scalable method for air quality assessment in data-scarce regions using satellite observations.