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Tracking Urban Atmospheric Pollutants using Sentinel-5P Satellite Data

arXiv:2606.02592v1 Announce Type: cross Abstract: Urban nitrogen dioxide (NO_2) is a key indicator of combustion-related air pollution and exhibits strong spatial and temporal variability in cities. T

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arXiv:2606.02592v1 Announce Type: cross Abstract: Urban nitrogen dioxide (NO_2) is a key indicator of combustion-related air pollution and exhibits strong spatial and temporal variability in cities. This study presents a satellite-based framework for tracking urban NO_2 pollution using tropospheric column observations from Sentinel-5P/TROPOMI over Guayas Province, Ecuador. Rather than estimating surface concentrations, the methodology emphasizes robust distributional metrics, including the median and upper-tail percentiles (P_{90}, P_{95}, and P_{99}), to characterize background conditions and localized pollution extremes at the canton scale. Multi-year satellite observations are aggregated annually and analyzed using unsupervised K-means clustering to identify characteristic pollution regimes without predefined thresholds. Results show that highly urbanized cantons consistently exhibit elevated extreme NO_2 values and greater variability, while less urbanized areas display lower and more homogeneous patterns. The proposed approach provides an interpretable and scalable tool for urban air-quality assessment in data-scarce regions using satellite observations alone. The implementation is publicly available on GitHub https://hvelesaca.github.io/sentinel-5P-clustering/.

Source: arXiv cs.AI | 2026-06-03

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