Satellite observations have transformed our ability to monitor atmospheric composition, air quality, and climate change from regional to global scales. Recent advances in polar-orbiting sensors and geostationary platforms have enabled unprecedented observations of aerosols, reactive trace gases, and greenhouse gases with increasing spatial, temporal, and spectral resolution. These systems provide new opportunities to resolve diurnal variability, extreme events, and transboundary pollution processes, reshaping how atmospheric composition is observed and applied in health research.

Artificial intelligence (AI) has further transformed how these observations are integrated and applied, enabling the fusion of satellite data with ground-based measurements and chemical transport models to generate high-resolution, gap-free datasets. These advances support near-real-time monitoring and forecasting, improve the characterization of atmospheric composition, and facilitate the assessment of air pollution exposure, radiative forcing, emission sources, and health impacts.

This session invites contributions that advance our understanding of atmospheric composition, air quality, and health using satellite observations.

• GH - GeoHealth