Aerosol mixing state is a fundamental yet still poorly constrained property governing aerosol optical effects, heterogeneous chemistry, hygroscopicity, cloud activation, atmospheric lifetime, and air quality impacts. It also has growing relevance for exposure assessment, particle toxicity, and environmental health. Rapid advances in single-particle observations, laboratory studies, remote sensing, and mixing-resolved modeling are improving our ability to characterize aerosol composition, morphology, aging, and heterogeneity across scales. At the same time, emerging AI and machine learning methods offer new opportunities for emulation, data fusion, and process inference. This session welcomes contributions that advance the observation, interpretation, and representation of aerosol mixing state from particle to regional and global scales, including applications to wildfire smoke, urban pollution, dust, sea salt, and secondary aerosols, as well as implications for climate, air quality, aerosol–cloud interactions, and health.

• GC - Global Environmental Change
• GH - GeoHealth
• IN - Informatics