Atmospheric aerosols are complex mixtures of different chemical species, and individual particles exist in many different shapes and morphologies. These characteristics contribute to the aerosol mixing state, which continuously evolves in the atmosphere. Atmospheric models have become sufficiently complex to incorporate aspects of aerosol mixing state in their predictions. Concurrently, sophisticated measurement techniques have been developed to probe various physicochemical properties of particles. However, there is no single instrument that can characterize all aspects of aerosol mixing state, and it has proven challenging to quantitatively compare measured mixing state attributes with mixing state predictions.
This talk will present a framework to synthesize a picture of the ambient aerosol from models and observations. We will focus on suitable metrics to quantify mixing state, sampling strategies to determine these metrics that are accessible for both models and observations, and modeling strategies to scale up detailed modeling results on the particle scale to global predictions of mixing state.
