Importance of mixing state for modeling aerosol impacts

Poster PDF

Description

Individual aerosol particles are a complex mixture of a wide variety of species, such as soluble inorganic salts and acids, insoluble crustal materials, trace metals, and carbonaceous materials, requiring a high-dimensional representation in models. The capabilities of traditional models to treat this high dimensionality are currently very limited, and this introduces serious shortcomings in our understanding of chemical reactivity, cloud condensation nuclei activity, radiative properties, and health impacts of aerosol particles. In contrast, the stochastic particle-resolved model PartMC-MOSAIC explicitly resolves the composition of individual particles in a given population of different types of aerosol particles. This approach tracks the evolution of the aerosol mixing state owing to emission, dilution, condensation, and coagulation. This model framework fills several crucial gaps in the way atmospheric aerosol particles are modeled: (1) It improves the theoretical understanding of aerosol mixing state representations, (2) it serves as a benchmark regarding mixing state for more approximate models, (3) it provides a way to estimate parameters needed by larger-scale models. Here we will show evaluations of the importance of mixing state on different climate-relevant aerosol properties based on particle-resolved model simulations. We will discuss the role of aerosol aging in this context.