Our quantitative understanding of the aerosol impact on climate still has large gaps and hence introduces large uncertainties in climate predictions. One of the challenges is the inherently multi-scale nature of the problem: the macro-scale impacts of aerosol particles are governed by processes that occur on the particle-scale, and these microscale processes are difficult to represent in large-scale models. An important quantity in this context is the so-called aerosol mixing state, which we define as the distribution of the aerosol chemical species over the population. It is not clear to what extent mixing state information needs to be represented in atmospheric aerosol models in order to capture aerosol impacts on climate. Progress on this question has been hampered by our lack of suitable metrics for aerosol mixing state, and suitable models that are able to resolve and simulate mixing state.

    In this seminar I will present a framework to quantify the aerosol mixing state impacts on climate. This includes a metric for aerosol mixing state, which is based on diversity measures derived from the information-theoretic entropy of the chemical species distribution among particles. I will also introduce a stochastic, particle-resolved modeling approach that is capable of tracking the evolution of the full aerosol mixing state. I will illustrate the usefulness of this approach by focusing on the aging process of black-carbon-containing particles.