A 3D Particle-resolved Model to Quantify the Importance of Aerosol Mixing State for CCN Properties

Jeffrey Curtis University of Illinois, Urbana
Nicole Riemer University of Illinois, Urbana
Matthew West University of Illinois at Urbana-Champaign

Category: Aerosol Mixing State

We present a 3D particle-resolved aerosol model to investigate the importance of aerosol mixing state in regional models. Understanding the aerosol mixing state impact on aerosol physical and optical properties and its temporal and spatial evolution is currently an open research question. Due to computational constraints, representing aerosol composition in numerical models has been a challenge, and as a result, both modal and sectional representations overly simplify the aerosol mixing state. This leads to uncertainties and errors in physical quantities that are not well understood. To address this, we coupled the Weather Research and Forecast (WRF) model and the particle-resolving aerosol physics and chemistry model PartMC-MOSAIC. The new model explicitly resolves and tracks the size and composition of individual particles as they undergo transformations by coagulation and condensation in the atmosphere and simulates stochastic particle transport between grid cells using velocity and turbulent mixing fields provided by the WRF model. We apply this model to an idealized 3D scenario to show how the aerosol mixing state of a spatially-resolved and particle-resolved plume evolves over time. We compare CCN concentrations of particle-resolved simulations to a composition-averaged simulation. To quantify the importance of mixing state on CCN properties, we present the differences in CCN concentrations between the two representations as a function of mixing state parameter χ.

This poster will be displayed at ASR Science Team Meeting.