AAAR 34th Annual Conference
October 12 - October 16, 2015
Hyatt Regency
Minneapolis, Minnesota, USA
Abstract View
A 3D Particle-resolved Model to Quantify the Importance of Black Carbon Mixing State for CCN Properties
JEFFREY H. CURTIS, Nicole Riemer, Matthew West, University of Illinois at Urbana-Champaign
Abstract Number: 515 Working Group: Carbonaceous Aerosols in the Atmosphere
Abstract Field observations show that black carbon is mixed with other aerosol species on an individual particle level. These mixtures evolve in the atmosphere as a result of aerosol aging processes, which impacts the black carbon optical properties and CCN activation properties, and hence the black carbon climate impact. To deal with such high-dimensional and multi-scale data, aerosol models have traditionally made simplifying assumptions regarding the particle composition. While this makes computation much cheaper, it introduces errors, since it artificially averages the composition of individual particles over a certain size range.
Recently, particle-resolved aerosol models have been introduced to avoid making a priori assumptions about the evolution of particle composition. These stochastic models simulate a representative group of particles distributed in composition space, treating coagulation, condensation/ evaporation, and other important processes on an individual particle level. Here we show the first simulation of the particle-resolving aerosol physics and chemistry model PartMC-MOSAIC, fully coupled to the Weather Research and Forecast model (WRF). We apply this model to investigate the aging of black carbon particles in a plume, where aerosol microphysics and chemistry interact with transport.
To quantify the importance of black carbon mixing state on CCN properties, differences in CCN concentrations between particle-resolved and composition-averaged simulations are evaluated as a function of mixing state parameter chi, which is a metric to characterize the degree of internal mixing of the aerosol population. It varied from 50% internally mixed near the emission sources to 100% downwind of the plume. For chi values larger than 90%, composition-averaging introduced only small errors in CCN concentrations. For chi lower than 60% the CCN concentrations were overestimated by as much as 90%.