  The mixing state of soot particles in the atmosphere is of crucial importance
for assessing their climatic impact, since it governs their chemical
reactivity, cloud condensation nuclei activity and radiative properties. To
improve the mixing state representation in models, we present a new approach,
the stochastic particle-resolved model PartMC-MOSAIC, which explicitly resolves
the composition of individual particles in a given population of different
types of aerosol particles. This approach accurately tracks the evolution of
the mixing state of particles due to emission, dilution, condensation and
coagulation. To make this direct stochastic particle-based method practical, we
implemented a new multiscale stochastic coagulation method. With this method we
achieved optimal efficiency for applications when the coagulation kernel is
highly non-uniform, as is the case for many realistic applications.
PartMC-MOSAIC was applied to an idealized urban plume case representative of a
large urban area to simulate the evolution of carbonaceous aerosols of
different types due to coagulation and condensation. For this urban plume
scenario we quantified the individual processes that contribute to the aging of
the aerosol distribution, illustrating the capabilities of our modeling
approach. The results showed for the first time the multidimensional structure
of particle composition, which is usually lost in internally-mixed sectional or
modal aerosol models.
