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 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 high computational efficiency for situations when the coagulation kernel is highly nonuniform, 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 contributed 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 sectional or modal aerosol models.
ASJC Scopus subject areas
- Condensed Matter Physics
- Materials Chemistry
- Polymers and Plastics
- Physical and Theoretical Chemistry