Characterizing the Sources of Cloud Condensation Nuclei Using a Global Aerosol Modeling Appoach

Atmospheric aerosols exert an indirect cooling effect on climate by brightening clouds (Twomey effect) or extending cloud lifetime (Albrecht effect). Cloud condensation nuclei, or CCN, are aerosol particles that are responsible for forming clouds, and their sources are currently uncertain and not well characterized. We know that primary (emissions) and secondary (nucleation) sources contribute to CCN but to what extent is still an open question. The present work aims to elucidate the sources of CCN in order to reduce uncertainty in the aerosol indirect effect by using global aerosol microphysics models. Global aerosol microphsyiscs models, such as GISS-TOMAS and GEOS-Chem-TOMAS, are three dimensional dynamic models of the atmosphere that focus on the evolution of the aerosol number and mass size distribution through time. The aerosol algorithm, TwO-Moment Aerosol Sectional microphysics code (TOMAS), solves the general dynamic equation to calculate the effect of condensation, coagulation, and nucleation on the aerosol population. We use this model to answer several interesting questions about the sources of CCN. We find that primary marine organic aerosol does not likely play a significant role (less than 5% global and regional impact) on forming CCN. We also find that although nucleation itself can enhance CCN by 40% or more, the differences between very slow and very fast nucleation rates is not as important. Instead, the condensation growth rates seem to control CCN concentrations to a greater degree. We test and validate the ability of TOMAS to predict nucleation in a global aerosol model and find that on average it is accurate to within 50% bias. Finally, we develop, implement, and test an aerosol source apportionment algorithm in TOMAS in order to make more robust conlusions about the sources of CCN in the global atmosphere.