|Title||Evaluation of aerosol mixing state classes in the GISS model E-MATRIX climate model using single-particle mass spectrometry measurements|
|Publication Type||Journal Article|
|Year of Publication||2013|
|Authors||Bauer S.E, Ault A., Prather KA|
|Journal||Journal of Geophysical Research-Atmospheres|
|Type of Article||Article|
|Keywords||chemistry; events; general-circulation model; los-angeles; matter; mixing state; nucleation; particulate; size distributions; sulfate aerosols; transport; variability|
Aerosol particles in the atmosphere are composed of multiple chemical species. The aerosol mixing state, which describes how chemical species are mixed at the single-particle level, provides critical information on microphysical characteristics that determine the interaction of aerosols with the climate system. The evaluation of mixing state has become the next challenge. This study uses aerosol time-of-flight mass spectrometry (ATOFMS) data and compares the results to those of the Goddard Institute for Space Studies model E-MATRIX (Multiconfiguration Aerosol TRacker of mIXing state) model, a global climate model that includes a detailed aerosol microphysical scheme. We use data from field campaigns that examine a variety of air mass regimens (urban, rural, and maritime). At all locations, polluted areas in California (Riverside, La Jolla, and Long Beach), a remote location in the Sierra Nevada Mountains (Sugar Pine) and observations from Jeju (South Korea), the majority of aerosol species are internally mixed. Coarse aerosol particles, those above 1 mu m, are typically aged, such as coated dust or reacted sea-salt particles. Particles below 1 mu m contain large fractions of organic material, internally mixed with sulfate and black carbon, and few external mixtures. We conclude that observations taken over multiple weeks characterize typical air mass types at a given location well; however, due to the instrumentation, we could not evaluate mass budgets. These results represent the first detailed comparison of single-particle mixing states in a global climate model with real-time single-particle mass spectrometry data, an important step in improving the representation of mixing state in global climate models.