ACP Atmospheric Chemistry and Physics ACP 1680-7324 Copernicus GmbH Göttingen, Germany 10.5194/acp-10-4033-2010 A detailed aerosol mixing state model for investigating interactions between mixing state, semivolatile partitioning, and coagulation Lu J. 1 3 Bowman F. M. 2 Department of Chemical Engineering, Vanderbilt University, Nashville, Tennessee, USA Department of Chemical Engineering, University of North Dakota, Grand Forks, North Dakota, USA now at: Planning and Technical Support Division, California Air Resources Board, Sacramento, California, USA 29 04 2010 10 8 4033 4046 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.atmos-chem-phys.net/10/4033/2010/acp-10-4033-2010.html The full text article is available as a PDF file from http://www.atmos-chem-phys.net/10/4033/2010/acp-10-4033-2010.pdf

A new method for describing externally mixed particles, the Detailed Aerosol Mixing State (DAMS) representation, is presented in this study. This novel method classifies aerosols by both composition and size, using a user-specified mixing criterion to define boundaries between compositional populations. Interactions between aerosol mixing state, semivolatile partitioning, and coagulation are investigated with a Lagrangian box model that incorporates the DAMS approach. Model results predict that mixing state affects the amount and types of semivolatile organics that partition to available aerosol phases, causing external mixtures to produce a more size-varying composition than internal mixtures. Both coagulation and condensation contribute to the mixing of emitted particles, producing a collection of multiple compositionally distinct aerosol populations that exists somewhere between the extremes of a strictly external or internal mixture. The selection of mixing criteria has a significant impact on the size and type of individual populations that compose the modeled aerosol mixture. Computational demands for external mixture modeling are significant and can be controlled by limiting the number of aerosol populations used in the model.

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