ACP Atmospheric Chemistry and Physics ACP 1680-7324 Copernicus GmbH Göttingen, Germany 10.5194/acp-13-1913-2013 Evaluation of factors controlling global secondary organic aerosol production from cloud processes He C. 1 4 Liu J. 1 Carlton A. G. 2 Fan S. 3 Horowitz L. W. 3 Levy II H. 3 Tao S. 1 College of Urban and Environmental Sciences, Peking University, Beijing, China Department of Environmental Sciences, Rutgers University, New Brunswick, NJ, USA Geophysical Fluid Dynamics Laboratory (GFDL), Princeton, NJ, USA now at: Department of Atmospheric and Oceanic Sciences, University of California at Los Angeles (UCLA), Los Angeles, CA, USA 19 02 2013 13 4 1913 1926 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/13/1913/2013/acp-13-1913-2013.html The full text article is available as a PDF file from http://www.atmos-chem-phys.net/13/1913/2013/acp-13-1913-2013.pdf

Secondary organic aerosols (SOA) exert a significant influence on ambient air quality and regional climate. Recent field, laboratorial and modeling studies have confirmed that in-cloud processes contribute to a large fraction of SOA production with large space-time heterogeneity. This study evaluates the key factors that govern the production of cloud-process SOA (SOA<sub>cld</sub>) on a global scale based on the GFDL coupled chemistry-climate model AM3 in which full cloud chemistry is employed. The association between SOA<sub>cld</sub> production rate and six factors (i.e., liquid water content (LWC), total carbon chemical loss rate (TC<sub>loss</sub>), temperature, VOC/NO<sub>x</sub>, OH, and O<sub>3</sub>) is examined. We find that LWC alone determines the spatial pattern of SOA<sub>cld</sub> production, particularly over the tropical, subtropical and temperate forest regions, and is strongly correlated with SOA<sub>cld</sub> production. TC<sub>loss</sub> ranks the second and mainly represents the seasonal variability of vegetation growth. Other individual factors are essentially uncorrelated spatiotemporally to SOA<sub>cld</sub> production. We find that the rate of SOA<sub>cld</sub> production is simultaneously determined by both LWC and TC<sub>loss</sub>, but responds linearly to LWC and nonlinearly (or concavely) to TC<sub>loss</sub>. A parameterization based on LWC and TC<sub>loss</sub> can capture well the spatial and temporal variability of the process-based SOA<sub>cld</sub> formation (<i>R</i><sup>2</sup> = 0.5) and can be easily applied to global three dimensional models to represent the SOA production from cloud processes.

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