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Does the POA-SOA split matter for global CCN formation?

DOI: 10.5194/acpd-13-10561-2013

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Abstract:

A model of carbonaceous aerosols has been implemented into the TwO-Moment Aerosol Sectional (TOMAS) microphysics module in the GEOS-Chem CTM, a model driven by assimilated meteorology. Inclusion of carbonaceous emissions alongside pre-existing treatments of sulfate and sea-salt aerosols increases the number of emitted primary aerosol particles by a factor of 2.5 and raises annual-average global CCN(0.2%) concentrations by a factor of two. Compared to the prior model without carbonaceous aerosols, this development improves the model prediction of CN10 number concentrations significantly from 45 to 7% bias when compared to long-term observations. However, similar to other OC/EC models, the model underpredicts OC and EC mass concentrations by a factor of 2–5 when compared to EMEP observations. Because primary OA and secondary OA affect aerosol number size distributions differently, we assess the sensitivity of CCN production, for a fixed source of OA mass, to the assumed POA-SOA split in the model. For a fixed OA budget, we found that CCN(0.2%) decreases nearly everywhere as the model changes from a world dominated by POA emissions to one dominated by SOA condensation. POA is about twice as effective per unit mass at CCN production compared to SOA. Changing from a 100% POA scenario to a 100% SOA scenario, CCN(0.2%) concentrations in the lowest model layer decrease by about 20%. In any scenario, carbonaceous aerosols contribute significantly to global CCN. The SOA-POA split has a significant effect on global CCN and the microphysical implications of POA emissions versus SOA condensation appear to be at least as important as differences in chemical composition as expressed by the hygroscopicity of OA. These findings stress the need to better understand carbonaceous aerosols loadings, the global SOA budget, microphysical pathways of OA formation (emissions versus condensation) as well as chemical composition to improve climate modeling.

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