Substantial Seasonal Contribution of Observed Biogenic Sulfate Particles to Cloud Condensation Nuclei View Full Text


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Article Info

DATE

2018-02-19

AUTHORS

Kevin J. Sanchez, Chia-Li Chen, Lynn M. Russell, Raghu Betha, Jun Liu, Derek J. Price, Paola Massoli, Luke D. Ziemba, Ewan C. Crosbie, Richard H. Moore, Markus Müller, Sven A. Schiller, Armin Wisthaler, Alex K. Y. Lee, Patricia K. Quinn, Timothy S. Bates, Jack Porter, Thomas G. Bell, Eric S. Saltzman, Robert D. Vaillancourt, Mike J. Behrenfeld

ABSTRACT

Biogenic sources contribute to cloud condensation nuclei (CCN) in the clean marine atmosphere, but few measurements exist to constrain climate model simulations of their importance. The chemical composition of individual atmospheric aerosol particles showed two types of sulfate-containing particles in clean marine air masses in addition to mass-based Estimated Salt particles. Both types of sulfate particles lack combustion tracers and correlate, for some conditions, to atmospheric or seawater dimethyl sulfide (DMS) concentrations, which means their source was largely biogenic. The first type is identified as New Sulfate because their large sulfate mass fraction (63% sulfate) and association with entrainment conditions means they could have formed by nucleation in the free troposphere. The second type is Added Sulfate particles (38% sulfate), because they are preexisting particles onto which additional sulfate condensed. New Sulfate particles accounted for 31% (7 cm-3) and 33% (36 cm-3) CCN at 0.1% supersaturation in late-autumn and late-spring, respectively, whereas sea spray provided 55% (13 cm-3) in late-autumn but only 4% (4 cm-3) in late-spring. Our results show a clear seasonal difference in the marine CCN budget, which illustrates how important phytoplankton-produced DMS emissions are for CCN in the North Atlantic. More... »

PAGES

3235

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41598-018-21590-9

    DOI

    http://dx.doi.org/10.1038/s41598-018-21590-9

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1101020026

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/29459666


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