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Titel Influence of crustal dust and sea spray supermicron particle concentrations and acidity on inorganic NO3− aerosol during the 2013 Southern Oxidant and Aerosol Study
VerfasserIn H. M. Allen, D. C. Draper, B. R. Ayres, A. Ault, A. Bondy, S. Takahama, R. L. Modini, K. Baumann, E. Edgerton, C. Knote, A. Laskin, B. Wang, J. L. Fry
Medientyp Artikel
Sprache Englisch
ISSN 1680-7316
Digitales Dokument URL
Erschienen In: Atmospheric Chemistry and Physics ; 15, no. 18 ; Nr. 15, no. 18 (2015-09-25), S.10669-10685
Datensatznummer 250120056
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/acp-15-10669-2015.pdf
 
Zusammenfassung
Inorganic aerosol composition was measured in the southeastern United States, a region that exhibits high aerosol mass loading during the summer, as part of the 2013 Southern Oxidant and Aerosol Study (SOAS) campaign. Measurements using a Monitor for AeRosols and GAses (MARGA) revealed two periods of high aerosol nitrate (NO3) concentrations during the campaign. These periods of high nitrate were correlated with increased concentrations of supermicron crustal and sea spray aerosol species, particularly Na+ and Ca2+, and with a shift towards aerosol with larger (1 to 2.5 μm) diameters. We suggest this nitrate aerosol forms by multiphase reactions of HNO3 and particles, reactions that are facilitated by transport of crustal dust and sea spray aerosol from a source within the United States. The observed high aerosol acidity prevents the formation of NH4NO3, the inorganic nitrogen species often dominant in fine-mode aerosol at higher pH. Calculation of the rate of the heterogeneous uptake of HNO3 on mineral aerosol supports the conclusion that aerosol NO3 is produced primarily by this process, and is likely limited by the availability of mineral cation-containing aerosol surface area. Modeling of NO3 and HNO3 by thermodynamic equilibrium models (ISORROPIA II and E-AIM) reveals the importance of including mineral cations in the southeastern United States to accurately balance ion species and predict gas–aerosol phase partitioning.
 
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