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New particle formation from sulfuric acid and ammonia: nucleation and growth model based on thermodynamics derived from CLOUD measurements for a wide range of conditions

  • Understanding new particle formation and growth is important because of the strong impact of these processes on climate and air quality. Measurements to elucidate the main new particle formation mechanisms are essential; however, these mechanisms have to be implemented in models to estimate their impact on the regional and global scale. Parameterizations are computationally cheap ways of implementing nucleation schemes in models but they have their limitations, as they do not necessarily include all relevant parameters. Process models using sophisticated nucleation schemes can be useful for the generation of look-up tables in large scale models or for the analysis of individual new particle formation events. In addition, some other important properties can be derived from a process model that implicitly calculates the evolution of the full aerosol size distribution, e.g., the particle growth rates. Within this study, a model (SANTIAGO, Sulfuric acid Ammonia NucleaTIon And GrOwth model) is constructed that simulates new particle formation starting from the monomer of sulfuric acid up to a particle size of several hundred nanometers. The smallest sulfuric acid clusters containing one to four acid molecules and varying amount of base (ammonia) are allowed to evaporate in the model, whereas growth beyond the pentamer (5 sulfuric acid molecules) is assumed to be entirely collision-controlled. The main goal of the present study is to derive appropriate thermodynamic data needed to calculate the cluster evaporation rates as a function of temperature. These data are derived numerically from CLOUD (Cosmics Leaving OUtdoor Droplets) chamber new particle formation rates for neutral sulfuric acid-water-ammonia nucleation at temperatures between 208 K and 292 K. The numeric methods include an optimization scheme to derive the best estimates for the thermodynamic data (dH and dS) and a Monte Carlo method to derive their probability density functions. The derived data are compared to literature values. Using different data sets for dH and dS in SANTIAGO detailed comparison between model results and measured CLOUD new particle formation rates is discussed.

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Metadaten
Verfasserangaben:Christoph Andreas KürtenORCiDGND
URN:urn:nbn:de:hebis:30:3-510766
DOI:https://doi.org/10.5194/acp-2018-1323
ISSN:1680-7375
ISSN:1680-7367
Titel des übergeordneten Werkes (Englisch):Atmospheric chemistry and physics. Discussions
Verlag:EGU
Verlagsort:Katlenburg-Lindau
Dokumentart:Wissenschaftlicher Artikel
Sprache:Englisch
Jahr der Fertigstellung:2019
Datum der Erstveröffentlichung:29.01.2019
Veröffentlichende Institution:Universitätsbibliothek Johann Christian Senckenberg
Datum der Freischaltung:16.09.2019
Jahrgang:18
Seitenzahl:32
Erste Seite:1
Letzte Seite:32
Bemerkung:
© Author(s) 2019. CC BY 4.0 License.
HeBIS-PPN:454033540
Institute:Geowissenschaften / Geographie / Geowissenschaften
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Sammlungen:Universitätspublikationen
Open-Access-Publikationsfonds:Geowissenschaften / Geographie
Lizenz (Deutsch):License LogoCreative Commons - Namensnennung 4.0