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MICE-TRAPS: Nanoparticles as a sensitive probe for studying the properties of atmospheric vapors

Duft, Denis ORCID iD icon; Nachbar, Mario; Dresch, Thomas; Leisner, Thomas ORCID iD icon

Abstract (englisch):

Time-of-Flight mass spectrometry (TOF-MS) is an established experimental technique used in a wide range of scientific fields and industrial processes. One of many reasons contributing to the success of this technique lies in the fact that very high (atomic) resolution can be achieved while maintaining a high signal-to-noise ratio. We employ this technique in our experimental setup, which consists of the Molecular flow Ice Cell (MICE) within the Trapped Reactive Atmospheric Particle Spectrometer (TRAPS) while studying the nucleation and condensation of condensable vapors on atmospheric aerosol nanoparticles. The TOF-MS enables us to investigate nucleation and condensation processes at extreme atmospheric conditions where typical experimental methods fail. The nanoparticles are trapped in MICE and are used as a probe for the properties of the condensable vapors under investigation, e.g. the low initial mass of the nanoparticles of roughly 20kDa enables us to identify the adsorption of a few hundred molecules on the particle surface (i.e. only a few molecules per minute). In this contribution we present the experimental setup in detail together with results on desorption energy, critical saturation for nucleation, contact parameter, saturation vapor pressure or sticking coefficient and light absorption coefficient of Water and CO2 in the higher atmospheres of Earth and Mars.

Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Atmosphärische Aerosolforschung (IMKAAF)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Poster
Publikationsdatum 18.09.2017
Sprache Englisch
Identifikator KITopen-ID: 1000076442
HGF-Programm 12.04.02 (POF III, LK 01) Cirrus Clouds
Veranstaltung 13th International Workshop on Layered Phenomena in the Mesopause Region (LPMR) , Kühlungsborng, 18. - 22. September 2017
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