English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Quantitative single-particle analysis with the Aerodyne aerosol mass spectrometer: development of a new classification algorithm and its application to field data

MPS-Authors
/persons/resource/persons100940

Freutel,  F.
Particle Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons100914

Drewnick,  F.
Particle Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons101255

Schneider,  J.
Particle Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons101066

Klimach,  T.
Particle Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons100858

Borrmann,  S.
Particle Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Freutel, F., Drewnick, F., Schneider, J., Klimach, T., & Borrmann, S. (2013). Quantitative single-particle analysis with the Aerodyne aerosol mass spectrometer: development of a new classification algorithm and its application to field data. Atmospheric Measurement Techniques, 6(11), 3131-3145.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0015-892B-C
Abstract
Single-particle mass spectrometry has proven a valuable tool for gaining information on the mixing state of aerosol particles. With the Aerodyne aerosol mass spectrometer (AMS) equipped with a light-scattering probe, nonrefractory components of submicron particles with diameters larger than about 300 nm can even be quantified on a single-particle basis. Here, we present a new method for the analysis of AMS single-particle mass spectra. The developed algorithm classifies the particles according to their components (e. g. sulphate, nitrate, different types of organics) and simultaneously provides quantitative information about the composition of the single particles. This classification algorithm was validated by applying it to data acquired in laboratory experiments with particles of known composition, and applied to field data acquired during the MEGAPOLI summer campaign (July 2009) in Paris. As shown, it is not only possible to directly measure the mixing state of atmospheric particles, but also to directly observe repartitioning of semi-volatile species between gas and particle phase during the course of the day.