Articles | Volume 20, issue 13
https://doi.org/10.5194/acp-20-7693-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-7693-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Jul 2020
Research article |
| 02 Jul 2020
| 02 Jul 2020
Deconvolution of FIGAERO–CIMS thermal desorption profiles using positive matrix factorisation to identify chemical and physical processes during particle evaporation
Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
Arttu Ylisirniö
Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
Wei Huang
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
Claudia Mohr
Department of Environmental Science and Analytical Chemistry,
Stockholm University, Stockholm, Sweden
Manjula Canagaratna
Aerodyne Research Inc., Billerica, MA 08121, USA
Douglas R. Worsnop
Aerodyne Research Inc., Billerica, MA 08121, USA
Siegfried Schobesberger
Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
Annele Virtanen
Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
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- A Coupled Volatility and Molecular Composition Based Source Apportionment of Atmospheric Organic Aerosol P. Rund et al. 10.1021/acsearthspacechem.3c00034
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- Volatility of Secondary Organic Aerosol from β-Caryophyllene Ozonolysis over a Wide Tropospheric Temperature Range L. Gao et al. 10.1021/acs.est.3c01151
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Latest update: 24 May 2025
Short summary
To understand the role of aerosol particles in the atmosphere, it is necessary to know their detailed chemical composition and physical properties, especially volatility. The thermal desorption data from FIGAERO–CIMS provides both but are difficult to analyse. With positive matrix factorisation, we can separate instrument background from the real signal. Compounds can be classified by their apparent volatility, and the contribution of thermal decomposition in the instrument can be identified.
To understand the role of aerosol particles in the atmosphere, it is necessary to know their...
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