Articles | Volume 14, issue 2
https://doi.org/10.5194/amt-14-923-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-923-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Feb 2021
Research article |
| 08 Feb 2021
| 08 Feb 2021
A new method for long-term source apportionment with time-dependent factor profiles and uncertainty assessment using SoFi Pro: application to 1 year of organic aerosol data
Francesco Canonaco
Datalystica Ltd., Park innovAARE, 5234 Villigen, Switzerland
Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, 5232 Villigen PSI, Switzerland
Anna Tobler
Datalystica Ltd., Park innovAARE, 5234 Villigen, Switzerland
Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, 5232 Villigen PSI, Switzerland
Gang Chen
Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, 5232 Villigen PSI, Switzerland
Yulia Sosedova
Datalystica Ltd., Park innovAARE, 5234 Villigen, Switzerland
Jay Gates Slowik
Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, 5232 Villigen PSI, Switzerland
Carlo Bozzetti
Datalystica Ltd., Park innovAARE, 5234 Villigen, Switzerland
Kaspar Rudolf Daellenbach
Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, 5232 Villigen PSI, Switzerland
Institute for Atmospheric and Earth System Research, Helsinki, Finland
Imad El Haddad
Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, 5232 Villigen PSI, Switzerland
Monica Crippa
European Commission, Joint Research Centre (JRC), Via Fermi, 2749, 21027 Ispra, Italy
Ru-Jin Huang
State Key Laboratory of Loess and Quaternary Geology, Center for Excellence in Quaternary Science and Global Change, and Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
Markus Furger
Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, 5232 Villigen PSI, Switzerland
Urs Baltensperger
Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, 5232 Villigen PSI, Switzerland
André Stephan Henry Prévôt
CORRESPONDING AUTHOR
Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, 5232 Villigen PSI, Switzerland
Data sets
A new method for long-term source apportionment with time-dependent factor profiles and uncertainty assessment using SoFi Pro: application to 1 year of organic aerosol data Francesco Canonaco, Anna Tobler, Gang Chen, Yulia Sosedova, Jay Gates Slowik, Carlo Bozzetti, Kaspar Rudolf Daellenbach, Imad El Haddad, Monica Crippa, Ru-Jin Huang, Markus Furger, Urs Baltensperger, and André Stephan Henry Prévôt https://doi.org/10.5281/zenodo.4456562
Short summary
Long-term ambient aerosol mass spectrometric data were analyzed with a statistical model (PMF) to obtain source contributions and fingerprints. The new aspects of this paper involve time-dependent source fingerprints by a rolling technique and the replacement of the full visual inspection of each run by a user-defined set of criteria to monitor the quality of each of these runs more efficiently. More reliable sources will finally provide better instruments for political mitigation strategies.
Long-term ambient aerosol mass spectrometric data were analyzed with a statistical model (PMF)...
