Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 14, issue 2
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.
https://doi.org/10.5194/amt-14-923-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 2
Research article
 | 
08 Feb 2021
Research article |  | 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, 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

Viewed

Total article views: 4,994 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
3,370 1,525 99 4,994 504 121 186
  • HTML: 3,370
  • PDF: 1,525
  • XML: 99
  • Total: 4,994
  • Supplement: 504
  • BibTeX: 121
  • EndNote: 186
Views and downloads (calculated since 17 Jul 2020)
Cumulative views and downloads (calculated since 17 Jul 2020)

Viewed (geographical distribution)

Total article views: 4,994 (including HTML, PDF, and XML) Thereof 4,820 with geography defined and 174 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 23 Nov 2025
Download
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.
Read more
Share