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


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Francesco Canonaco on behalf of the Authors (21 Nov 2020)  Author's response   Manuscript 
ED: Publish as is (21 Nov 2020) by Mingjin Tang
AR by Francesco Canonaco on behalf of the Authors (22 Nov 2020)
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.