Articles | Volume 17, issue 4
https://doi.org/10.5194/acp-17-3165-2017
https://doi.org/10.5194/acp-17-3165-2017
Research article
 | 
01 Mar 2017
Research article |  | 01 Mar 2017

Resolving anthropogenic aerosol pollution types – deconvolution and exploratory classification of pollution events

Mikko Äijälä, Liine Heikkinen, Roman Fröhlich, Francesco Canonaco, André S. H. Prévôt, Heikki Junninen, Tuukka Petäjä, Markku Kulmala, Douglas Worsnop, and Mikael Ehn

Viewed

Total article views: 3,994 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,359 1,496 139 3,994 500 108 130
  • HTML: 2,359
  • PDF: 1,496
  • XML: 139
  • Total: 3,994
  • Supplement: 500
  • BibTeX: 108
  • EndNote: 130
Views and downloads (calculated since 01 Sep 2016)
Cumulative views and downloads (calculated since 01 Sep 2016)

Viewed (geographical distribution)

Total article views: 3,994 (including HTML, PDF, and XML) Thereof 3,977 with geography defined and 17 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 15 Jun 2025
Download
Short summary
Mass spectrometric measurements commonly yield data on hundreds of variables over thousands of points in time. Refining and synthesising this “raw” data into chemical information necessitates the use of advanced, statistics-based data analysis techniques. Here we present an example of combining data dimensionality reduction (factorisation) with exploratory classification (clustering) and show that the results complement and broaden our current perspectives on aerosol chemical classification.
Share
Altmetrics
Final-revised paper
Preprint