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

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Cited articles

Aalto, P., Hameri, K., Becker, E., Weber, R., Salm, J., Makela, J. M., Hoell, C., O'Dowd, C. D., Karlsson, H., Hansson, H. C., Vakeva, M., Koponen, I. K., Buzorius, G., and Kulmala, M.: Physical characterization of aerosol particles during nucleation events, Tellus B, 53, 344–358, https://doi.org/10.1034/j.1600-0889.2001.530403.x, 2001.
Aiken, A. C., DeCarlo, P. F., and Jimenez, J. L.: Elemental analysis of organic species with electron ionization high-resolution mass spectrometry, Anal. Chem., 79, 8350–8358, 2007.
Äijälä, M., Junninen, H., Petäjä, T., Kulmala, M., Worsnop, D., and Ehn, M.: De-convolved mass spectra from the air pollution events and their classification solution, available at: https://etsin.avointiede.fi/dataset/urn-nbn-fi-csc-kata20170118173805948017 (last access: 20 February 2017), 2017.
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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.
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