A new method to discriminate secondary organic aerosols from different sources using high-resolution aerosol mass spectra

M.F. Heringa, P.F. Decarlo, R. Chirico, T. Tritscher, M. Clairotte, C. Mohr, M. Crippa, J.G. Slowik, L. Pfaffenberger, J. Dommen, E. Weingartner, A.S.H. Prévôt, U. Baltensperger

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Abstract

Organic aerosol (OA) represents a significant and often major fraction of the non-refractory PM1 (particulate matter with an aerodynamic diameter d 0.94 for the correlations between the four different SOA types after five hours of aging. High-resolution mass spectra (HR-MS) showed that the dominant peaks in the MS, m/z 43 and 44, are dominated by the oxygenated ions C2H3O+and C2+, respectively, similarly to the relatively fresh semi-volatile oxygenated OA (SV-OOA) observed in the ambient aerosol. The atomic O:C ratios were found to be in the range of 0.25-0.55 with no major increase during the first five hours of aging. On average, the diesel SOA showed the lowest O:C ratio followed by SOA from wood burning, α-pinene and the scooter emissions. Grouping the fragment ions revealed that the SOA source with the highest O:C ratio had the largest fraction of small ions. The HR data of the four sources could be clustered and separated using principal component analysis (PCA). The model showed a significant separation of the four SOA types and clustering of the duplicate experiments on the first two principal components (PCs), which explained 79% of the total variance. Projection of ambient SV-OOA spectra resolved by positive matrix factorization (PMF) showed that this approach could be useful to identify large contributions of the tested SOA sources to SV-OOA. The first results from this study indicate that the SV-OOA in Barcelona is strongly influenced by diesel emissions in winter while in summer at SIRTA at the southwestern edge of Paris SV-OOA is more similar to alpha-pinene SOA. However, contributions to the ambient SV-OOA from SOA sources that are not covered by the model can cause major interference and therefore future expansions of the PCA model with additional SOA sources is recommended. © 2012 Author(s).
Original languageEnglish
Pages (from-to)2189 - 2203
Number of pages15
JournalAtmospheric Chemistry and Physics
Volume12
Issue number4
DOIs
Publication statusPublished - 2012
Externally publishedYes

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All Science Journal Classification (ASJC) codes

  • Atmospheric Science

Cite this

Heringa, M. F., Decarlo, P. F., Chirico, R., Tritscher, T., Clairotte, M., Mohr, C., ... Baltensperger, U. (2012). A new method to discriminate secondary organic aerosols from different sources using high-resolution aerosol mass spectra. Atmospheric Chemistry and Physics, 12(4), 2189 - 2203. https://doi.org/10.5194/acp-12-2189-2012