Articles | Volume 15, issue 12
Atmos. Chem. Phys., 15, 6993–7002, 2015
https://doi.org/10.5194/acp-15-6993-2015
Atmos. Chem. Phys., 15, 6993–7002, 2015
https://doi.org/10.5194/acp-15-6993-2015

Research article 29 Jun 2015

Research article | 29 Jun 2015

Seasonal differences in oxygenated organic aerosol composition: implications for emissions sources and factor analysis

F. Canonaco, J. G. Slowik, U. Baltensperger, and A. S. H. Prévôt F. Canonaco et al.
  • Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland

Abstract. Aerosol chemical speciation monitor (ACSM) measurements were performed in Zurich, Switzerland, for 13 months (February 2011 through February 2012). Many previous studies using this or related instruments have utilized the fraction of organic mass measured at m/z 44 (f44), which is typically dominated by the CO2+ ion and related to oxygenation, as an indicator of atmospheric aging. The current study demonstrates that during summer afternoons, when photochemical processes are most vigorous as indicated by high oxidant – OX (O3 + NO2), f44 for ambient secondary organic aerosol (SOA) is not higher but is rather similar or lower than on days with low OX. On the other hand, f43 (less oxidized fragment) tends to increase. These changes are discussed in the f44 / f43 space frequently used to interpret ACSM and aerosol mass spectrometer (AMS) data. This is likely due to the formation of semi-volatile oxygenated aerosol produced from biogenic precursor gases, whose emissions increase with ambient temperature.

In addition, source apportionment analyses conducted on winter and summer data using positive matrix factorization (PMF) yield semi-volatile oxygenated organic aerosol (SV-OOA) factors that retain source-related chemical information. Winter SV-OOA is highly influenced by biomass burning, whereas summer SV-OOA is to a high degree produced from biogenic precursor gases. These sources contribute to substantial differences between the winter and summer f44 / f43 data, suggesting that PMF analysis of multi-season data employing only two OOA factors cannot capture the seasonal variability of OOA.

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