4.7 Article

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

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ATMOSPHERIC CHEMISTRY AND PHYSICS
卷 15, 期 12, 页码 6993-7002

出版社

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/acp-15-6993-2015

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资金

  1. Swiss Federal Office for the Environment (FOEN)
  2. Environmental group of the Swiss Federal Laboratories for Materials and Testing (Empa)
  3. Swiss National Science Foundation (SNF) [PZ00P2_131673, BSSGI0_155846]
  4. Swiss National Science Foundation (SNF) [PZ00P2_131673] Funding Source: Swiss National Science Foundation (SNF)

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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 (f(44)), 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 (O-3 + NO2), f(44) 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, f(43) (less oxidized fragment) tends to increase. These changes are discussed in the f(44) / f(43) 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 f(44) / f(43) 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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