Mass Spectra Deconvolution of Low, Medium, and High Volatility Biogenic Secondary Organic Aerosol. Kostenidou, E., Lee, B., Engelhart, G., J., Pierce, J., R., & Pandis, S., N. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 43(13):4884-4889, 7, 2009.
abstract   bibtex   
Secondary organic aerosol (SON consists of compounds with a wide range of volatilities and its ambient concentration is sensitive to this volatility distribution. Recent field studies have shown that the typical mass spectrum of ambient oxygenated organic aerosol (OOA) as measured by the Aerodyne Aerosol Mass Spectrometer (AMS) is quite different from the SOA mass spectra reported in smog chamber experiments. Part of this discrepancy is due to the dependence of SOA composition on the organic aerosol concentration. High precursor concentrations lead to higher concentrations of the more volatile species in the produced SOA while at lower concentrations the less volatile compounds dominate the SOA composition. alpha-Pinene, beta-pinene, d-limonene, and P-caryophyllone ozonolysis experiments were. performed at moderate concentration levels. Using a thermodenuder the more volatile SOA species were removed achieving even lower SOA concentration. The less volatile fraction was then chemically characterized by an AMS. The signal fraction of m/z 44, and thus the concentration of CO2+, is significantly higher for the less volatile SOA. High NO, conditions result in less oxidized SOA than low NO, conditions, while increasing relative humidity levels results in more oxidized products for limonene but has little effect on alpha-and beta-pinene SOA. Combining a smog chamber with a thermodenuder model employing the volatility basis-set framework, the AMS SOA mass spectrum for each experiment and for each precursor is deconvoluted into low, medium, and high volatility component mass spectra. The spectrum of the surrogate component with the lower volatility is quite similar to that of ambient OOA.
@article{
 title = {Mass Spectra Deconvolution of Low, Medium, and High Volatility Biogenic Secondary Organic Aerosol},
 type = {article},
 year = {2009},
 identifiers = {[object Object]},
 pages = {4884-4889},
 volume = {43},
 month = {7},
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 citation_key = {Kostenidou.est.2009a},
 source_type = {article},
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 abstract = {Secondary organic aerosol (SON consists of compounds with a wide range
of volatilities and its ambient concentration is sensitive to this
volatility distribution. Recent field studies have shown that the
typical mass spectrum of ambient oxygenated organic aerosol (OOA) as
measured by the Aerodyne Aerosol Mass Spectrometer (AMS) is quite
different from the SOA mass spectra reported in smog chamber
experiments. Part of this discrepancy is due to the dependence of SOA
composition on the organic aerosol concentration. High precursor
concentrations lead to higher concentrations of the more volatile
species in the produced SOA while at lower concentrations the less
volatile compounds dominate the SOA composition. alpha-Pinene,
beta-pinene, d-limonene, and P-caryophyllone ozonolysis experiments
were. performed at moderate concentration levels. Using a thermodenuder
the more volatile SOA species were removed achieving even lower SOA
concentration. The less volatile fraction was then chemically
characterized by an AMS. The signal fraction of m/z 44, and thus the
concentration of CO2+, is significantly higher for the less volatile
SOA. High NO, conditions result in less oxidized SOA than low NO,
conditions, while increasing relative humidity levels results in more
oxidized products for limonene but has little effect on alpha-and
beta-pinene SOA. Combining a smog chamber with a thermodenuder model
employing the volatility basis-set framework, the AMS SOA mass spectrum
for each experiment and for each precursor is deconvoluted into low,
medium, and high volatility component mass spectra. The spectrum of the
surrogate component with the lower volatility is quite similar to that
of ambient OOA.},
 bibtype = {article},
 author = {Kostenidou, Evangelia and Lee, Byong-Hyoek and Engelhart, Gabriella J and Pierce, Jeffrey R and Pandis, Spyros N},
 journal = {ENVIRONMENTAL SCIENCE & TECHNOLOGY},
 number = {13}
}

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