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| Titel |
Tracer-based source-apportionment from the EUCAARI project and comparison with the EMEP model |
| VerfasserIn |
David Simpson, Célia Alves, Robert Bergstrom, Stefano Decesari, Gyula Kiss, Eiko Nemitz, André Prévôt, Erik Swietlicki |
| Konferenz |
EGU General Assembly 2011
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 13 (2011) |
| Datensatznummer |
250051031
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| Zusammenfassung |
| Particulate carbonaceous matter (PCM) is found to constitute 10-40% (mean 30%) of PM10
levels at rural and natural background sites in Europe (Yttri et al., 2007; Putaud et
al., 2004). Recent reviews have highlighted the complexity of the carbonaceous
aerosol both in terms composition and formation mechanisms Hallquist et al. (2009),
and until recently there have been very few direct measurements which allow a
determination of how much of PCM is from anthropogenic versus biogenic sources, or from
primary emissions versus from secondary organic aerosol (SOA) formation. However,
over the last few years a number measurement results using tracer methods have
become available which have started to shed light on the important sources of PCM in
Europe (Gelencsér et al., 2007; Saarikoski et al., 2008; Szidat et al., 2006, 2007,
2009).
Within the EUCAARI project, data on 14C, EC, OC and GC-MS analyses are available
from four sites, K-Puszta (Hungary), Hyytiälä (Finland), Melpitz (Germany), and San Pietro
Capofiume (Italy). Additional data and analyses (AMS, NMR, other) are available from a
number of other sites, including for example Barcelona (Spain), or Vavihill (Sweden). The
link between tracers and their associated organic carbon amounts are of course very
uncertain. Following Gelencsér et al. (2007) we define both a central best-estimate value for
each factor and a plausible range of uncertainty. In order to tackle the multitude of possible
combinations of these uncertain parameters, we have made use of an effective statistical
approach known as Latinhypercube sampling (LHS) (Iman et al., 1981). LHS approaches are
somewhat similar to Monte Carlo calculations, and allow vast numbers of combinations of
input variables to be computed. A Monte-Carlo simulation would involve testing all possible
combinations of input parameters. LHS provides a much more effective way of
sampling the data, and for our purposes provides essentially the same results as a full
Monte-Carlo analysis.All valid combinations of parameters (i.e. excluding those
producing negative contributions) are condensed in frequency distributions of possible
solutions.
This talk focuses on the use of such tracers to shed light on the sources of PCM in
Europe. We make use of methodologies similar to those used by Szidat et al. (2006, 2009),
and within the EU CARBOSOL project (Gelencsér et al., 2007), in an effort to calculate the
relative contributions of the primary/secondary and anthropogenic/natural sources of the
carbonaceous aerosol.
Model results for SOA are also extremely sensitive to a wide range of assumptions, with little
bases for choosing between different approaches. We illustrate how source-apportionment
analysis can be used to discriminate between different SOA schemes, and to constrain model
possibilities. |
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