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| Titel |
Receptor modelling of both particle composition and size distribution from a background site in London, UK |
| VerfasserIn |
D. C. S. Beddows, R. M. Harrison, D. C. Green, G. W. Fuller |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 15, no. 17 ; Nr. 15, no. 17 (2015-09-09), S.10107-10125 |
| Datensatznummer |
250120026
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| Publikation (Nr.) |
 copernicus.org/acp-15-10107-2015.pdf |
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| Zusammenfassung |
| Positive matrix factorisation (PMF) analysis was applied to PM10
chemical composition and particle number size distribution (NSD) data
measured at an urban background site (North Kensington) in London, UK, for the
whole of 2011 and 2012. The PMF analyses for these 2 years revealed six and four factors
respectively which described seven sources or aerosol types. These included
nucleation, traffic, urban background, secondary, fuel oil, marine and
non-exhaust/crustal sources. Urban background, secondary and traffic sources
were identified by both the chemical composition and particle NSD analysis, but a nucleation source was identified only from the
particle NSD data set. Analysis of the PM10 chemical
composition data set revealed fuel oil, marine, non-exhaust traffic/crustal
sources which were not identified from the NSD data. The
two methods appear to be complementary, as the analysis of the PM10
chemical composition data is able to distinguish components contributing
largely to particle mass, whereas the number particle size distribution
data set – although limited to detecting sources of particles below the
diameter upper limit of the SMPS (604 nm) – is more effective for identifying
components making an appreciable contribution to particle number. Analysis
was also conducted on the combined chemical composition and NSD data set, revealing five factors representing urban background,
nucleation, secondary, aged marine and traffic sources. However, the combined
analysis appears not to offer any additional power to discriminate sources
above that of the aggregate of the two separate PMF analyses. Day-of-the-week
and month-of-the-year associations of the factors proved consistent with
their assignment to source categories, and bivariate polar plots which
examined the wind directional and wind speed association of the different
factors also proved highly consistent with their inferred sources. Source
attribution according to the air mass back trajectory showed, as expected,
higher concentrations from a number of source types in air with continental
origins. However, when these were weighted according to their frequency of
occurrence, air with maritime origins made a greater contribution to annual
mean concentrations. |
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