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| Titel |
Mixing state of carbonaceous aerosol in an urban environment: single particle characterization using the soot particle aerosol mass spectrometer (SP-AMS) |
| VerfasserIn |
A. K. Y. Lee, M. D. Willis, R. M. Healy, T. B. Onasch, J. P. D. Abbatt |
| 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. 4 ; Nr. 15, no. 4 (2015-02-20), S.1823-1841 |
| Datensatznummer |
250119447
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| Publikation (Nr.) |
 copernicus.org/acp-15-1823-2015.pdf |
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| Zusammenfassung |
| Understanding the impact of atmospheric black carbon (BC)-containing
particles on human health and radiative forcing requires knowledge of the
mixing state of BC, including the characteristics of the materials with
which it is internally mixed. In this study, we examine the mixing state of
refractory BC (rBC) and other aerosol components in an urban environment
(downtown Toronto) utilizing the Aerodyne soot particle aerosol mass
spectrometer equipped with a light scattering module (LS-SP-AMS). k-means
cluster analysis was used to classify single particle mass spectra into
chemically distinct groups. One resultant particle class is dominated by rBC
mass spectral signals (C1+ to C5+) while the organic
signals fall into a few major particle classes identified as
hydrocarbon-like organic aerosol (HOA), oxygenated organic aerosol (OOA),
and cooking emission organic aerosol (COA). A gradual mixing is observed
with small rBC particles only thinly coated by HOA (~ 28%
by mass on average), while over 90% of the HOA-rich particles did not
contain detectable amounts of rBC. Most of the particles classified into
other inorganic and organic particle classes were not significantly
associated with rBC. The single particle results also suggest that HOA and
COA emitted from anthropogenic sources were likely major contributors to
organic-rich particles with vacuum aerodynamic diameter (dva) ranging
from ~ 200 to 400 nm. The similar temporal profiles and mass
spectral features of the organic classes identified by cluster analysis and
the factors from a positive matrix factorization (PMF) analysis of the
ensemble aerosol data set validate the interpretation of the PMF results. |
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