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| Titel |
A comparison of four receptor models used to quantify the boreal wildfire smoke contribution to surface PM2.5 in Halifax, Nova Scotia during the BORTAS-B experiment |
| VerfasserIn |
M. D. Gibson, J. Haelssig, J. R. Pierce, M. Parrington, J. E. Franklin, J. T. Hopper, Z. Li, T. J. Ward |
| 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. 2 ; Nr. 15, no. 2 (2015-01-23), S.815-827 |
| Datensatznummer |
250119341
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| Publikation (Nr.) |
 copernicus.org/acp-15-815-2015.pdf |
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| Zusammenfassung |
| This paper presents a quantitative comparison of the four most commonly used
receptor models, namely absolute principal component scores (APCS),
pragmatic mass closure (PMC), chemical mass balance (CMB) and positive
matrix factorization (PMF). The models were used to predict the
contributions of a wide variety of sources to PM2.5 mass in Halifax,
Nova Scotia during the experiment to quantify the impact of BOReal forest fires
on Tropospheric oxidants over the Atlantic using Aircraft and Satellites
(BORTAS). However, particular emphasis was placed on the capacity
of the models to predict the boreal wildfire smoke contributions during the
BORTAS experiment. The performance of the four receptor models was assessed
on their ability to predict the observed PM2.5 with an R2 close
to 1, an intercept close to zero, a low bias and low RSME. Using PMF, a
new woodsmoke enrichment factor of 52 was estimated for use in the PMC
receptor model. The results indicate that the APCS and PMC receptor models
were not able to accurately resolve total PM2.5 mass concentrations
below 2 μg m−3. CMB was better able to resolve these low
PM2.5 concentrations, but it could not be run on 9 of the 45 days of
PM2.5 samples. PMF was found to be the most robust of the four models
since it was able to resolve PM2.5 mass below 2 μg m−3,
predict PM2.5 mass on all 45 days and utilise an unambiguous
woodsmoke chemical tracer. The median woodsmoke relative contributions to
PM2.5 estimated using PMC, APCS, CMB and PMF were found to be 0.08,
0.09, 3.59 and 0.14 μg m−3 respectively. The contribution
predicted by the CMB model seemed to be clearly too high based on other
observations. The use of levoglucosan as a tracer for woodsmoke was found to
be vital for identifying this source. |
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