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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 : Volume 14, Issue 17 (17/09/2014)

By Gibson, M. D.

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Book Id: WPLBN0003978028
Format Type: PDF Article :
File Size: Pages 44
Reproduction Date: 2015

Title: 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 : Volume 14, Issue 17 (17/09/2014)  
Author: Gibson, M. D.
Volume: Vol. 14, Issue 17
Language: English
Subject: Science, Atmospheric, Chemistry
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Haelssig, J., Parrington, M., Hopper, J. T., Pierce, J. R., Franklin, J. E., Gibson, M. D.,...Ward, T. J. (2014). 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 : Volume 14, Issue 17 (17/09/2014). Retrieved from

Description: Department of Process Engineering and Applied Science, Dalhousie University, Halifax, Nova Scotia, Canada. 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 Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites (BORTAS) experiment. However, particular emphasis was placed on the capacity of the models to predict the boreal wild fire smoke contributions during the BORTAS experiment. 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 2.0 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 2.0 Μg m−3, predict PM2.5 mass on all 45 days, and utilized an unambiguous woodsmoke chemical marker. The median woodsmoke relative contribution 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 seems 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.

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

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