Articles | Volume 18, issue 18
https://doi.org/10.5194/acp-18-13531-2018
https://doi.org/10.5194/acp-18-13531-2018
Research article
 | 
25 Sep 2018
Research article |  | 25 Sep 2018

Improving air quality model predictions of organic species using measurement-derived organic gaseous and particle emissions in a petrochemical-dominated region

Craig A. Stroud, Paul A. Makar, Junhua Zhang, Michael D. Moran, Ayodeji Akingunola, Shao-Meng Li, Amy Leithead, Katherine Hayden, and May Siu

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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Craig Stroud on behalf of the Authors (01 Aug 2018)  Author's response 
ED: Reconsider after major revisions (16 Aug 2018) by Jan W. Bottenheim
AR by Craig Stroud on behalf of the Authors (24 Aug 2018)  Author's response   Manuscript 
ED: Publish subject to technical corrections (02 Sep 2018) by Jan W. Bottenheim
AR by Craig Stroud on behalf of the Authors (05 Sep 2018)  Manuscript 
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Short summary
It is shown that using measurement-derived volatile organic compound (VOC) and organic aerosol (OA) emissions in the GEM-MACH air quality model provides better overall predictions compared to using bottom-up emission inventories. This work was done to better constrain the fugitive organic emissions from the Athabasca oil sands region, which are a challenge to estimate with bottom-up emission approaches. We use observations from the 2013 Joint Oil Sands Monitoring study.
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