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

his study assesses the impact of revised volatile organic compound (VOC) and organic aerosol (OA) emissions estimates in the GEM-MACH (Global Environmental Multiscale–Modelling Air Quality and CHemistry) chemical transport model (CTM) on air quality model predictions of organic species for the Athabasca oil sands (OS) region in Northern Alberta, Canada.

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Short Name of Publication https://www.atmos-chem-phys.net/18/13531/2018/
Deliverable Type Science Article
Program Catagory Atmospheric
Program Type OSM
Autors Craig A. Stroud, Paul A. Makar, Junhua Zhang, Michael D. Moran, Ayodeji Akingunola, Shao-Meng Li, Amy Leithead, Katherine Hayden, and May Siu
Periodical Title Atmospheric Chemistry and Physics
Year of Publication 2018
Publishing Organization Air Quality Research Division, Environment and Climate Change Canada
Month of Publication 9
Periodical Volumes 18
Page Range 13531-13545
Digital Object Identifier (DOI) 10.5194/acp-18-13531-2018
Online ISBN/ISSN 1680-7324
Print ISBN/ISSN 1680-7316
Recomended Citation Stroud, C. A., Makar, P. A., Zhang, J., Moran, M. D., Akingunola, A., Li, S.-M., … Siu, M. (2018). Improving air quality model predictions of organic species using measurement-derived organic gaseous and particle emissions in a petrochemical-dominated region. Atmospheric Chemistry and Physics, 18(18), 13531–13545. doi:10.5194/acp-18-13531-2018
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