Articles | Volume 18, issue 18
Atmos. Chem. Phys., 18, 13531–13545, 2018
https://doi.org/10.5194/acp-18-13531-2018

Special issue: Atmospheric emissions from oil sands development and their...

Atmos. Chem. Phys., 18, 13531–13545, 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 et al.

Data sets

Joint Oil Sands Monitoring Program Emissions Inventory report Environment and Climate Change Canada https://www.canada.ca/en/environment-climate-change/services/science-technology/publications/joint-oil-sands-monitoring-emissions-report.html

Joint Oil Sands Emissions Inventory Database Environment and Climate Change Canada http://ec.gc.ca/data_donnees/SSB-OSM_Air/Air/Emissions_inventory_files/

Oil Sands Data Portal Environment and Climate Change Canada https://www.canada.ca/en/environment-climate-change/services/oil-sands-monitoring/monitoring-air-quality-alberta-oil-sands.html

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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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