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Abstract. The oil sands (OS) of Alberta, Canada, which are classified as unconventional oil,are the third-largest oil reserves in the world. We describe here a 6-yeareffort to improve the emissions data used for air quality (AQ) modeling ofthe roughly 100 km  ×  100 km oil extraction and processingindustrial complex operating in the Athabasca Oil Sands Region (AOSR) ofnortheastern Alberta. This paper reviews the national, provincial, andsub-provincial emissions inventories that were available during the threephases of the study, supplemented by hourly SO2 and NOx emissions and stack characteristics for larger pointsources measured by a continuous emission monitoring system (CEMS), as well as dailyreports of SO2 from one AOSR facility for a 1-week period duringa 2013 field campaign when the facility experienced upset conditions. Next itdescribes the creation of several detailed hybrid emissions inventories andthe generation of model-ready emissions input files for the GlobalEnvironmental Multiscale–Modelling Air quality and CHemistry (GEM-MACH) AQmodeling system that were used during the 2013 field study and for variouspost-campaign GEM-MACH sensitivity studies, in particular for ahigh-resolution model domain with 2.5 km grid spacing covering much ofwestern Canada and centered over the AOSR. Lastly, it compares inventory-basedbottom-up emissions with aircraft-observation-based top-down emissionsestimates. Results show that emissions values obtained from different datasources can differ significantly, such as a possible 10-fold difference inPM 2.5 emissions and approximately 40 and 20 % differences for totalVOC (volatile organic compound) and SO2 emissions. A novel emissions-processing approach was alsoemployed to allocate emissions spatially within six large AOSR miningfacilities in order to address the urban-scale spatial extent of thefacilities and the high-resolution 2.5 km model grid. Gridded facility- andprocess-specific spatial surrogate fields that were generated using spatialinformation from GIS (geographic information system) shapefiles and satelliteimages were used to allocate non-smokestack emissions for each facility tomultiple grid cells instead of treating these emissions as point sources andallocating them to a single grid cell as is normally done. Facility- andprocess-specific temporal profiles and VOC speciation profiles were alsodeveloped. The pre-2013 vegetation and land-use databases normally used toestimate biogenic emissions and meteorological surface properties weremodified to account for the rapid change in land use in the study area due tomarked, year-by-year changes in surface mining activities, including the 2013opening of a new mine. Lastly, mercury emissions data were also processed inaddition to the seven criteria-air-contaminant (CAC) species ( NOx ,VOC, SO2 , NH3 , CO, PM 2.5 , and PM 10 ) to supportAOSR mercury modeling activities. Six GEM-MACH modeling papers in thisspecial issue used some of these new sets of emissions and land-use inputfiles.

Emissions preparation and analysis for multiscale air quality modeling over the Athabasca Oil Sands Region of Alberta, Canada