1.4 High Resolution On-Line Air-Quality Model Simulations of Canada's Oil Sands

Tuesday, 8 January 2013: 4:45 PM
Room 16A (Austin Convention Center)
Paul, A. Makar, EC, Toronto, ON, Canada; and S. Gravel, C. Stroud, B. Pabla, J. Zhang, M. D. Moran, W. Gong, P. Cheung, S. H. Cho, C. McLinden, S. Gong, and C. J. Mooney

The governments of Canada and the Canadian province of Alberta have recently begun a long-term campaign to monitor air quality at and downwind of the Oil Sands of Alberta. This multi-year project includes enhanced monitoring network observations, measurement intensives, and special studies designed to elucidate the key processes for air-quality in this heavily industrialized region.

The myriad of different measurements, the complexity of the chemistry, and the need for estimating both ecosystem and human impacts of the primary and secondary chemistry, require the use of air-quality models as a tool for synthesis and explanation of the local and long-range-transport chemistry.

The use of the Global Environmental Multiscale – Modelling Air-quality and Chemistry (GEM-MACH) model as this integrating tool will be discussed. GEM-MACH has been used as the Canadian Operational Air-Quality forecast model since 2009. The model is on-line (one-way coupling with the GEM weather forecast model) and multi-pollutant (42 gas-phase species, 8 particle species, sectional size representation with 2 or 12 bins). Process representation in GEM-MACH includes semi-lagrangian advection, major point source plume rise, gas-phase chemistry, vertical diffusion and area emissions, organic and inorganic particle chemistry, aqueous phase processes, cloud processing of aerosols, and particle microphysics. Diagnostics include accumulation of wet and dry deposited fields and column values for comparison to satellite observations. Emissions are provided using the SMOKE emissions processing system. The highest resolution domain of this multi-level system covers most of the Canadian provinces of Alberta and Saskatchewan with a grid spacing of 2.5 km.

In the work to be presented, we will describe the setup, testing and initial evaluation of a nested version of GEM-MACH, operating as an experimental forecast since the fall of 2012. Also in the fall of 2012, a surface based monitoring intensive took place – initial comparisons between these observations and the model will be presented.

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