The governments of Canada and Alberta are implementing a joint plan for oil sands monitoring that includes investigating emissions, transport and downwind chemistry associated with the Canadian oil sands region. As part of that effort, Environment Canada's Global Environmental Multiscale-Modelling Air-quality And CHemistry (GEM-MACH) system was reconfigured for the first time to create nested forecasts of air quality at model grid resolutions down to 2.5 km, with the highest resolution domain including the Canadian provinces of Alberta and Saskatchewan. The forecasts were used to direct an airborne research platform during a summer 2013 monitoring intensive. Subsequent work with the modelling system has included an in-depth comparison of the model predictions to monitoring network observations, and to field intensive airborne and surface supersite observations. A year of model predictions and monitoring network observations were compared, as were model and aircraft flight track values. The relative impact of different model versions (including modified emissions and feedbacks between weather and air pollution) will be discussed. Model-based predictions of indicators of human-health (i.e., Air Quality Health Index) and ecosystem (i.e. deposition of pollutants) impacts for the region will also be described.
Luo G, Zhang W, Zhang J, Cong J. Scaling Up Physical Design, in Proceedings of the 2016 on International Symposium on Physical Design - ISPD '16. New York, New York, USA: ACM Press; 2016:131–137. 访问链接