Abstract: Multi-scale-modelling study of conventional top-down source emission-rate estimation methodologies was conducted. Two modelling systems were employed: Environment and Climate Change Canada's regional air quality model GEM-MACH at 2.5km resolution (high-resolution), and Weather Research and Forecasting (WRF) with ARW dynamical core at 50m resolution (super-resolution). Using GEM-MACH, high-resolution air-quality model simulations were conducted for the period of an airborne campaign in 2013 over the Canadian oil sands facilities. Modelling products from these simulations were analyzed to investigate the application of the mass-balance technique in aircraft-based retrievals. Using WRF-ARW, super-resolution model simulations with LES subgrid-parameterization were developed/implemented. The objective was to resolve smaller dynamical processes at the spatio-temporal scales of the airborne measurements. This was achieved by multi-domain model nesting in the horizontal, grid-refining in the vertical, and down-scaling of reanalysis data from 31.25 km to 50 m. Modelling products from GEM-MACH and WRF-ARW simulations were used to simulate/evaluate conventional aircraft-based retrievals. It was shown that conventional methods can result in estimates with 30-50% uncertainty/error. Further, multi-scale modelling products were used to explore methods and strategies for optimizing aircraft-based retrievals.