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. We evaluate four high-resolution model simulations of pollutantemissions, chemical transformation, and downwind transport for the Athabascaoil sands using the Global Environmental Multiscale – Modelling Air-qualityand Chemistry (GEM-MACH) model, and compare model results with surfacemonitoring network and aircraft observations of multiple pollutants, forsimulations spanning a time period corresponding to an aircraft measurementcampaign in the summer of 2013. We have focussed here on the impact ofdifferent representations of the model's aerosol size distribution andplume-rise parameterization on model results. The use of a more finely resolved representation of the aerosol sizedistribution was found to have a significant impact on model performance,reducing the magnitude of the original surface PM2.5 negative biases32 %, from −2.62 to −1.72 µg m−3. We compared model predictions of SO2, NO2, and speciatedparticulate matter concentrations from simulations employing the commonlyused Briggs (1984) plume-rise algorithms to redistribute emissions from largestacks, with stack plume observations. As in our companion paper (Gordon etal., 2017), we found that Briggs algorithmsbased on estimates of atmospheric stability at the stack height resulted inunder-predictions of plume rise, with 116 out of 176 test cases falling belowthe model : observation 1 : 2 line, 59 cases falling within a factor of 2of the observed plume heights, and an average model plume height of 289 mcompared to an average observed plume height of 822 m. We used ahigh-resolution meteorological model to confirm the presence of significanthorizontal heterogeneity in the local meteorological conditions driving plumerise. Using these simulated meteorological conditions at the stack locations,we found that a layered buoyancy approach for estimating plume rise in stableto neutral atmospheres, coupled with the assumption of free rise inconvectively unstable atmospheres, resulted in much better model performancerelative to observations (124 out of 176 cases falling within a factor of 2of the observed plume height, with 69 of these cases above and 55 of thesecases below the 1 : 1 line and within a factor of 2 of observed values).This is in contrast to our companion paper, wherein this layered approach(driven by meteorological observations not co-located with the stacks) showeda relatively modest impact on predicted plume heights. Persistent issues withover-fumigation of plumes in the model were linked to a more rapid decreasein simulated temperature with increasing height than was observed. This inturn may have led to overestimates of near-surface diffusivity, resulting inexcessive fumigation.

A chemical transport model study of plume-rise and particle size distribution for the Athabasca oil sands