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Abstract

Pollutant transport modelling is widely used to study and forecast pollution events. Regional scale models are often employed to produce high-resolution datasets to drive transport modelling; however, this requires expertise, resources, and time. As such, the benefits of downscaling under different transport scenarios need to be explored. Here, the added value of downscaling was tested in the aftermath of the “Effect of Megacities on the transport and transformation of pollutants on the regional to global scales” (EMeRGe) project. During the project, transport forecasts were carried out after controlled releases of perfluoroalkylcycloalkanes (PFCs) to identify sampling areas for aircraft observations using IFS forecast data for 3 cases over different orographic settings: short-distance transport over small-scale topographic maxima (Manilla; Philippines), short-distance transport over large-scale topographic maxima (Taipei, Taiwan) and long-distance transport over mixed topography (Nanjing, China, sampled over Taiwan). Considering the expected PFC mixing ratios of ppqV, it is important to explore whether the best possible areas were chosen. To do this, transport simulations were repeated using: FLEXPART (with ERA5 and IFS data), and FLEXPART-WRF (with dynamically-downscaled IFS data down to 1.1km and 4 PBL parametrisations. Of the three scenarios, dynamical downscaling led to significant differences for the Manilla and Taipei cases, caused by the representation of the orographic flow regimes. The choice of PBL scheme also significantly impacted accuracy, but there was no systematically better-performing option. Overall, results highlight the role that dynamical downscaling can play as an important component in campaign planning when dealing with observations over orographically-complex areas.