Downscaling global anthropogenic emissions for high-resolution urban air quality studies
2022
Valencia, Victor H. | Levin, Gregor | Ketzel, Matthias
This study presents a method for “downscaling” aggregated global emissions of CO, NOₓ, and PM₂.₅ based on georeferenced information (spatial proxies). We distribute ECLIPSE-CLE emissions for Quito, Ecuador, in 2015 and 2017. The study area is a grid of 0.5 × 0.5 km² cells over a 110 × 110 km² area. The emission sectors (proxies in parenthesis) are agricultural (land-use maps), domestic (land-use and population density), energy, industry, and waste disposal (point source location from local inventory), and transport (population, vehicle traffic, and road density). Emission distribution quality is satisfactorily evaluated (graphically and statistically) by implementing them in the UBM model and comparing modeled concentrations with observations. This study also explores an alternative proxy set-up for main road emissions based on road density, which, for some modeling sites, results in a better agreement with the observations. Finally, this methodology is applied for comparing air pollution due to two urban growth types for Quito in 2040: sprawl and densification. Both scenarios lead to lower concentrations than in 2017, except for O₃. Although the two scenarios attain similar concentrations, urban sprawl presents, in general, noticeably higher values for NOₓ and NO₂.
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