Numerical simulations of global atmospheric composition for the purpose of improving air quality modelling

Where observations of air pollution are unavailable, e.g. from emissions of future facilities or in remote areas, air pollution is simulated with computer models. These models require input of emissions from nearby sources but also of background concentrations that are caused by sources outside of the modelling domain, because the domain is limited by computational power and the need to resolve air quality at a fine spatial resolution. The objective of this internship is to generate air quality output from a coarse global computer model to provide background concentrations for smaller regions over historical (and potentially future) periods. This output would improve regulatory air quality modelling, which is currently performed on the basis of crude assumptions of constant background concentrations. Improved regulatory modelling benefit regulators, industrial emitters, and the general public by providing improved guidance on policy, emission control, and protection of human, animal, and ecosystem health.

Faculty Supervisor:

Ann-Lise Norman


Zahra Hosseini




Physics / Astronomy


Environmental industry


University of Calgary



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