The Arctic has warmed disproportionately relative to mid-latitudes over recent decades. This warming is predominantly controlled by radiative forcing from well-mixed greenhouse gases, amplified by efficient Arctic climate feedbacks. However, warming from changes in short-lived climate pollutants (SLCPs), such as tropospheric ozone, have been shown to contribute substantially to Arctic warming, whilst also degrading air quality. Arctic SLCP abundances are controlled by long-range transport from mid-latitudes, and by local sources within the Arctic. At present, high latitude emissions of SLCPs and ozone precursors (e.g nitrogen dioxide [NO2]) are poorly quantified, with a paucity of in-situ observations. Using a regional chemistry transport model, this thesis aims to improve the understanding of processes controlling tropospheric ozone abundances and distributions in areas of limited in-situ observations at high latitudes.
In western Siberia there is widespread negative bias in modelled tropospheric column NO2 when compared to satellite observations from May–August. Despite the large negative bias, the spatial correlations between model and observed NO2 columns suggest that the spatial pattern of NOx sources in the region is well represented. Scaling the two largest anthropogenic sectors (energy & transport) by a factor of 2 reduces column NO2 bias (fractional mean bias =−0.66 to −0.35). The findings in this thesis suggest that western Siberian ozone is more sensitive to anthropogenic emissions, particularly from the transport sector, and the contribution from fire emissions maximises in June and is largely confined to latitudes south of 60°N. Ozone dry deposition fluxes from the model simulations show that the dominant ozone dry deposition sink in the region is to forest vegetation, averaging 8.0 Tg of ozone per month.
In Fairbanks, Alaska, modelled surface ozone is overestimated during springtime, with an interplay between ozone being vertically mixed down from ozone-rich air above and subsequent ozone loss to NO (O3 + NO = NO2) dominating ozone abundances, suppressing surface ozone. This also leads to significant overestimations in surface NO2. Sensitivity studies tested modelled ozone sensitivity to Fairbanks NOx emissions and model upper boundary conditions. Results suggest that upper troposphere ozone is sensitive to a 20% reduction in initial boundary condition ozone, which brings the values in-line with observations. Whilst a doubling of NOx emissions from within Fairbanks improves the model ozone bias at the surface, but still leads to model overestimation above the boundary layer
