| Summary: | The Arctic is an area of particular interest in the field of atmospheric science, owing to the amplified warming observed relative to the global mean, and the impact this will have on the global environment. Contributing factors to Arctic climate forcing that are not yet well understood include the dynamics and impacts of aerosols. Long-range transported anthropogenic aerosols dominate the population during the winter, and more locally produced biogenic aerosols dominate during the summer. It is well established that anthropogenic aerosols, specifically those containing sulphate and black carbon (BC), typically scatter and absorb light more strongly than smaller, biogenic aerosols. The concentrations of these species have also declined in recent years. This thesis addresses the fact that despite these observations, aerosols will most likely continue to have a significant climate-forcing effect in the Arctic in the following decades. Firstly, a trend analysis of physical aerosol properties and air mass history was performed for an aerosol number concentration dataset from Villum between the years 2010 and 2018. This showed an increasing trend in the concentrations of ultrafine mode aerosols, and specifically biogenic aerosols from new particle formation processes, which is attributed to changing transport patterns. A separate study into the optical properties and direct radiative forcing potential of these aerosols showed that these same biogenic aerosols are in fact capable of interacting with a significant amount of sunlight over the course of a year. This is because they are predominantly present in the atmosphere during the summer, when the Arctic experiences polar day. A study was also carried out investigating the response of Arctic BC concentrations to the COVID-19 lockdown of spring/summer 2020, as a case study for extreme global emission changes. It was found that despite severe cuts in emission sources like road traffic and aviation, only a reduction in Arctic BC of around 10% was predicted by the model ...
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