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    A full year of aerosol size distribution data from the central Arctic under an extreme positive Arctic Oscillation: insights from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition
    (Katlenburg-Lindau : EGU, 2023) Boyer, Matthew; Aliaga, Diego; Pernov, Jakob Boyd; Angot, Hélène; Quéléver, Lauriane L. J.; Dada, Lubna; Heutte, Benjamin; Dall'Osto, Manuel; Beddows, David C. S.; Brasseur, Zoé; Beck, Ivo; Bucci, Silvia; Duetsch, Marina; Stohl, Andreas; Laurila, Tiia; Asmi, Eija; Massling, Andreas; Thomas, Daniel Charles; Nøjgaard, Jakob Klenø; Chan, Tak; Sharma, Sangeeta; Tunved, Peter; Krejci, Radovan; Hansson, Hans Christen; Bianchi, Federico; Lehtipalo, Katrianne; Wiedensohler, Alfred; Weinhold, Kay; Kulmala, Markku; Petäjä, Tuukka; Sipilä, Mikko; Schmale, Julia; Jokinen, Tuija
    The Arctic environment is rapidly changing due to accelerated warming in the region. The warming trend is driving a decline in sea ice extent, which thereby enhances feedback loops in the surface energy budget in the Arctic. Arctic aerosols play an important role in the radiative balance and hence the climate response in the region, yet direct observations of aerosols over the Arctic Ocean are limited. In this study, we investigate the annual cycle in the aerosol particle number size distribution (PNSD), particle number concentration (PNC), and black carbon (BC) mass concentration in the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. This is the first continuous, year-long data set of aerosol PNSD ever collected over the sea ice in the central Arctic Ocean. We use a k-means cluster analysis, FLEXPART simulations, and inverse modeling to evaluate seasonal patterns and the influence of different source regions on the Arctic aerosol population. Furthermore, we compare the aerosol observations to land-based sites across the Arctic, using both long-term measurements and observations during the year of the MOSAiC expedition (2019-2020), to investigate interannual variability and to give context to the aerosol characteristics from within the central Arctic. Our analysis identifies that, overall, the central Arctic exhibits typical seasonal patterns of aerosols, including anthropogenic influence from Arctic haze in winter and secondary aerosol processes in summer. The seasonal pattern corresponds to the global radiation, surface air temperature, and timing of sea ice melting/freezing, which drive changes in transport patterns and secondary aerosol processes. In winter, the Norilsk region in Russia/Siberia was the dominant source of Arctic haze signals in the PNSD and BC observations, which contributed to higher accumulation-mode PNC and BC mass concentrations in the central Arctic than at land-based observatories. We also show that the wintertime Arctic Oscillation (AO) phenomenon, which was reported to achieve a record-breaking positive phase during January-March 2020, explains the unusual timing and magnitude of Arctic haze across the Arctic region compared to longer-term observations. In summer, the aerosol PNCs of the nucleation and Aitken modes are enhanced; however, concentrations were notably lower in the central Arctic over the ice pack than at land-based sites further south. The analysis presented herein provides a current snapshot of Arctic aerosol processes in an environment that is characterized by rapid changes, which will be crucial for improving climate model predictions, understanding linkages between different environmental processes, and investigating the impacts of climate change in future Arctic aerosol studies.
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    Aerosol dynamics and dispersion of radioactive particles
    (Katlenburg-Lindau : European Geosciences Union, 2021) Schoenberg, Pontus von; Tunved, Peter; Grahn, Håkan; Wiedensohler, Alfred; Krejci, Radovan; Brännström, Niklas
    In the event of a failure of a nuclear power plant with release of radioactive material into the atmosphere, dispersion modelling is used to understand how the released radioactivity is spread. For the dispersion of particles, Lagrangian particle dispersion models (LPDMs) are commonly used, in which model particles, representing the released material, are transported through the atmosphere. These model particles are usually inert and undergo only first-order processes such as dry deposition and simplified wet deposition along the path through the atmosphere. Aerosol dynamic processes including coagulation, condensational growth, chemical interactions, formation of new particles and interaction with new aerosol sources are usually neglected in such models. The objective of this study is to analyse the impact of these advanced aerosol dynamic processes if they were to be included in LPDM simulations for use in radioactive preparedness. In this investigation, a fictitious failure of a nuclear power plant is studied for three geographically and atmospherically different sites. The incident was simulated with a Lagrangian single-trajectory box model with a new simulation for each hour throughout a year to capture seasonal variability of meteorology and variation in the ambient aerosol. (a) We conclude that modelling of wet deposition by incorporating an advanced cloud parameterization is advisable, since it significantly influence simulated levels of airborne and deposited activity including radioactive hotspots, and (b) we show that inclusion of detailed ambient-aerosol dynamics can play a large role in the model result in simulations that adopt a more detailed representation of aerosol–cloud interactions. The results highlight a potential necessity for implementation of more detailed representation of general aerosol dynamic processes into LPDMs in order to cover the full range of possible environmental characteristics that can apply during a release of radionuclides into the atmosphere.