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- ItemUnderstanding aerosol microphysical properties from 10 years of data collected at Cabo Verde based on an unsupervised machine learning classification(Katlenburg-Lindau : EGU, 2022) Gong, Xianda; Wex, Heike; Müller, Thomas; Henning, Silvia; Voigtländer, Jens; Wiedensohler, Alfred; Stratmann, FrankThe Cape Verde Atmospheric Observatory (CVAO), which is influenced by both marine and desert dust air masses, has been used for long-term measurements of different properties of the atmospheric aerosol from 2008 to 2017. These properties include particle number size distributions (PNSD), light-absorbing carbon (LAC) and concentrations of cloud condensation nuclei (CCN) together with their hygroscopicity. Here we summarize the results obtained for these properties and use an unsupervised machine learning algorithm for the classification of aerosol types. Five types of aerosols, i.e., marine, freshly formed, mixture, moderate dust and heavy dust, were classified. Air masses during marine periods are from the Atlantic Ocean and during dust periods are from the Sahara Desert. Heavy dust was more frequently present during wintertime, whereas the clean marine periods were more frequently present during springtime. It was observed that during the dust periods CCN number concentrations at a supersaturation of 0.30g% were roughly 2.5 times higher than during marine periods, but the hygroscopicity (κ) of particles in the size range from g1/4g30 to g1/4g175gnm during marine and dust periods were comparable. The long-term data presented here, together with the aerosol classification, can be used as a basis to improve our understanding of annual cycles of the atmospheric aerosol in the eastern tropical Atlantic Ocean and on aerosol-cloud interactions and it can be used as a basis for driving, evaluating and constraining atmospheric model simulations.
- ItemDecreasing trends of particle number and black carbon mass concentrations at 16 observational sites in Germany from 2009 to 2018(Katlenburg-Lindau : EGU, 2020) Sun, Jia; Birmili, Wolfram; Hermann, Markus; Tuch, Thomas; Weinhold, Kay; Merkel, Maik; Rasch, Fabian; Müller, Thomas; Schladitz, Alexander; Bastian, Susanne; Löschau, Gunter; Cyrys, Josef; Gu, Jianwei; Flentje, Harald; Briel, Björn; Asbach, Christoph; Kaminski, Heinz; Ries, Ludwig; Sohmer, Ralf; Gerwig, Holger; Wirtz, Klaus; Meinhardt, Frank; Schwerin, Andreas; Bath, Olaf; Ma, Nan; Wiedensohler, AlfredAnthropogenic emissions are dominant contributors to air pollution. Consequently, mitigation policies have been attempted since the 1990s in Europe to reduce pollution by anthropogenic emissions. To evaluate the effectiveness of these mitigation policies, the German Ultrafine Aerosol Network (GUAN) was established in 2008, focusing on black carbon (BC) and sub-micrometre aerosol particles. In this study, long-term trends of atmospheric particle number concentrations (PNCs) and equivalent BC (eBC) mass concentration over a 10-year period (2009-2018) were determined for 16 GUAN sites ranging from roadside to high Alpine environments. Overall, statistically significant decreasing trends are found for most of these parameters and environments in Germany. The annual relative slope of eBC mass concentration varies between-13.1% and-1.7% per year. The slopes of the PNCs vary from-17.2% to-1.7 %,-7.8% to-1.1 %, and-11.1% to-1.2% per year for 10-30, 30-200, and 200-800 nm size ranges, respectively. The reductions in various anthropogenic emissions are found to be the dominant factors responsible for the decreasing trends of eBC mass concentration and PNCs. The diurnal and seasonal variations in the trends clearly show the effects of the mitigation policies for road transport and residential emissions. The influences of other factors such as air masses, precipitation, and temperature were also examined and found to be less important or negligible. This study proves that a combination of emission mitigation policies can effectively improve the air quality on large spatial scales. It also suggests that a long-term aerosol measurement network at multi-type sites is an efficient and necessary tool for evaluating emission mitigation policies. © 2020 Author(s).