Filters

2017 - 201922020 - 20231

More filters

2021 - 20233
Reset filters

Settings

End date: 2023 × Start date: 2020 × Subject: aerosol × Subject: black carbon × Subject: size distribution ×

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Variability of black carbon mass concentrations, sub-micrometer particle number concentrations and size distributions: results of the German Ultrafine Aerosol Network ranging from city street to High Alpine locations
    (Amsterdam [u.a.] : Elsevier Science, 2018) Sun, J.; Birmili, W.; Hermann, M.; Tuch, T.; Weinhold, K.; Spindler, G.; Schladitz, A.; Bastian, S.; Löschau, G.; Cyrys, J.; Gu, J.; Flentje, H.; Briel, B.; Asbac, C.; Kaminski, H.; Ries, L.; Sohme, R.; Gerwig, H.; Wirtz, K.; Meinhardt, F.; Schwerin, A.; Bath, O.; Ma, N.; Wiedensohler, A.
    This work reports the first statistical analysis of multi-annual data on tropospheric aerosols from the German Ultrafine Aerosol Network (GUAN). Compared to other networks worldwide, GUAN with 17 measurement locations has the most sites equipped with particle number size distribution (PNSD) and equivalent black carbon (eBC) instruments and the most site categories in Germany ranging from city street/roadside to High Alpine. As we know, the variations of eBC and particle number concentration (PNC) are influenced by several factors such as source, transformation, transport and deposition. The dominant controlling factor for different pollutant parameters might be varied, leading to the different spatio-temporal variations among the measured parameters. Currently, a study of spatio-temporal variations of PNSD and eBC considering the influences of both site categories and spatial scale is still missing. Based on the multi-site dataset of GUAN, the goal of this study is to investigate how pollutant parameters may interfere with spatial characteristics and site categories. © 2019 The Authors
  • Thumbnail Image
    Item
    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.
  • Thumbnail Image
    Item
    A novel method for deriving the aerosol hygroscopicity parameter based only on measurements from a humidified nephelometer system
    (Katlenburg-Lindau : EGU, 2017) Kuang, Ye; Zhao, Chunsheng; Tao, Jiangchuan; Bian, Yuxuan; Ma, Nan; Zhao, Gang
    Aerosol hygroscopicity is crucial for understanding roles of aerosol particles in atmospheric chemistry and aerosol climate effects. Light-scattering enhancement factor f (RH, λ) is one of the parameters describing aerosol hygroscopicity, which is defined as f (RH, λ) = δsp(RH, λ)=δsp(dry, λ), where δsp(RH, λ) or δsp(dry, λ) represents δsp at wavelength λ under certain relative humidity (RH) or dry conditions. Traditionally, an overall hygroscopicity parameter κ can be retrieved from measured f (RH, λ), hereinafter referred to as κf(RH), by combining concurrently measured particle number size distribution (PNSD) and mass concentration of black carbon. In this paper, a new method is proposed to directly derive κf(RH) based only on measurements from a three-wavelength humidified nephelometer system. The advantage of this newly proposed approach is that κf(RH) can be estimated without any additional information about PNSD and black carbon. This method is verified with measurements from two different field campaigns. Values of κf(RH) estimated from this new method agree very well with those retrieved by using the traditional method: all points lie near the 1 : 1 line and the square of correlation coefficient between them is 0.99. The verification results demonstrate that this newly proposed method of deriving κf(RH) is applicable at different sites and in seasons of the North China Plain and might also be applicable in other regions around the world.