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Aerosol activation characteristics and prediction at the central European ACTRIS research station of Melpitz, Germany
2022, Wang, Yuan, Henning, Silvia, Poulain, Laurent, Lu, Chunsong, Stratmann, Frank, Wang, Yuying, Niu, Shengjie, Pöhlker, Mira L., Herrmann, Hartmut, Wiedensohler, Alfred
Understanding aerosol particle activation is essential for evaluating aerosol indirect effects (AIEs) on climate. Long-term measurements of aerosol particle activation help to understand the AIEs and narrow down the uncertainties of AIEs simulation. However, they are still scarce. In this study, more than 4 years of comprehensive aerosol measurements were utilized at the central European research station of Melpitz, Germany, to gain insight into the aerosol particle activation and provide recommendations on improving the prediction of number concentration of cloud condensation nuclei (CCN, NCCN). (1) The overall CCN activation characteristics at Melpitz are provided. As supersaturation (SS) increases from 0.1% to 0.7%, the median NCCN increases from 399 to 2144cm-3, which represents 10% to 48% of the total particle number concentration with a diameter range of 10-800nm, while the median hygroscopicity factor (κ) and critical diameter (Dc) decrease from 0.27 to 0.19 and from 176 to 54nm, respectively. (2) Aerosol particle activation is highly variable across seasons, especially at low-SS conditions. At SSCombining double low line0.1%, the median NCCN and activation ratio (AR) in winter are 1.6 and 2.3 times higher than the summer values, respectively. (3) Both κ and the mixing state are size-dependent. As the particle diameter (Dp) increases, κ increases at Dp of 1/440 to 100nm and almost stays constant at Dp of 100 to 200nm, whereas the degree of the external mixture keeps decreasing at Dp of 1/440 to 200nm. The relationships of κ vs. Dp and degree of mixing vs. Dp were both fitted well by a power-law function. (4) Size-resolved κ improves the NCCN prediction. We recommend applying the κ-Dp power-law fit for NCCN prediction at Melpitz, which performs better than using the constant κ of 0.3 and the κ derived from particle chemical compositions and much better than using the NCCN (AR) vs. SS relationships. The κ-Dp power-law fit measured at Melpitz could be applied to predict NCCN for other rural regions. For the purpose of improving the prediction of NCCN, long-term monodisperse CCN measurements are still needed to obtain the κ-Dp relationships for different regions and their seasonal variations.
The value of remote marine aerosol measurements for constraining radiative forcing uncertainty
2020, Regayre, Leighton A., Schmale, Julia, Johnson, Jill S., Tatzelt, Christian, Baccarini, Andrea, Henning, Silvia, Yoshioka, Masaru, Stratmann, Frank, Gysel-Beer, Martin, Grosvenor, Daniel P., Carslaw, Ken S.
Aerosol measurements over the Southern Ocean are used to constrain aerosol-cloud interaction radiative forcing (RFaci) uncertainty in a global climate model. Forcing uncertainty is quantified using 1 million climate model variants that sample the uncertainty in nearly 30 model parameters. Measurements of cloud condensation nuclei and other aerosol properties from an Antarctic circumnavigation expedition strongly constrain natural aerosol emissions: default sea spray emissions need to be increased by around a factor of 3 to be consistent with measurements. Forcing uncertainty is reduced by around 7% using this set of several hundred measurements, which is comparable to the 8% reduction achieved using a diverse and extensive set of over 9000 predominantly Northern Hemisphere measurements. When Southern Ocean and Northern Hemisphere measurements are combined, uncertainty in RFaci is reduced by 21 %, and the strongest 20% of forcing values are ruled out as implausible. In this combined constraint, observationally plausible RFaci is around 0.17Wm-2 weaker (less negative) with 95% credible values ranging from-2:51 to-1:17Wm-2 (standard deviation of-2:18 to-1:46Wm-2). The Southern Ocean and Northern Hemisphere measurement datasets are complementary because they constrain different processes. These results highlight the value of remote marine aerosol measurements. © 2020 Laser Institute of America. All rights reserved.
Marine organic matter in the remote environment of the Cape Verde islands-an introduction and overview to the MarParCloud campaign
2020, van Pinxteren, Manuela, Fomba, KhannehWadinga, Triesch, Nadja, Stolle, Christian, Wurl, Oliver, Bahlmann, Enno, Gong, Xianda, Voigtländer, Jens, Wex, Heike, Robinson, Tiera-Brandy, Barthel, Stefan, Zeppenfeld, Sebastian, Hoffmann, Erik Hans, Roveretto, Marie, Li, Chunlin, Grosselin, Benoit, Daële, Veronique, Senf, Fabian, van Pinxteren, Dominik, Manzi, Malena, Zabalegui, Nicolás, Frka, Sanja, Gašparović, Blaženka, Pereira, Ryan, Li, Tao, Wen, Liang, Li, Jiarong, Zhu, Chao, Chen, Hui, Chen, Jianmin, Fiedler, Björn, von Tümpling, Wolf, Read, Katie Alana, Punjabi, Shalini, Lewis, Alastair Charles, Hopkins, James Roland, Carpenter, Lucy Jane, Peeken, Ilka, Rixen, Tim, Schulz-Bull, Detlef, Mong, María Eugenia, Mellouki, Abdelwahid, George, Christian, Stratmann, Frank, Herrmann, Hartmut
The project MarParCloud (Marine biological production, organic aerosol Particles and marine Clouds: a process chain) aims to improve our understanding of the genesis, modification and impact of marine organic matter (OM) from its biological production, to its export to marine aerosol particles and, finally, to its ability to act as ice-nucleating particles (INPs) and cloud condensation nuclei (CCN). A field campaign at the Cape Verde Atmospheric Observatory (CVAO) in the tropics in September-October 2017 formed the core of this project that was jointly performed with the project MARSU (MARine atmospheric Science Unravelled). A suite of chemical, physical, biological and meteorological techniques was applied, and comprehensive measurements of bulk water, the sea surface microlayer (SML), cloud water and ambient aerosol particles collected at a ground-based and a mountain station took place. Key variables comprised the chemical characterization of the atmospherically relevant OM components in the ocean and the atmosphere as well as measurements of INPs and CCN. Moreover, bacterial cell counts, mercury species and trace gases were analyzed. To interpret the results, the measurements were accompanied by various auxiliary parameters such as air mass back-trajectory analysis, vertical atmospheric profile analysis, cloud observations and pigment measurements in seawater. Additional modeling studies supported the experimental analysis. During the campaign, the CVAO exhibited marine air masses with low and partly moderate dust influences. The marine boundary layer was well mixed as indicated by an almost uniform particle number size distribution within the boundary layer. Lipid biomarkers were present in the aerosol particles in typical concentrations of marine background conditions. Accumulation-and coarse-mode particles served as CCN and were efficiently transferred to the cloud water. The ascent of ocean-derived compounds, such as sea salt and sugar-like compounds, to the cloud level, as derived from chemical analysis and atmospheric transfer modeling results, denotes an influence of marine emissions on cloud formation. Organic nitrogen compounds (free amino acids) were enriched by several orders of magnitude in submicron aerosol particles and in cloud water compared to seawater. However, INP measurements also indicated a significant contribution of other non-marine sources to the local INP concentration, as (biologically active) INPs were mainly present in supermicron aerosol particles that are not suggested to undergo strong enrichment during ocean-atmosphere transfer. In addition, the number of CCN at the supersaturation of 0.30 % was about 2.5 times higher during dust periods compared to marine periods. Lipids, sugar-like compounds, UV-absorbing (UV: ultraviolet) humic-like substances and low-molecularweight neutral components were important organic compounds in the seawater, and highly surface-active lipids were enriched within the SML. The selective enrichment of specific organic compounds in the SML needs to be studied in further detail and implemented in an OM source function for emission modeling to better understand transfer patterns, the mechanisms of marine OM transformation in the atmosphere and the role of additional sources. In summary, when looking at particulate mass, we see oceanic compounds transferred to the atmospheric aerosol and to the cloud level, while from a perspective of particle number concentrations, sea spray aerosol (i.e., primary marine aerosol) contributions to both CCN and INPs are rather limited. © Author(s) 2020.