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Author: Merkel, Maik × Publisher: Katlenburg-Lindau : Copernicus ×

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    A global analysis of climate-relevant aerosol properties retrieved from the network of Global Atmosphere Watch (GAW) near-surface observatories
    (Katlenburg-Lindau : Copernicus, 2020) Laj, Paolo; Bigi, Alessandro; Rose, Clémence; Andrews, Elisabeth; Lund Myhre, Cathrine; Collaud Coen, Martine; Lin, Yong; Wiedensohler, Alfred; Schulz, Michael; Ogren, John A.; Fiebig, Markus; Prenni, Anthony; Reisen, Fabienne; Romano, Salvatore; Sellegri, Karine; Sharma, Sangeeta; Schauer, Gerhard; Sheridan, Patrick; Sherman, James Patrick; Schütze, Maik; Schwerin, Andreas; Tuch, Thomas; Sohmer, Ralf; Sorribas, Mar; Steinbacher, Martin; Sun, Junying; Titos, Gloria; Toczko, Barbara; Tulet, Pierre; Tunved, Peter; Vakkari, Ville; Velarde, Fernando; Velasquez, Patricio; Villani, Paolo; Vratolis, Sterios; Wang, Sheng-Hsiang; Weinhold, Kay; Gliß, Jonas; Weller, Rolf; Yela, Margarita; Yus-Diez, Jesus; Zdimal, Vladimir; Zieger, Paul; Zikova, Nadezda; Mortier, Augustin; Pandolfi, Marco; Petäja, Tuukka; Kim, Sang-Woo; Aas, Wenche; Putaud, Jean-Philippe; Mayol-Bracero, Olga; Keywood, Melita; Labrador, Lorenzo; Aalto, Pasi; Ahlberg, Erik; Alados Arboledas, Lucas; Alastuey, Andrés; Andrade, Marcos; Artíñano, Begoña; Ausmeel, Stina; Arsov, Todor; Asmi, Eija; Backman, John; Baltensperger, Urs; Bastian, Susanne; Bath, Olaf; Beukes, Johan Paul; Brem, Benjamin T.; Bukowiecki, Nicolas; Conil, Sébastien; Couret, Cedric; Day, Derek; Dayantolis, Wan; Degorska, Anna; Eleftheriadis, Konstantinos; Fetfatzis, Prodromos; Favez, Olivier; Flentje, Harald; Gini, Maria I.; Gregorič, Asta; Gysel-Beer, Martin; Hallar, A. Gannet; Hand, Jenny; Hoffer, Andras; Hueglin, Christoph; Hooda, Rakesh K.; Hyvärinen, Antti; Kalapov, Ivo; Kalivitis, Nikos; Kasper-Giebl, Anne; Kim, Jeong Eun; Kouvarakis, Giorgos; Kranjc, Irena; Krejci, Radovan; Kulmala, Markku; Labuschagne, Casper; Lee, Hae-Jung; Lihavainen, Heikki; Lin, Neng-Huei; Löschau, Gunter; Luoma, Krista; Marinoni, Angela; Martins Dos Santos, Sebastiao; Meinhardt, Frank; Merkel, Maik; Metzger, Jean-Marc; Mihalopoulos, Nikolaos; Nguyen, Nhat Anh; Ondracek, Jakub; Pérez, Noemi; Perrone, Maria Rita; Petit, Jean-Eudes; Picard, David; Pichon, Jean-Marc; Pont, Veronique; Prats, Natalia
    Aerosol particles are essential constituents of the Earth's atmosphere, impacting the earth radiation balance directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei. In contrast to most greenhouse gases, aerosol particles have short atmospheric residence times, resulting in a highly heterogeneous distribution in space and time. There is a clear need to document this variability at regional scale through observations involving, in particular, the in situ near-surface segment of the atmospheric observation system. This paper will provide the widest effort so far to document variability of climate-relevant in situ aerosol properties (namely wavelength dependent particle light scattering and absorption coefficients, particle number concentration and particle number size distribution) from all sites connected to the Global Atmosphere Watch network. High-quality data from almost 90 stations worldwide have been collected and controlled for quality and are reported for a reference year in 2017, providing a very extended and robust view of the variability of these variables worldwide. The range of variability observed worldwide for light scattering and absorption coefficients, single-scattering albedo, and particle number concentration are presented together with preliminary information on their long-term trends and comparison with model simulation for the different stations. The scope of the present paper is also to provide the necessary suite of information, including data provision procedures, quality control and analysis, data policy, and usage of the ground-based aerosol measurement network. It delivers to users of the World Data Centre on Aerosol, the required confidence in data products in the form of a fully characterized value chain, including uncertainty estimation and requirements for contributing to the global climate monitoring system.
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    On the application and grid-size sensitivity of the urban dispersion model CAIRDIO v2.0 under real city weather conditions
    (Katlenburg-Lindau : Copernicus, 2022) Weger, Michael; Baars, Holger; Gebauer, Henriette; Merkel, Maik; Wiedensohler, Alfred; Heinold, Bernd
    There is a gap between the need for city-wide air-quality simulations considering the intra-urban variability and mircoscale dispersion features and the computational capacities that conventional urban microscale models require. This gap can be bridged by targeting model applications on the gray zone situated between the mesoscale and large-eddy scale. The urban dispersion model CAIRDIO is a new contribution to the class of computational-fluid dynamics models operating in this scale range. It uses a diffuse-obstacle boundary method to represent buildings as physical obstacles at gray-zone resolutions in the order of tens of meters. The main objective of this approach is to find an acceptable compromise between computationally inexpensive grid sizes for spatially comprehensive applications and the required accuracy in the description of building and boundary-layer effects. In this paper, CAIRDIO is applied on the simulation of black carbon and particulate matter dispersion for an entire mid-size city using a uniform horizontal grid spacing of 40gm. For model evaluation, measurements from five operational air monitoring stations representative for the urban background and high-traffic roads are used. The comparison also includes the mesoscale host simulation, which provides the boundary conditions. The measurements show a dominant influence of the mixing layer evolution at background sites, and therefore both the mesoscale and large-eddy simulation (LES) results are in good agreement with the observed air pollution levels. In contrast, at the high-traffic sites the proximity to emissions and the interactions with the building environment lead to a significantly amplified diurnal variability in pollutant concentrations. These urban road conditions can only be reasonably well represented by CAIRDIO while the meosocale simulation indiscriminately reproduces a typical urban-background profile, resulting in a large positive model bias. Remaining model discrepancies are further addressed by a grid-spacing sensitivity study using offline-nested refined domains. The results show that modeled peak concentrations within street canyons can be further improved by decreasing the horizontal grid spacing down to 10gm, but not beyond. Obviously, the default grid spacing of 40gm is too coarse to represent the specific environment within narrow street canyons. The accuracy gains from the grid refinements are still only modest compared to the remaining model error, which to a large extent can be attributed to uncertainties in the emissions. Finally, the study shows that the proposed gray-scale modeling is a promising downscaling approach for urban air-quality applications. The results, however, also show that aspects other than the actual resolution of flow patterns and numerical effects can determine the simulations at the urban microscale.