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    Knowledge Transfer with Citizen Science: Luft-Leipzig Case Study
    (Basel : MDPI, 2021) Tõnisson, Liina; Voigtländer, Jens; Weger, Michael; Assmann, Denise; Käthner, Ralf; Heinold, Bernd; Macke, Andreas
    Community-based participatory research initiatives such as “hackAir”, “luftdaten.info”, “senseBox”, “CAPTOR”, “CurieuzeNeuzen Vlaanderen”, “communityAQ”, and “Healthy Air, Healthier Children” campaign among many others for mitigating short-lived climate pollutants (SLCPs) and improving air quality have reported progressive knowledge transfer results. These research initiatives provide the research community with the practical four-element state-of-the-art method for citizen science. For the preparation-, measurements-, data analysis-, and scientific support-elements that collectively present the novel knowledge transfer method, the Luft-Leipzig project results are presented. This research contributes to science by formulating a novel method for SLCP mitigation projects that employ citizen scientists. The Luft-Leipzig project results are presented to validate the four-element state-of-the-art method. The method is recommended for knowledge transfer purposes beyond the scope of mitigating short-lived climate pollutants (SLCPs) and improving air quality.
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    CRAAS: A European Cloud Regime dAtAset Based on the CLAAS-2.1 Climate Data Record
    (Basel : MDPI, 2022) Tzallas, Vasileios; Hünerbein, Anja; Stengel, Martin; Meirink, Jan Fokke; Benas, Nikos; Trentmann, Jörg; Macke, Andreas
    Given the important role of clouds in our planet’s climate system, it is crucial to further improve our understanding of their governing processes as well as the resulting spatio-temporal variability of their properties. This co-variability of different cloud optical properties is adequately represented through the well-established concept of cloud regimes. The focus of the present study lies on the creation of a cloud regime dataset over Europe, named “Cloud Regime dAtAset based on the CLAAS-2.1 climate data record” (CRAAS), in order to analyze their variability and their changes at different spatio-temporal scales. In addition, co-occurrences between the cloud regimes and large-scale weather patterns are investigated. The CLoud property dAtAset using Spinning Enhanced Visible and Infrared (SEVIRI) edition 2.1 (CLAAS-2.1) data record, which is produced by the Satellite Application Facility on Climate Monitoring (CM SAF), was used as the basis for the derivation of the cloud regimes over Europe for a 14-year period (2004–2017). In particular, the cloud optical thickness (COT) and cloud top pressure (CTP) products of CLAAS-2.1 were used in order to compute 2D histograms. Then, the k-means clustering algorithm was applied to the generated 2D histograms in order to derive the cloud regimes. Eight cloud regimes were identified, which, along with the geographical distribution of their frequency of occurrence, assisted in providing a detailed description of the climate of the cloud properties over Europe. The annual and diurnal variabilities of the eight cloud regimes were studied, and trends in their frequency of occurrence were also examined. Larger changes in the frequency of occurrence of the produced cloud regimes were found for a regime associated to alto- and nimbo-type clouds and for a regime connected to shallow cumulus clouds and fog (−0.65% and +0.70% for the time period of the study, respectively).
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    From Transfer to Knowledge Co-Production: A Transdisciplinary Research Approach to Reduce Black Carbon Emissions in Metro Manila, Philippines
    (Basel : MDPI, 2020) Tõnisson, Liina; Kunz, Yvonne; Kecorius, Simonas; Madueño, Leizel; Tamayo, Everlyn Gayle; Casanova, Dang Marviluz; Zhao, Qi; Schikowski, Tamara; Hornidge, Anna-Katharina; Wiedensohler, Alfred; Macke, Andreas
    Air pollution, which kills an estimated 7 million people every year, is one of the greatest environmental health risks of our times. Finding solutions to this threat poses challenges to practitioners and policymakers alike. Increasing awareness on the benefits of transdisciplinary research in solution-oriented sustainable development projects has led to the establishment of the research project “A Transdisciplinary Approach to Mitigate Emissions of Black Carbon” (TAME-BC). This paper introduces the TAME-BC research setup that took place with Metro Manila, Philippines, case study. The approach integrates BC measurements with technological, socio-political, and health aspects to improve the scientific state of the art, policymaking, transport sector planning, and clinical studies related to air pollution health effects. The first pillar in the setup presents an (1) air quality assessment through aerosol measurements and instrumentation, complemented by a (2) description and assessment of the current policies, technologies, and practices of the transport sector that is responsible for pollution levels in the Philippines, as well as a (3) BC exposure and associated health impacts assessment. The fourth pillar is intercrossing, fostering (4) knowledge co-creation through stakeholder involvement across scales. We argue that this transdisciplinary approach is useful for research endeavors aiming for emission mitigation in rapidly urbanizing regions beyond Metro Manila.