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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Mona, Lucia; Amiridis, Vassilis; Cuevas, Emilio; Gkikas, Antonis; +22 Authors

    Authors acknowledge dr Sangboom Ryoo of Korean Meteorological Administration in Seoul for his help and support.The research leading to these results has received funding from the COST ActionCA16202, supported by COST Association (European Cooperation in Science and Technology), from DustClim Project as part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462) and by the European Union’s Horizon 2020 research program for societal challenges – smart, green and integrated transport under grant agreement no.723986 (project EUNADICS-AV – European Natural Disaster Coordination and Information System for Aviation). L. Mona acknowledges the ACTRIS-IMP (Implementation project), funded by the European Union’s Horizon 2020 research and innovation programme (Grant no 871115) and the contribution of the ACTRIS-ITALIA JRU (CNR prot. n. 0067310/2017). S. Basart acknowledges CAMS-84 and CAMS2-82 (part of the Copernicus Atmospheric Monitoring Services, CAMS) and the Spanish Jose Castillejo mobility programme (CAS18/0033). V. Amiridis acknowledges support from the European Research Council (grant no. 725698, D-TECT). A. Gkikas acknowledges support by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “2nd Call for H.F.R.I. Research Projects to support Post-Doctoral Researchers” (project acronym: ATLANTAS, project number: 544). S. Kazadzis acknowledges the ACTRIS-CH (Aerosol, Clouds and Trace Gases Research Infrastructure–- Swiss contribution) funded by the State Secretariat for Education, Research, and Innovation, Switzerland. Work of P. Dagsson-Waldhauserova was partly funded by the Czech Science Foundation (HLD-CHANGE project, no. 20-06168Y). C. Pérez García-Pando acknowledges the long-term support from the AXA Research Fund, as well as the support received through the Ramón y Cajal programme (grant RYC-2015-18690) of the Spanish Ministry of Economy and Competitiveness, and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 773051).B. Weinzierl acknowledges funding under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 640458, A‐LIFE). Mineral dust produced by wind erosion of arid and semi-arid surfaces is a major component of atmospheric aerosol that affects climate, weather, ecosystems, and socio-economic sectors such as human health, transportation, solar energy, and air quality. Understanding these effects and ultimately improving the resilience of affected countries requires a reliable, dense, and diverse set of dust observations, fundamental for the development and the provision of skillful dust forecasts tailored products. The last decade has seen a notable improvement of dust observational capabilities in terms of considered parameters, geographical coverage, and delivery times, as well as of tailored products of interest to both the scientific community and the various end-users. Given this progress, here we review the current state of observational capabilities including in-situ, ground-based and satellite remote sensing observations, in Northern Africa, the Middle East and Europe for the provision of dust information considering the needs of various users. We also critically discuss observational gaps and related unresolved questions while providing suggestions for overcoming the current limitations. Our review aims to be a milestone for discussing dust observational gaps at a global level to address the needs of users, from research communities to nonscientific stakeholders "Article signat per 26 autors/es: Lucia Mona, Vassilis Amiridis, Emilio Cuevas, Antonis Gkikas, Serena Trippetta, Sophie Vandenbussche, Angela Benedetti, Pavla Dagsson-Waldhauserova, Paola Formenti, Alexander Haefele, Stelios Kazadzis, Peter Knippertz, Benoit Laurent, Fabio Madonna, Slobodan Nickovic, Nikolaos Papagiannopoulos, Gelsomina Pappalardo, Carlos Pérez García-Pando, Thomas Popp, Sergio Rodríguez, Andrea Sealy, Nobuo Sugimoto, Enric Terradellas, Ana Vukovic Vimic, Bernadette Weinzierl, and Sara Basart " Peer Reviewed

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CNR ExploRAarrow_drop_down
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    CNR ExploRA
    Article . 2023
    Data sources: CNR ExploRA
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Stewart, Adam; Lehmann, Nils; Corley, Isaac; Chang, Yi-Chia; +4 Authors
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DLR publication serv...arrow_drop_down
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    DLR publication server
    Conference object . 2023
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DLR publication serv...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      DLR publication server
      Conference object . 2023
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Matthias Weigand; Michael Wurm; Ariane Droin; Thomas Stark; +3 Authors

    AbstractGreen space (GS) is a crucial resource in urban areas, but not spatially uniformly distributed. We compare the availability of GS on a national scale using green land cover (GLC) and public green space (PGS). Using spatial census data we analyse GS availability and accessibility for the German population. The average GS availability differs by a factor of three between GLC and PGS. 19.2 % of Germans find less than the WHO defined target for PGS in their neighbourhood. PGS is less equally distributed among the population than GLC, and green space equity varies significantly between rural and urban areas. In areas with multi-family homes, a higher share of the population has access to sufficient PGS than in areas with predominantly single-family homes. We find a negative relation between GLC availability and share of immigrant population, which does not extend to PGS.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Geocarto Internation...arrow_drop_down
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    Geocarto International
    Article . 2023
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Geocarto International; DLR publication server
    Article . 2023 . Peer-reviewed
    License: CC BY
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Geocarto Internation...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Geocarto International
      Article . 2023
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Geocarto International; DLR publication server
      Article . 2023 . Peer-reviewed
      License: CC BY
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    This article examines the current status of quantum computing in Earth observation (EO) and satellite imagery. We analyze the potential limitations and applications of quantum learning models when dealing with satellite data, considering the persistent challenges of profiting from quantum advantage and finding the optimal sharing between high-performance computing (HPC) and quantum computing (QC). We then assess some parameterized quantum circuit models transpiled into a Clifford+T universal gate set. The T-gates shed light on the quantum resources required to deploy quantum models, either on an HPC system or several QC systems. In particular, if the T-gates cannot be simulated efficiently on an HPC system, we can apply a quantum computer and its computational power over conventional techniques. Our quantum resource estimation showed that quantum machine learning (QML) models, with a sufficient number of T-gates, provide the quantum advantage if and only if they generalize on unseen data points better than their classical counterparts deployed on the HPC system and they break the symmetry in their weights at each learning iteration like in conventional deep neural networks. We also estimated the quantum resources required for some QML models as an initial innovation. Lastly, we defined the optimal sharing between an HPC+QC system for executing QML models for hyperspectral satellite images. These are a unique dataset compared to other satellite images since they have a limited number of input qubits and a small number of labeled benchmark images, making them less challenging to deploy on quantum computers. Comment: It could be withdrawn if accepted in IEEE Transaction on Quantum Engineering

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DLR publication serv...arrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    IEEE Transactions on Quantum Engineering
    Article . 2024 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    https://doi.org/10.36227/techr...
    Preprint . 2023
    License: CC BY
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    https://doi.org/10.36227/techr...
    Preprint . 2023
    License: CC BY
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    arXiv.org e-Print Archive
    Other literature type . Preprint . 2023
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    https://doi.org/10.48550/arxiv...
    Article . 2023
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DLR publication serv...arrow_drop_down
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      IEEE Transactions on Quantum Engineering
      Article . 2024 . Peer-reviewed
      License: CC BY
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      https://doi.org/10.36227/techr...
      Preprint . 2023
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      https://doi.org/10.36227/techr...
      Preprint . 2023
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      arXiv.org e-Print Archive
      Other literature type . Preprint . 2023
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      https://doi.org/10.48550/arxiv...
      Article . 2023
      License: CC BY
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    Authors: Ursula Gessner; Sophie Reinermann; Sarah Asam; Claudia Kuenzer;

    Over the past two decades, and particularly since 2018, Central Europe has experienced several droughts with strong impacts on ecosystems and food production. It is expected that under accelerating climate change, droughts and resulting vegetation and ecosystem stress will further increase. Against this background, there is a need for techniques and datasets that allow for monitoring of the timing, extent and effects of droughts. Vegetation indices (VIs) based on satellite Earth observation (EO) can be used to directly assess vegetation stress over large areas. Here, we use a MODIS Enhanced Vegetation Index (EVI) time series to analyze and characterize the vegetation stress on Germany’s croplands and grasslands that has occurred since 2000. A special focus is put on the years from 2018 to 2022, an extraordinary 5-year period characterized by a high frequency of droughts and heat waves. The study reveals strong variations in agricultural drought patterns during the past major drought years in Germany (such as 2003 or 2018), as well as large regional differences in climate-related vegetation stress. The northern parts of Germany showed a higher tendency to be affected by drought effects, particularly after 2018. Further, correlation analyses showed a strong relationship between annual yields of maize, potatoes and winter wheat and previous vegetation stress, where the timing of strongest relationships could be related to crop-specific development stages. Our results support the potential of VI time series for robustly monitoring and predicting effects of climate-related vegetation development and agricultural yields.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Remote Sensingarrow_drop_down
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    Remote Sensing
    Article . 2023
    Data sources: DOAJ
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    Remote Sensing
    Article . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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      Remote Sensing
      Article . 2023
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      Remote Sensing
      Article . 2023 . Peer-reviewed
      License: CC BY
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    Authors: X. Zhao; J. Chen; J. Marshall; M. Gałkowski​​​​​​​; +7 Authors

    To address ambitious goals of carbon neutrality set at national and city scales, a number of atmospheric networks have been deployed to monitor greenhouse gas (GHG) concentrations in and around cities. To convert these measurements into estimates of emissions from cities, atmospheric models are used to simulate the transport of various trace gases and help interpret these measurements. We set up a modelling framework using the Weather Research and Forecasting (WRF) model applied at a high spatial resolution (up to 400 m) to simulate the atmospheric transport of GHGs and attempt a preliminary interpretation of the observations provided by the Munich Urban Carbon Column Network (MUCCnet). Building on previous analyses using similar measurements performed within a campaign for the city of Berlin and its surroundings (Zhao et al., 2019), our modelling framework has been improved regarding the initialization of tagged tracers, model settings, and input data. To assess the model performance, we validate the modelled output against two local weather stations and two radiosonde observations, as well as observed column GHG concentrations. The measurements were provided by the measurement campaign that was carried out from 1 to 30 August 2018. The modelled wind matches well with the measurements from the weather stations, with wind speeds slightly overestimated. In general, the model is able to reproduce the measured slant column concentrations of CH₄ and their variability, while for CO₂, a difference in the slant column CO₂ of around 3.7 ppm is found in the model. This can be attributed to the initial and lateral boundary conditions used for the background tracer. Additional mismatches in the diurnal cycle could be explained by an underestimation of nocturnal respiration in the modelled CO₂ biogenic fluxes. The differential column method (DCM) has been applied to cancel out the influence from the background concentrations. We optimize its application by selecting suitable days on which the assumption of the DCM holds true: a relatively uniform air mass travels over the city, passing from an upwind site to a downwind site. In particular, the Stochastic Time-Inverted Lagrangian Transport (STILT) model is used here and driven by our WRF-modelled meteorological fields to obtain footprints (i.e. the potential areas of influence for signals observed at measurement stations), further used for interpreting measurement results. Combining these footprints with local knowledge of emission sources, we find evidence of CH₄ sources near Munich that are missing or underestimated in the emission inventory used. This demonstrates the potential of this data–model framework to constrain local sources and improve emission inventories. Atmospheric Chemistry and Physics, 23 (22) ISSN:1680-7375 ISSN:1680-7367

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    Atmospheric Chemistry and Physics
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    Authors: Mönnig, Carsten; Schwarz, Egbert;
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    Authors: Kaminski, Tobias; Schwarz, Egbert; Voinov, Sergey;
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    Authors: Aigner, Johanna;
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    Authors: Lennart Lobitz; Hendrik Traub; Mats Overbeck; Maximilian Bień; +4 Authors

    Laminar flow offers significant potential for increasing the energy-efficiency of future transport aircraft. The German Cluster of Excellence SE2A is developing a new approach for hybrid laminar flow control. The concept aims to maintain laminar flow up to 80% of the chord length by integrating suction panels at the rear part of the wing, which consist of a thin suction skin and a supporting core structure. This study examines effects of various suction panel configurations on wing mass and load transfer for an all-electric short-range aircraft. Suction panel material, as well as thickness and relative density of the suction panel core are modified in meaningful boundaries. Suction panels made from Ti6Al4V offer the most robust design resulting in a significant increase in wing mass. For the studied configurations, they represent up to 33.8% of the mass of the wingbox. In contrast, panels made from Nylon11CF or PU1000 do not significantly increase the wing mass. However, the use of these materials raises questions about their robustness under operational conditions. The results demonstrate that the choice of material strongly influences the load path within the wing structure. Ti6Al4V suction panels provide sufficient mechanical properties to significantly contribute to load transfer and buckling stiffness. Locally, the share of load transfer attributed to the suction panel exceeds 50%. In contrast, compliant materials such as Nylon11CF or PU1000 are inherently decoupled from load transfer. Unlike the thickness of the suction skin, the relative density of the core structure strongly affects the wrinkling stiffness. However, wrinkling failure did not appear critical for the examined suction panel configurations. In the present study, the mechanical properties of Ti6Al4V cannot fully be exploited. Therefore, compliant suction panels made from Nylon11CF are preferred in order to achieve a lightweight solution, provided that they meet operational requirements.

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    Aerospace
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    Aerospace
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Mona, Lucia; Amiridis, Vassilis; Cuevas, Emilio; Gkikas, Antonis; +22 Authors

    Authors acknowledge dr Sangboom Ryoo of Korean Meteorological Administration in Seoul for his help and support.The research leading to these results has received funding from the COST ActionCA16202, supported by COST Association (European Cooperation in Science and Technology), from DustClim Project as part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462) and by the European Union’s Horizon 2020 research program for societal challenges – smart, green and integrated transport under grant agreement no.723986 (project EUNADICS-AV – European Natural Disaster Coordination and Information System for Aviation). L. Mona acknowledges the ACTRIS-IMP (Implementation project), funded by the European Union’s Horizon 2020 research and innovation programme (Grant no 871115) and the contribution of the ACTRIS-ITALIA JRU (CNR prot. n. 0067310/2017). S. Basart acknowledges CAMS-84 and CAMS2-82 (part of the Copernicus Atmospheric Monitoring Services, CAMS) and the Spanish Jose Castillejo mobility programme (CAS18/0033). V. Amiridis acknowledges support from the European Research Council (grant no. 725698, D-TECT). A. Gkikas acknowledges support by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “2nd Call for H.F.R.I. Research Projects to support Post-Doctoral Researchers” (project acronym: ATLANTAS, project number: 544). S. Kazadzis acknowledges the ACTRIS-CH (Aerosol, Clouds and Trace Gases Research Infrastructure–- Swiss contribution) funded by the State Secretariat for Education, Research, and Innovation, Switzerland. Work of P. Dagsson-Waldhauserova was partly funded by the Czech Science Foundation (HLD-CHANGE project, no. 20-06168Y). C. Pérez García-Pando acknowledges the long-term support from the AXA Research Fund, as well as the support received through the Ramón y Cajal programme (grant RYC-2015-18690) of the Spanish Ministry of Economy and Competitiveness, and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 773051).B. Weinzierl acknowledges funding under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 640458, A‐LIFE). Mineral dust produced by wind erosion of arid and semi-arid surfaces is a major component of atmospheric aerosol that affects climate, weather, ecosystems, and socio-economic sectors such as human health, transportation, solar energy, and air quality. Understanding these effects and ultimately improving the resilience of affected countries requires a reliable, dense, and diverse set of dust observations, fundamental for the development and the provision of skillful dust forecasts tailored products. The last decade has seen a notable improvement of dust observational capabilities in terms of considered parameters, geographical coverage, and delivery times, as well as of tailored products of interest to both the scientific community and the various end-users. Given this progress, here we review the current state of observational capabilities including in-situ, ground-based and satellite remote sensing observations, in Northern Africa, the Middle East and Europe for the provision of dust information considering the needs of various users. We also critically discuss observational gaps and related unresolved questions while providing suggestions for overcoming the current limitations. Our review aims to be a milestone for discussing dust observational gaps at a global level to address the needs of users, from research communities to nonscientific stakeholders "Article signat per 26 autors/es: Lucia Mona, Vassilis Amiridis, Emilio Cuevas, Antonis Gkikas, Serena Trippetta, Sophie Vandenbussche, Angela Benedetti, Pavla Dagsson-Waldhauserova, Paola Formenti, Alexander Haefele, Stelios Kazadzis, Peter Knippertz, Benoit Laurent, Fabio Madonna, Slobodan Nickovic, Nikolaos Papagiannopoulos, Gelsomina Pappalardo, Carlos Pérez García-Pando, Thomas Popp, Sergio Rodríguez, Andrea Sealy, Nobuo Sugimoto, Enric Terradellas, Ana Vukovic Vimic, Bernadette Weinzierl, and Sara Basart " Peer Reviewed

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    Authors: Stewart, Adam; Lehmann, Nils; Corley, Isaac; Chang, Yi-Chia; +4 Authors
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    Authors: Matthias Weigand; Michael Wurm; Ariane Droin; Thomas Stark; +3 Authors

    AbstractGreen space (GS) is a crucial resource in urban areas, but not spatially uniformly distributed. We compare the availability of GS on a national scale using green land cover (GLC) and public green space (PGS). Using spatial census data we analyse GS availability and accessibility for the German population. The average GS availability differs by a factor of three between GLC and PGS. 19.2 % of Germans find less than the WHO defined target for PGS in their neighbourhood. PGS is less equally distributed among the population than GLC, and green space equity varies significantly between rural and urban areas. In areas with multi-family homes, a higher share of the population has access to sufficient PGS than in areas with predominantly single-family homes. We find a negative relation between GLC availability and share of immigrant population, which does not extend to PGS.

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    This article examines the current status of quantum computing in Earth observation (EO) and satellite imagery. We analyze the potential limitations and applications of quantum learning models when dealing with satellite data, considering the persistent challenges of profiting from quantum advantage and finding the optimal sharing between high-performance computing (HPC) and quantum computing (QC). We then assess some parameterized quantum circuit models transpiled into a Clifford+T universal gate set. The T-gates shed light on the quantum resources required to deploy quantum models, either on an HPC system or several QC systems. In particular, if the T-gates cannot be simulated efficiently on an HPC system, we can apply a quantum computer and its computational power over conventional techniques. Our quantum resource estimation showed that quantum machine learning (QML) models, with a sufficient number of T-gates, provide the quantum advantage if and only if they generalize on unseen data points better than their classical counterparts deployed on the HPC system and they break the symmetry in their weights at each learning iteration like in conventional deep neural networks. We also estimated the quantum resources required for some QML models as an initial innovation. Lastly, we defined the optimal sharing between an HPC+QC system for executing QML models for hyperspectral satellite images. These are a unique dataset compared to other satellite images since they have a limited number of input qubits and a small number of labeled benchmark images, making them less challenging to deploy on quantum computers. Comment: It could be withdrawn if accepted in IEEE Transaction on Quantum Engineering

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    IEEE Transactions on Quantum Engineering
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    https://doi.org/10.36227/techr...
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    https://doi.org/10.36227/techr...
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    https://doi.org/10.48550/arxiv...
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      IEEE Transactions on Quantum Engineering
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      https://doi.org/10.48550/arxiv...
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    Authors: Ursula Gessner; Sophie Reinermann; Sarah Asam; Claudia Kuenzer;

    Over the past two decades, and particularly since 2018, Central Europe has experienced several droughts with strong impacts on ecosystems and food production. It is expected that under accelerating climate change, droughts and resulting vegetation and ecosystem stress will further increase. Against this background, there is a need for techniques and datasets that allow for monitoring of the timing, extent and effects of droughts. Vegetation indices (VIs) based on satellite Earth observation (EO) can be used to directly assess vegetation stress over large areas. Here, we use a MODIS Enhanced Vegetation Index (EVI) time series to analyze and characterize the vegetation stress on Germany’s croplands and grasslands that has occurred since 2000. A special focus is put on the years from 2018 to 2022, an extraordinary 5-year period characterized by a high frequency of droughts and heat waves. The study reveals strong variations in agricultural drought patterns during the past major drought years in Germany (such as 2003 or 2018), as well as large regional differences in climate-related vegetation stress. The northern parts of Germany showed a higher tendency to be affected by drought effects, particularly after 2018. Further, correlation analyses showed a strong relationship between annual yields of maize, potatoes and winter wheat and previous vegetation stress, where the timing of strongest relationships could be related to crop-specific development stages. Our results support the potential of VI time series for robustly monitoring and predicting effects of climate-related vegetation development and agricultural yields.

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    Authors: X. Zhao; J. Chen; J. Marshall; M. Gałkowski​​​​​​​; +7 Authors

    To address ambitious goals of carbon neutrality set at national and city scales, a number of atmospheric networks have been deployed to monitor greenhouse gas (GHG) concentrations in and around cities. To convert these measurements into estimates of emissions from cities, atmospheric models are used to simulate the transport of various trace gases and help interpret these measurements. We set up a modelling framework using the Weather Research and Forecasting (WRF) model applied at a high spatial resolution (up to 400 m) to simulate the atmospheric transport of GHGs and attempt a preliminary interpretation of the observations provided by the Munich Urban Carbon Column Network (MUCCnet). Building on previous analyses using similar measurements performed within a campaign for the city of Berlin and its surroundings (Zhao et al., 2019), our modelling framework has been improved regarding the initialization of tagged tracers, model settings, and input data. To assess the model performance, we validate the modelled output against two local weather stations and two radiosonde observations, as well as observed column GHG concentrations. The measurements were provided by the measurement campaign that was carried out from 1 to 30 August 2018. The modelled wind matches well with the measurements from the weather stations, with wind speeds slightly overestimated. In general, the model is able to reproduce the measured slant column concentrations of CH₄ and their variability, while for CO₂, a difference in the slant column CO₂ of around 3.7 ppm is found in the model. This can be attributed to the initial and lateral boundary conditions used for the background tracer. Additional mismatches in the diurnal cycle could be explained by an underestimation of nocturnal respiration in the modelled CO₂ biogenic fluxes. The differential column method (DCM) has been applied to cancel out the influence from the background concentrations. We optimize its application by selecting suitable days on which the assumption of the DCM holds true: a relatively uniform air mass travels over the city, passing from an upwind site to a downwind site. In particular, the Stochastic Time-Inverted Lagrangian Transport (STILT) model is used here and driven by our WRF-modelled meteorological fields to obtain footprints (i.e. the potential areas of influence for signals observed at measurement stations), further used for interpreting measurement results. Combining these footprints with local knowledge of emission sources, we find evidence of CH₄ sources near Munich that are missing or underestimated in the emission inventory used. This demonstrates the potential of this data–model framework to constrain local sources and improve emission inventories. Atmospheric Chemistry and Physics, 23 (22) ISSN:1680-7375 ISSN:1680-7367

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    Atmospheric Chemistry and Physics
    Article . 2023
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    MPG.PuRe
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    MPG.PuRe
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    Atmospheric Chemistry and Physics (ACP)
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      Atmospheric Chemistry and Physics
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    Authors: Mönnig, Carsten; Schwarz, Egbert;
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    Authors: Kaminski, Tobias; Schwarz, Egbert; Voinov, Sergey;
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    Authors: Aigner, Johanna;
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    Authors: Lennart Lobitz; Hendrik Traub; Mats Overbeck; Maximilian Bień; +4 Authors

    Laminar flow offers significant potential for increasing the energy-efficiency of future transport aircraft. The German Cluster of Excellence SE2A is developing a new approach for hybrid laminar flow control. The concept aims to maintain laminar flow up to 80% of the chord length by integrating suction panels at the rear part of the wing, which consist of a thin suction skin and a supporting core structure. This study examines effects of various suction panel configurations on wing mass and load transfer for an all-electric short-range aircraft. Suction panel material, as well as thickness and relative density of the suction panel core are modified in meaningful boundaries. Suction panels made from Ti6Al4V offer the most robust design resulting in a significant increase in wing mass. For the studied configurations, they represent up to 33.8% of the mass of the wingbox. In contrast, panels made from Nylon11CF or PU1000 do not significantly increase the wing mass. However, the use of these materials raises questions about their robustness under operational conditions. The results demonstrate that the choice of material strongly influences the load path within the wing structure. Ti6Al4V suction panels provide sufficient mechanical properties to significantly contribute to load transfer and buckling stiffness. Locally, the share of load transfer attributed to the suction panel exceeds 50%. In contrast, compliant materials such as Nylon11CF or PU1000 are inherently decoupled from load transfer. Unlike the thickness of the suction skin, the relative density of the core structure strongly affects the wrinkling stiffness. However, wrinkling failure did not appear critical for the examined suction panel configurations. In the present study, the mechanical properties of Ti6Al4V cannot fully be exploited. Therefore, compliant suction panels made from Nylon11CF are preferred in order to achieve a lightweight solution, provided that they meet operational requirements.

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    Aerospace
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    Aerospace
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