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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: Sepehr Eslami; Jannis M. Hoch; Edwin H. Sutanudjaja; Hal E. Voepel;

    Projections of Sea Level Rise (SLR) under RCP 4.5 and RCP 8.5 (AR5) along the Mekong Coast, Published1 by the Ministry of Natural Resources and Environment (MONRE), Hanoi, Vietnam. Projections of Mekong River discharge during the dry season under RCP 4.5 and RCP 8.5 at Kratie, Cambodia. The data contains the cumulative, minimum and maximum dry season (January-1st to April-30th) discharge from 5 different climate models. PCR-GLOBWB2 was run at 5 arc-min spatial resolution and forced with the data based on output from five ISIMIP CMIP5 global climate models (HadGEM2-ES, GFDL-ESM2, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M). 1. Ministry of Natural Resources and Environment (MONRE), V. Climate change and sea level rise scenarios for Vietnam, Ministry of Natural Resources and Environment. (2016). 2. Sutanudjaja, E. H. et al. PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model. Geosci. Model Dev. 11, 2429–2453 (2018). {"references": ["Sutanudjaja et al. (2018)", "Ministry of Natural Resources and Environment (2016)"]}

    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/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
    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/
    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
      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/
      Smithsonian figshare
      Dataset . 2021
      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/
    Authors: Pappis, Ioannis; Sridharan, Vignesh; Howells, Mark; Medarac, Hrvoje; +4 Authors

    This dataset underpins the study "Synergies and conflicts of energy development and water security in Africa". The study provides insights into energy supply and demand, power generation, investments and total system costs, water consumption and withdrawal as well as carbon dioxide emissions for the African continent. We developed a model to evaluate energy supply and water requirements to cover the energy needs of the African continent during the period 2015-2065. The model was developed using the open-source modeling system for long-term energy planning OSeMOSYS. The objective function is to minimise total energy system costs, rather than, for example, co-optimise the energy and water sectors. Other energy resources were also included in the model except for adding the water analysis, and the dataset was updated based on the latest available information. The OSeMOSYS model developed to conduct the study “Energy projections for African countries”, itself extended from the Electricity Model Base for Africa (TEMBA), was further extended, included exports for all fuels, water loss due to evaporation in hydropower plants and more scenarios examined. Furthermore, the latest available data on the energy system of Africa was also updated. The TEMBA model produces aggregate energy, and detailed power system results in each country in the African continent. The power sector results are also reported with power pool aggregation. The OSeMOSYS model and input data used to produce these results can be found at KTH-dESA/jrc_temba: TEMBA 2.1 (Version v2.1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4889373 (Authors: Ioannis Pappis, Vignesh Sridharan, Will Usher, & Mark Howells. (2021). The initial study was funded by the Joint Research Centre of the European Commission (contract number C936531 - JRC/PTT/2018/C.7/0038/NC).

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    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/
    Smithsonian figshare
    Dataset . 2021
    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/ ZENODOarrow_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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
      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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      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/
      Smithsonian figshare
      Dataset . 2021
      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/
    Authors: Bunyod Holmatov; Arjen Hoekstra; Maarten Krol;

    To reduce greenhouse gas (GHG) emissions, the European Union (EU) has targets for utilizing energy from renewable sources. By 2030, a minimum of 3.5% of energy in the EU���s transport sector should come from renewable biological sources, such as crop residues. This paper analyzed EU���s ���advanced bioethanol��� potential from wheat straw and maize stover and evaluated its environmental (land, water, and carbon) footprint. We differentiated between gross and net bioethanol output, the latter by subtracting the energy inputs in production. Results suggest that the annual amount of the sustainably harvestable wheat straw and maize stover is 81.9 Megatonnes (Mt) at field moisture weight (65.3 Mt as dry weight), yielding 470 PJ as gross (404 PJ as net) advanced bioethanol output. Calculated net advanced bioethanol can replace 2.95% of EU transport sector���s energy consumption. EU���s advanced bioethanol has a land footprint of 0.28 m2 MJ���1 for wheat straw and 0.18 m2 MJ���1 for maize stover. The average water footprint of advanced bioethanol is 173 L MJ���1 for wheat straw and 113 L MJ���1 for maize stover. The average carbon footprint per unit of advanced bioethanol is 19.4 and 19.6 g CO2eq MJ���1 for wheat straw and maize stover, respectively. Using advanced bioethanol can lead to emission savings, but EU���s advanced bioethanol production potential is insufficient to achieve EU���s target of a minimum share of 3.5% of advanced biofuels in the transport sector by 2030, and the associated water and land footprints are not smaller than footprints of conventional bioethanol.

    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/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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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/ ZENODOarrow_drop_down
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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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: Haberl, Helmut; Wiedenhofer, Dominik; Schug, Franz; Frantz, David; +13 Authors

    Dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Building up and maintaining stocks requires large amounts of resources; currently stock-building materials amount to almost 60% of all materials used by humanity. Buildings, infrastructures and machinery shape social practices of production and consumption, thereby creating path dependencies for future resource use. They constitute the physical basis of the spatial organization of most socio-economic activities, for example as mobility networks, urbanization and settlement patterns and various other infrastructures. This dataset features a detailed map of material stocks for the whole of Germany on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors. Temporal extent The map is representative for ca. 2018. Data format Per federal state, the data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. The dataset features area and mass for different street types area and mass for different rail types area and mass for other infrastructure area, volume and mass for different building types Masses are reported as total values, and per material category. Units area in m² height in m volume in m³ mass in t for infrastructure and buildings Further information For further information, please see the publication or contact Helmut Haberl (helmut.haberl@boku.ac.at). A web-visualization of this dataset is available here. Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society. Publication Haberl, H., Wiedenhofer, D., Schug, F., Frantz, D., Virág, D., Plutzar, C., Gruhler, K., Lederer, J., Schiller, G. , Fishman, T., Lanau, M., Gattringer, A., Kemper, T., Liu, G., Tanikawa, H., van der Linden, S., Hostert, P. (accepted): High-resolution maps of material stocks in buildings and infrastructures in Austria and Germany. Environmental Science & Technology Funding This research was primarly funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). ML and GL acknowledge funding by the Independent Research Fund Denmark (CityWeight, 6111-00555B), ML thanks the Engineering and Physical Sciences Research Council (EPSRC; project Multi-Scale, Circular Economic Potential of Non-Residential Building Scale, EP/S029273/1), JL acknowledges funding by the Vienna Science and Technology Fund (WWTF), project ESR17-067, TF acknowledges the Israel Science Foundation grant no. 2706/19.

    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/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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    Authors: Mulder, Karel F.; Ferrer-Balas, Didac; Segalàs Coral, Jordi; Kordas, Olga; +2 Authors

    This chapter presents an overview of positive motivators for students, lecturers, and educational managers to prioritize Sustainable Development in education. Very often, we implicitly assume that students and colleagues should all be motivated by the great challenges that the world faces. And if they appear not to react sufficiently to these challenges, we sometimes tend to give these challenges an apocalyptic character. But is this the right motivator for students and colleagues to work on Sustainable Development? We all know that if you only use a stick and no carrot… So why don’t we use more carrots? The bureaucracy that comes with tools for checking/auditing/evaluating the (SD content of) programs/curricula is not particularly a strong motivator for university lecturers. And building courses that add another subject to the erudition of the graduate might not be the right motivators for students that want to make a difference. We are often still in the process of convincing university managers to add SD to the curriculum, convincing colleagues to address SD, and convincing students to pick SD electives and address SD in their projects. How to motivate them to do this when this gives them no direct personal reward and even might increase their workload? The paper will explore options to develop motivating educating by reviewing case studies on educational renewal in four universities. It concludes that there are various options for more motivating education. However, to fully utilize these options, more priority should be given to education. Peer Reviewed

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    Recolector de Ciencia Abierta, RECOLECTA
    Part of book or chapter of book . 2013 . Peer-reviewed
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    Recolector de Ciencia Abierta, RECOLECTA
    Part of book or chapter of book . Peer-reviewed
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    https://doi.org/10.1007/978-3-...
    Part of book or chapter of book . 2013 . Peer-reviewed
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      Recolector de Ciencia Abierta, RECOLECTA
      Part of book or chapter of book . 2013 . Peer-reviewed
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      Recolector de Ciencia Abierta, RECOLECTA
      Part of book or chapter of book . Peer-reviewed
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      https://doi.org/10.1007/978-3-...
      Part of book or chapter of book . 2013 . Peer-reviewed
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    Authors: Jussi Heinimö; Mirja Mikkilä; Virgilio Panapanaan; Lassi Linnanen; +1 Authors

    PurposeThe purpose of this paper is to outline a comprehensive picture of the coverage of various certification schemes and sustainability principles relating to the entire value‐added chain of biomass and bioenergy and comparing them accordingly.Design/methodology/approachA tri‐dimensional approach (sustainability issues; technical biomass conversion routes; physical trade flows) was developed for testing the coverage of various sustainability dimensions in different phases of the value‐added chain with the chosen certification schemes and sustainability principles.FindingsUsing the tri‐dimensional approach, a comparison of the chosen schemes and principles demonstrated that the application of existing schemes and the development of new ones have placed a major emphasis on the primary production of biomass. Economic and social dimensions related to biofuels and bioenergy processing and trade were either emphasised less or they were covered inadequately. In view of this, the schemes sometimes seem to ignore that the utilisation of renewable energy as such guarantee no positive or neutral climate impact and may not be economically sustainable, especially when bioenergy can often be more expensive than energy generated from fossil energy sources.Originality/valueThe analysis showed that the tri‐dimensional model is an applicable framework that could facilitate policy makers to formulate policies that comprehensively take into consideration the various sustainability dimensions throughout the entire value‐added chain, now and in the future. It can be applied to the future outlining and completion of certification schemes and sustainability principles for biomass and bioenergy, as well as in the testing of their applicability in the implementation.

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    International Journal of Energy Sector Management
    Article . 2009 . Peer-reviewed
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      International Journal of Energy Sector Management
      Article . 2009 . Peer-reviewed
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    Authors: Iakovos T. Michailidis; Thomas Schild; Roozbeh Sangi; Panagiotis Michailidis; +4 Authors

    Abstract A variety of novel, recyclable and reusable, construction materials has already been studied within literature during the past years, aiming at improving the overall energy efficiency ranking of the building envelope. However, several studies show that a delicate control of indoor climating elements can lead to a significant performance improvement by exploiting the building’s savings potential via smart adaptive HVAC regulation to exogenous uncertain disturbances (e.g. weather, occupancy). Building Optimization and Control (BOC) systems can be categorized into two different groups: centralized (requiring high data transmission rates at a central node from every corner of the overall system) and decentralized 1 (assuming an intercommunication among neighboring constituent systems). Moreover, both approaches can be further divided into two subcategories, respectively: model-assisted (usually introducing modeling oversimplifications) and model-free (typically presenting poor stability and very slow convergence rates). This paper presents the application of a novel, decentralized, agent-based , model-free BOC methodology (abbreviated as L4GPCAO) to a modern non-residential building (E.ON. Energy Research Center’s main building), equipped with controllable HVAC systems and renewable energy sources by utilizing the existing Building Management System (BES). The building testbed is located inside the RWTH Aachen University campus in Aachen, Germany. A combined rule criterion composed of the non-renewable energy consumption (NREC) and the thermal comfort index – aligned to international comfort standards – was adopted in all cases presented herein. Besides the limited availability of the specified building testbed, real-life experiments demonstrated operational effectiveness of the proposed approach in BOC applications with complex, emerging dynamics arising from the building’s occupancy and thermal characteristics. L4GPCAO outperformed the control strategy that was designed by the planers and system provider, in a conventional manner, requiring no more than five test days.

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    Applied Energy
    Article . 2018 . Peer-reviewed
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      Applied Energy
      Article . 2018 . Peer-reviewed
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    Authors: Mahima Kalla; Micheal Jerowsky; Benjamin Howes; Ann Borda;

    A key determinant and outcome of successful environmental education is ‘pro-environmental behavior’, i.e., behavior that involves conscious action to mitigate adverse environmental impacts at personal or community level, e.g., reducing resource consumption and waste generation, avoiding toxic substances, and organizing community awareness initiatives. However, some theorists have sought to move away from rationalist models of behavioral modification, towards holistic pedagogical initiatives that seek to develop action competence. In light of the global push towards achievement of the Sustainable Development Goals (SDGs), emerging evidence suggests that education initiatives should foster action competence so students may be equipped to contribute to sustainable development as part of their education. The UNESCO Education for Sustainable Development (ESD) Roadmap 2030 has also identified key priority areas to strengthen ESD in formal curricula. This article reports two informal environmental education initiatives for promoting action competence and pro-environmental behaviors in school-aged children. The authors recommend that formal education settings (e.g., schools) should incorporate self-directed, free-choice project-based learning to augment environmental education programs and promote students’ action competence for contribution to attainment of SDGs. To this end, we propose a Free-Choice Project-based Learning for Action Competence in Sustainable Development (ACiSD) Curriculum, comprising six implementation dimensions, namely: (1) project duration and teaming arrangements, (2) topic selection, (3) student support, (4) teacher support, (5) learning environments, and (6) digital access and equity. For each implementation dimension, we recommend action steps to help educators implement this curriculum in their own educational settings, with the aid of an illustrative worked example.

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    Sustainability
    Article . 2022 . Peer-reviewed
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    Sustainability
    Article . 2022
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    https://dx.doi.org/10.14288/1....
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      Sustainability
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    Authors: Martens, S.; Hangx, S.; Juhlin, C.; Kühn, M.; +1 Authors

    The European Geosciences Union (EGU) brings together geoscientists from all over the world covering all disciplines of the Earth, planetary and space sciences. This geoscientific interdisciplinarity is needed to tackle the challenges of the future. One major challenge for humankind is to provide adequate and reliable supplies of affordable energy and other resources in efficient and environmentally sustainable ways. This Energy Procedia issue provides an overview of the contributions of the Division on Energy, Resources & the Environment (ERE) at the EGU General Assembly 2017.

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    Energy Procedia
    Article . 2017 . Peer-reviewed
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    Authors: Haoxuan Ge; Jue Wang;

    Environmental factors may operate differently when relations are measured across different geographical locations, a phenomenon known as spatial non-stationarity. This study investigates the spatial non-stationarity effect of unhealthy food environments and green spaces on the T2DM prevalence rate at the neighborhood level in Toronto. This study also compares how the results vary between age groups, classified as all adults (20 and above), young adults (from 20 to 44), middle adulthood (from 45 to 64), and seniors (65 and above). The geographically weighted regression model is utilized to explore the impacts of spatial non-stationarity effects on the research results, which may lead to biased conclusions, which have often been ignored in past studies. The results from this study reveal that environmental variables dissimilarly affect T2DM prevalence rates among different age groups and neighborhoods in Toronto after controlling for socioeconomic factors. For example, the green space density yields positive associations with diabetes prevalence rates for elder generations but negative relationships for younger age groups in twenty-two and four neighborhoods, respectively, around Toronto East. The observed associations will provide beneficial suggestions to support government and public health authorities in designing education, prevention, and intervention programs targeting different neighborhoods to control the burden of diabetes.

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    Sustainability
    Article . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Sustainability
    Article . 2023
    Data sources: DOAJ
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      Sustainability
      Article . 2023 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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      Article . 2023
      Data sources: DOAJ
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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: Sepehr Eslami; Jannis M. Hoch; Edwin H. Sutanudjaja; Hal E. Voepel;

    Projections of Sea Level Rise (SLR) under RCP 4.5 and RCP 8.5 (AR5) along the Mekong Coast, Published1 by the Ministry of Natural Resources and Environment (MONRE), Hanoi, Vietnam. Projections of Mekong River discharge during the dry season under RCP 4.5 and RCP 8.5 at Kratie, Cambodia. The data contains the cumulative, minimum and maximum dry season (January-1st to April-30th) discharge from 5 different climate models. PCR-GLOBWB2 was run at 5 arc-min spatial resolution and forced with the data based on output from five ISIMIP CMIP5 global climate models (HadGEM2-ES, GFDL-ESM2, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M). 1. Ministry of Natural Resources and Environment (MONRE), V. Climate change and sea level rise scenarios for Vietnam, Ministry of Natural Resources and Environment. (2016). 2. Sutanudjaja, E. H. et al. PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model. Geosci. Model Dev. 11, 2429–2453 (2018). {"references": ["Sutanudjaja et al. (2018)", "Ministry of Natural Resources and Environment (2016)"]}

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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      Smithsonian figshare
      Dataset . 2021
      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/
    Authors: Pappis, Ioannis; Sridharan, Vignesh; Howells, Mark; Medarac, Hrvoje; +4 Authors

    This dataset underpins the study "Synergies and conflicts of energy development and water security in Africa". The study provides insights into energy supply and demand, power generation, investments and total system costs, water consumption and withdrawal as well as carbon dioxide emissions for the African continent. We developed a model to evaluate energy supply and water requirements to cover the energy needs of the African continent during the period 2015-2065. The model was developed using the open-source modeling system for long-term energy planning OSeMOSYS. The objective function is to minimise total energy system costs, rather than, for example, co-optimise the energy and water sectors. Other energy resources were also included in the model except for adding the water analysis, and the dataset was updated based on the latest available information. The OSeMOSYS model developed to conduct the study “Energy projections for African countries”, itself extended from the Electricity Model Base for Africa (TEMBA), was further extended, included exports for all fuels, water loss due to evaporation in hydropower plants and more scenarios examined. Furthermore, the latest available data on the energy system of Africa was also updated. The TEMBA model produces aggregate energy, and detailed power system results in each country in the African continent. The power sector results are also reported with power pool aggregation. The OSeMOSYS model and input data used to produce these results can be found at KTH-dESA/jrc_temba: TEMBA 2.1 (Version v2.1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4889373 (Authors: Ioannis Pappis, Vignesh Sridharan, Will Usher, & Mark Howells. (2021). The initial study was funded by the Joint Research Centre of the European Commission (contract number C936531 - JRC/PTT/2018/C.7/0038/NC).

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    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/
    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
      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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      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/
      Smithsonian figshare
      Dataset . 2021
      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/
    Authors: Bunyod Holmatov; Arjen Hoekstra; Maarten Krol;

    To reduce greenhouse gas (GHG) emissions, the European Union (EU) has targets for utilizing energy from renewable sources. By 2030, a minimum of 3.5% of energy in the EU���s transport sector should come from renewable biological sources, such as crop residues. This paper analyzed EU���s ���advanced bioethanol��� potential from wheat straw and maize stover and evaluated its environmental (land, water, and carbon) footprint. We differentiated between gross and net bioethanol output, the latter by subtracting the energy inputs in production. Results suggest that the annual amount of the sustainably harvestable wheat straw and maize stover is 81.9 Megatonnes (Mt) at field moisture weight (65.3 Mt as dry weight), yielding 470 PJ as gross (404 PJ as net) advanced bioethanol output. Calculated net advanced bioethanol can replace 2.95% of EU transport sector���s energy consumption. EU���s advanced bioethanol has a land footprint of 0.28 m2 MJ���1 for wheat straw and 0.18 m2 MJ���1 for maize stover. The average water footprint of advanced bioethanol is 173 L MJ���1 for wheat straw and 113 L MJ���1 for maize stover. The average carbon footprint per unit of advanced bioethanol is 19.4 and 19.6 g CO2eq MJ���1 for wheat straw and maize stover, respectively. Using advanced bioethanol can lead to emission savings, but EU���s advanced bioethanol production potential is insufficient to achieve EU���s target of a minimum share of 3.5% of advanced biofuels in the transport sector by 2030, and the associated water and land footprints are not smaller than footprints of conventional bioethanol.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    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/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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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/ ZENODOarrow_drop_down
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      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/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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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: Haberl, Helmut; Wiedenhofer, Dominik; Schug, Franz; Frantz, David; +13 Authors

    Dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Building up and maintaining stocks requires large amounts of resources; currently stock-building materials amount to almost 60% of all materials used by humanity. Buildings, infrastructures and machinery shape social practices of production and consumption, thereby creating path dependencies for future resource use. They constitute the physical basis of the spatial organization of most socio-economic activities, for example as mobility networks, urbanization and settlement patterns and various other infrastructures. This dataset features a detailed map of material stocks for the whole of Germany on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors. Temporal extent The map is representative for ca. 2018. Data format Per federal state, the data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. The dataset features area and mass for different street types area and mass for different rail types area and mass for other infrastructure area, volume and mass for different building types Masses are reported as total values, and per material category. Units area in m² height in m volume in m³ mass in t for infrastructure and buildings Further information For further information, please see the publication or contact Helmut Haberl (helmut.haberl@boku.ac.at). A web-visualization of this dataset is available here. Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society. Publication Haberl, H., Wiedenhofer, D., Schug, F., Frantz, D., Virág, D., Plutzar, C., Gruhler, K., Lederer, J., Schiller, G. , Fishman, T., Lanau, M., Gattringer, A., Kemper, T., Liu, G., Tanikawa, H., van der Linden, S., Hostert, P. (accepted): High-resolution maps of material stocks in buildings and infrastructures in Austria and Germany. Environmental Science & Technology Funding This research was primarly funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). ML and GL acknowledge funding by the Independent Research Fund Denmark (CityWeight, 6111-00555B), ML thanks the Engineering and Physical Sciences Research Council (EPSRC; project Multi-Scale, Circular Economic Potential of Non-Residential Building Scale, EP/S029273/1), JL acknowledges funding by the Vienna Science and Technology Fund (WWTF), project ESR17-067, TF acknowledges the Israel Science Foundation grant no. 2706/19.

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    ZENODO
    Dataset . 2021
    License: CC BY
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    ZENODO
    Dataset . 2021
    License: CC BY
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    ZENODO
    Dataset . 2021
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      ZENODO
      Dataset . 2021
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      ZENODO
      Dataset . 2021
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      ZENODO
      Dataset . 2021
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    Authors: Mulder, Karel F.; Ferrer-Balas, Didac; Segalàs Coral, Jordi; Kordas, Olga; +2 Authors

    This chapter presents an overview of positive motivators for students, lecturers, and educational managers to prioritize Sustainable Development in education. Very often, we implicitly assume that students and colleagues should all be motivated by the great challenges that the world faces. And if they appear not to react sufficiently to these challenges, we sometimes tend to give these challenges an apocalyptic character. But is this the right motivator for students and colleagues to work on Sustainable Development? We all know that if you only use a stick and no carrot… So why don’t we use more carrots? The bureaucracy that comes with tools for checking/auditing/evaluating the (SD content of) programs/curricula is not particularly a strong motivator for university lecturers. And building courses that add another subject to the erudition of the graduate might not be the right motivators for students that want to make a difference. We are often still in the process of convincing university managers to add SD to the curriculum, convincing colleagues to address SD, and convincing students to pick SD electives and address SD in their projects. How to motivate them to do this when this gives them no direct personal reward and even might increase their workload? The paper will explore options to develop motivating educating by reviewing case studies on educational renewal in four universities. It concludes that there are various options for more motivating education. However, to fully utilize these options, more priority should be given to education. Peer Reviewed

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    Recolector de Ciencia Abierta, RECOLECTA
    Part of book or chapter of book . 2013 . Peer-reviewed
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    Recolector de Ciencia Abierta, RECOLECTA
    Part of book or chapter of book . Peer-reviewed
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    https://doi.org/10.1007/978-3-...
    Part of book or chapter of book . 2013 . Peer-reviewed
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      Recolector de Ciencia Abierta, RECOLECTA
      Part of book or chapter of book . 2013 . Peer-reviewed
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      Recolector de Ciencia Abierta, RECOLECTA
      Part of book or chapter of book . Peer-reviewed
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      https://doi.org/10.1007/978-3-...
      Part of book or chapter of book . 2013 . Peer-reviewed
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Jussi Heinimö; Mirja Mikkilä; Virgilio Panapanaan; Lassi Linnanen; +1 Authors

    PurposeThe purpose of this paper is to outline a comprehensive picture of the coverage of various certification schemes and sustainability principles relating to the entire value‐added chain of biomass and bioenergy and comparing them accordingly.Design/methodology/approachA tri‐dimensional approach (sustainability issues; technical biomass conversion routes; physical trade flows) was developed for testing the coverage of various sustainability dimensions in different phases of the value‐added chain with the chosen certification schemes and sustainability principles.FindingsUsing the tri‐dimensional approach, a comparison of the chosen schemes and principles demonstrated that the application of existing schemes and the development of new ones have placed a major emphasis on the primary production of biomass. Economic and social dimensions related to biofuels and bioenergy processing and trade were either emphasised less or they were covered inadequately. In view of this, the schemes sometimes seem to ignore that the utilisation of renewable energy as such guarantee no positive or neutral climate impact and may not be economically sustainable, especially when bioenergy can often be more expensive than energy generated from fossil energy sources.Originality/valueThe analysis showed that the tri‐dimensional model is an applicable framework that could facilitate policy makers to formulate policies that comprehensively take into consideration the various sustainability dimensions throughout the entire value‐added chain, now and in the future. It can be applied to the future outlining and completion of certification schemes and sustainability principles for biomass and bioenergy, as well as in the testing of their applicability in the implementation.

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    International Journal of Energy Sector Management
    Article . 2009 . Peer-reviewed
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      International Journal of Energy Sector Management
      Article . 2009 . Peer-reviewed
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    Authors: Iakovos T. Michailidis; Thomas Schild; Roozbeh Sangi; Panagiotis Michailidis; +4 Authors

    Abstract A variety of novel, recyclable and reusable, construction materials has already been studied within literature during the past years, aiming at improving the overall energy efficiency ranking of the building envelope. However, several studies show that a delicate control of indoor climating elements can lead to a significant performance improvement by exploiting the building’s savings potential via smart adaptive HVAC regulation to exogenous uncertain disturbances (e.g. weather, occupancy). Building Optimization and Control (BOC) systems can be categorized into two different groups: centralized (requiring high data transmission rates at a central node from every corner of the overall system) and decentralized 1 (assuming an intercommunication among neighboring constituent systems). Moreover, both approaches can be further divided into two subcategories, respectively: model-assisted (usually introducing modeling oversimplifications) and model-free (typically presenting poor stability and very slow convergence rates). This paper presents the application of a novel, decentralized, agent-based , model-free BOC methodology (abbreviated as L4GPCAO) to a modern non-residential building (E.ON. Energy Research Center’s main building), equipped with controllable HVAC systems and renewable energy sources by utilizing the existing Building Management System (BES). The building testbed is located inside the RWTH Aachen University campus in Aachen, Germany. A combined rule criterion composed of the non-renewable energy consumption (NREC) and the thermal comfort index – aligned to international comfort standards – was adopted in all cases presented herein. Besides the limited availability of the specified building testbed, real-life experiments demonstrated operational effectiveness of the proposed approach in BOC applications with complex, emerging dynamics arising from the building’s occupancy and thermal characteristics. L4GPCAO outperformed the control strategy that was designed by the planers and system provider, in a conventional manner, requiring no more than five test days.

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    Applied Energy
    Article . 2018 . Peer-reviewed
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      Applied Energy
      Article . 2018 . Peer-reviewed
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    Authors: Mahima Kalla; Micheal Jerowsky; Benjamin Howes; Ann Borda;

    A key determinant and outcome of successful environmental education is ‘pro-environmental behavior’, i.e., behavior that involves conscious action to mitigate adverse environmental impacts at personal or community level, e.g., reducing resource consumption and waste generation, avoiding toxic substances, and organizing community awareness initiatives. However, some theorists have sought to move away from rationalist models of behavioral modification, towards holistic pedagogical initiatives that seek to develop action competence. In light of the global push towards achievement of the Sustainable Development Goals (SDGs), emerging evidence suggests that education initiatives should foster action competence so students may be equipped to contribute to sustainable development as part of their education. The UNESCO Education for Sustainable Development (ESD) Roadmap 2030 has also identified key priority areas to strengthen ESD in formal curricula. This article reports two informal environmental education initiatives for promoting action competence and pro-environmental behaviors in school-aged children. The authors recommend that formal education settings (e.g., schools) should incorporate self-directed, free-choice project-based learning to augment environmental education programs and promote students’ action competence for contribution to attainment of SDGs. To this end, we propose a Free-Choice Project-based Learning for Action Competence in Sustainable Development (ACiSD) Curriculum, comprising six implementation dimensions, namely: (1) project duration and teaming arrangements, (2) topic selection, (3) student support, (4) teacher support, (5) learning environments, and (6) digital access and equity. For each implementation dimension, we recommend action steps to help educators implement this curriculum in their own educational settings, with the aid of an illustrative worked example.

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    Sustainability
    Article . 2022 . Peer-reviewed
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    Sustainability
    Article . 2022
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    https://dx.doi.org/10.14288/1....
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      Sustainability
      Article . 2022 . Peer-reviewed
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      Sustainability
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      https://dx.doi.org/10.14288/1....
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    Authors: Martens, S.; Hangx, S.; Juhlin, C.; Kühn, M.; +1 Authors

    The European Geosciences Union (EGU) brings together geoscientists from all over the world covering all disciplines of the Earth, planetary and space sciences. This geoscientific interdisciplinarity is needed to tackle the challenges of the future. One major challenge for humankind is to provide adequate and reliable supplies of affordable energy and other resources in efficient and environmentally sustainable ways. This Energy Procedia issue provides an overview of the contributions of the Division on Energy, Resources & the Environment (ERE) at the EGU General Assembly 2017.

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    Energy Procedia
    Article . 2017 . Peer-reviewed
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    Energy Procedia
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      Energy Procedia
      Article . 2017 . Peer-reviewed
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      Energy Procedia
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    Authors: Haoxuan Ge; Jue Wang;

    Environmental factors may operate differently when relations are measured across different geographical locations, a phenomenon known as spatial non-stationarity. This study investigates the spatial non-stationarity effect of unhealthy food environments and green spaces on the T2DM prevalence rate at the neighborhood level in Toronto. This study also compares how the results vary between age groups, classified as all adults (20 and above), young adults (from 20 to 44), middle adulthood (from 45 to 64), and seniors (65 and above). The geographically weighted regression model is utilized to explore the impacts of spatial non-stationarity effects on the research results, which may lead to biased conclusions, which have often been ignored in past studies. The results from this study reveal that environmental variables dissimilarly affect T2DM prevalence rates among different age groups and neighborhoods in Toronto after controlling for socioeconomic factors. For example, the green space density yields positive associations with diabetes prevalence rates for elder generations but negative relationships for younger age groups in twenty-two and four neighborhoods, respectively, around Toronto East. The observed associations will provide beneficial suggestions to support government and public health authorities in designing education, prevention, and intervention programs targeting different neighborhoods to control the burden of diabetes.

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    Article . 2023 . Peer-reviewed
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    Article . 2023
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