• Energy Research
• 7. Clean energy close
• EU close
• IT close
• English close

Comprehensive and reliable information on anthropogenic sources of greenhouse gas emissions is required to track progress towards keeping warming well below 2°C as agreed upon in the Paris Agreement. Here we provide a dataset on anthropogenic GHG emissions 1970-2019 with a broad country and sector coverage. We build the dataset from recent releases from the “Emissions Database for Global Atmospheric Research” (EDGAR) for CO2 emissions from fossil fuel combustion and industry (FFI), CH4 emissions, N2O emissions, and fluorinated gases and use a well-established fast-track method to extend this dataset from 2018 to 2019. We complement this with information on net CO2 emissions from land use, land-use change and forestry (LULUCF) from three available bookkeeping models.

Three data files are provided for Case Study 1 in the openENTRANCE project: Full_potential.V9.csv, metaData.Full_Potential.csv, and acheivable_NUTS2_summary.csv. The data covers 10 residential devices on the NUTS2 level for the EU27 + UK +TR + NO + CH from 2020-2050. The devices included are storage heater, water heater with storage capabilitites, air conditiong, heat circulation pump, air-to-air heat pump, refreigeration (includes refrigerators and freezers), dish washer, washing machine, and tumble drier. Full_potential.V9.csv shows the NUTS2 level unadjusted loads for residential storage heater, water heater, air conditiong, circulation pump, air-to-air heat pump, refreigeration (includes refrigerators and freezers), dish washer, washing machine, and tumble drier using representative hours from 2020-2050. The loads provided here have not been adjusted with the direct load participation rates (see paper for more details). More details on the dataset can be found in the metaData.Full_Potential.csv file. The acheivable_NUTS2_summary.csv shows the NUTS2 level acheivable direct load control potentials for the average hour in the respective year (years - 2020, 2022,2030,2040, 2050).

The goal of WP3 is to develop a design framework for novel ground (slinky/earth basket) type shallow heat exchangers. This design framework, based on developing theoretical models of heat transfer and on experimental data, will be implemented in a design- and engineering calculation tool to support the implementation of these new technologies in the market. The design framework defines the goals of the (thermal and hydraulic) design (especially sizing) of the ground source heat exchanger, as a function of different boundary conditions (building energy demand, soil thermal parameters, required system performance etc.). Moreover, an engineering tool it is aimed at the overall system design and will support the engineer in the choices of heat exchanger technology (vertical, horizontal or earth basket/slinky) and other design parameterizations. This deliverable describes the overall design process and provides information and procedures for data collection and evaluation. The detailed description of the design process for different types of Ground Heat Exchangers is based on the design of the actual GHEX systems implemented in the demo sites of the Geofit project and includes vertical borehole heat exchangers, shallow slinky heat exchangers and earth basket type heat exchangers. This deliverable is suited to be implemented in a design handbook or procedure that can be part of an integrated quality control system.

The EMB3Rs Unified Modelling Platform is a tool to assist on modelling the recovery of excess heat and its reuse to meet final energy demand within and beyond the boundaries of industrial sites. The tool consists of a knowledge base and several simulation modules. This database comprises the research data generated in the course of the EMB3Rs project by using the EMB3Rs platform. The pdf file contains the detailed description of the database content It has been deposited at Zenodo’s open data repository with DOI 10.5281/zenodo.7994255.

This dataset contains the underlying data for the following publication: Song, L., Lieu, J., Nikas, A., Arsenopoulos, A., Vasileiou, G., & Doukas, H. (2020). Contested energy futures, conflicted rewards? Examining low-carbon transition risks and governance dynamics in China's built environment. Energy Research & Social Science, 59, 101306., https://doi.org/10.1016/j.erss.2019.101306. Full details of methods used to create the dataset and provided within this publication.

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).

OSeEM-SN is a tool constructed using Oemof Tabular to apply cross-sectoral approaches for analyzing 100% renewable and sector-coupled sub-national energy systems. The model is validated using the case study of Schleswig-Holstein, Germany. To run the scripts, you need to install Oemof Tabular using the following command- pip install oemof.tabular For details on Oemof Tabular please go through the documentation- https://oemof-tabular.readthedocs.io/ The model uses Oemof-Solph, a model generator for energy system modelling and optimisation. The oemof.solph package is part of the Open energy modelling framework (Oemof). This an organisational framework to bundle tools for energy system modelling. Details on Oemof-Solph is described here- https://github.com/oemof/oemof-solph The article based on the OSeEM-SN based analysis of Schleswig-Holstein is available at- https://www.mdpi.com/2071-1050/13/7/3852 The complete model, including all datasets, scripts, and results are available at: Details are also available at: https://github.com/znes/OSeEM-SN If you have any questions about the model, please contact- mnimaruf@gmail.com

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.