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Data set with reference scenarios. As it is not possible to include the entire dataset in this report, we only include two Tables on final energy demand. Table 1 shows the Final Energy Demand projections per industrial subsector and EU28 country in the Reference Scenario and Table 2 the Final Energy Demand projections per industrial subsector and EU28 country in the Frozen Efficiency Scenario. The full dataset, including physical production (in ktonnes) and fuel and electricity demand (in TJ) per industrial sub-sector, per fuel type and per EU 28 country is available upon request to the project coordinator.

Survey of Timisoara City residents conducted by the West University of Timisoara for the SMARTEES project between March and August 2020 (n=439). The survey was aimed at (1) understanding individual behaviours related to the environment and energy in general, and (2) assessing how people make decisions about energy efficiency measures in particular (i.e., perceptions about existing regional or national programmes aiming to improve the energy efficiency of homes through upgrades to the building fabric with a neighbourhood-scale heat network retrofit). It includes data about citizens' attitudes, behaviours and social networks. Files include the dataset in two formats: .csv and .sav. The questionnaire, a data dictionary and background and sampling details are also included.

Dataset supporting publication: “A novel ROM methodology to support the estimation of the energy savings under the Measurement and Verification protocol” (publication available for download: GEOFIT Zenodo) Datasets resultant from simulation of the integrated system into buildings. Conference paper presented in IBPSA-England Building Simulation and Optimisation Conference 2020 This paper presents a novel Reduced Order grey box Model (ROM) methodology, based on a Resistor-Capacitor (RC) network, which supports the creation of the baseline energy consumption and the estimation of energy savings due to Energy Conservation Measures (ECMs) under the Measurement and Verification protocol. Within this scope, a description of the RC network, including a calculation of the parameters’ needed to execute the ROM, are presented. This ROM methodology is demonstrated on an educational building located in Sant Cugat, Spain as part of the H2020 GEOFIT project. The results presented in this paper demonstrate that the ROM is sufficiently accurate for the creation of the baseline energy consumption and for estimating the energy savings of different ECMs.

This dataset was prepared by TNO as a contribution to the H2020 project CHE and the H2020 project VERIFY. The basis is a high-resolution (~1x1 km) emission inventory providing CO2 and CO (from fossil fuels and biofuels separately) over western Europe (2ºW - 19ºE, 47ºN - 56ºN). The reported emissions by European countries to UNFCCC (CO2) and to EMEP/CEIP (CO) have been used and where needed gap-filled or replaced with emission data from the GAINS model. These country-level emissions are disaggregated in space using a consistent spatial distribution methodology, whereas large point sources are listed with their exact locations. This approach is similar to the one described by Kuenen et al., (ACP, 2014). Emissions are reported per GNFR sector, with an extra split for road transport. The emission grids that are part of this dataset are a variation on the base grid, representing the uncertainty in the emission data. Each grid is equally plausible. The grids have been created using a Monte Carlo approach. The uncertainties in the underlying data used to create the base grid (emissions: activity data and emission factors, spatial proxies) have been collected (either from country reports or based on expert judgement). Through the Monte Carlo simulation these uncertainties, taking into account error correlations between some sub-sectors, are combined to create ten new emission grids. The spread in emissions between these emission maps gives an indication of the uncertainty in the emissions. The grid files (in .csv and .nc format) contain annual total emissions per grid cell for the year 2015. A separate file has been prepared for each ensemble member in the Monte Carlo simulation (indicated with M). The unit in the files is kg/yr. A detailed description of the Monte Carlo simulation is presented in: Super, I., Dellaert, S. N. C., Visschedijk, A. J. H., and Denier van der Gon, H. A. C.: Uncertainty analysis of a European high-resolution emission inventory of CO2 and CO to support inverse modelling and network design, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-696, in review, 2019. N.B. It is important to note that 10 maps are not sufficient to describe the sometimes complex uncertainty structures, for example in the case of lognormal uncertainty distributions. The interpretation of the uncertainty based on these 10 maps should therefore be done with care. NB. Despite efforts to prevent negative emissions to occur in the grid maps, some negative values are still present. In local studies this might cause some issues, and we recommend to set negative emissions to zero in those cases.

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).

Data reported by companies on the production, import, export, destruction and feedstock use of fluorinated greenhouse gases in the European Union during the years 2007-2019. The primary data is synthesised and aggregated at EU level and used to assess the progress on HFC phase-down made under both EU legislation and the UN framework as part of the Kigali Amendment to the Montreal Protocol. The data also details the amount of F-gases supplied to various industrial applications.

This article describes an innovative method for measuring lighting levels and other lighting parameters through the use of aerial imagery of towns and cities. Combined with electricity consumption data from smart electricity meters, it was possible to measure the energy efficiency of public lighting installations. The results of this study also confirmed that lighting measurements, installation material, luminaire position, and electricity consumption data can be easily integrated into geographic information systems (GIS). The main advantage of this new methodology is that it provides information about lighting installations in large areas in less time than more conventional procedures. It is thus a more effective way of obtaining the data required to calculate the energy efficiency of lighting levels and electricity consumption. There is even the possibility of generating street lighting maps that provide local administrations with up-to-date information regarding the status of public lighting installations in their city. In this way, modifications or improvements can be made to achieve greater energy savings and, if necessary, to correct the distribution or configuration of public lighting systems to make them more efficient and sustainable. This research studied levels of street lighting and calculated the energy efficiency in various streets of Deifontes (Granada), through the use of aerial imagery.

This study focuses on formulating the most sustainable concrete by incorporating recycled concrete aggregates and other products retrieved from construction and demolition (C&D) activities. Both recycled coarse aggregates (RCA) and recycled fine aggregates (RFA) are firstly used to fully replace the natural coarse and fine aggregates in the concrete mix design. Later, the cement rich ultrafine particles, recycled glass powder and mineral fibres recovered from construction and demolition wastes (CDW) are further incorporated at a smaller rate either as cement substituent or as supplementary additives. Remarkable properties are noticed when the RCA (4–12 mm) and RFA (0.25–4 mm) are fully used to replace the natural aggregates in a new concrete mix. The addition of recycled cement rich ultrafines (RCU), Recycled glass ultrafines (RGU) and recycled mineral fibres (RMF) into recycled concrete improves the modulus of elasticity. The final concrete, which comprises more than 75% (wt.) of recycled components/materials, is believed to be the most sustainable and green concrete mix. Mechanical properties and durability of this concrete have been studied and found to be within acceptable limits, indicating the potential of recycled aggregates and other CDW components in shaping sustainable and circular construction practices. The authors wish to acknowledge the financial support from EU Horizon 2020 Project VEEP ‘‘Cost-Effective Recycling of C&DW in High Added Value Energy Efficient Prefabricated Concrete Compo-nents for Massive Retrofitting of our Built Environment” (No.723582).