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This dataset, in the context of the MultiPACK Project, describes the development of a CO2 air/water reversible heat pump, specifically investigating the domestic hot water (DHW) production operating mode. A dynamic model of the heat pump is developed with the software Simcenter Amesim. After validation against experimental data, the numerical model is utilized to predict the performance of the heat pump to varying hot water demand, evaporator air inlet conditions and high-pressure value, leading to the discussion of the optimal control strategy. A paper, based on this dataset, "Experimental and numerical investigation of a transcritical CO2 air/water reversible heat pump: analysis of domestic hot water production (14th Gustav Lorentzen Conference, Kyoto, Japan, 6th- 9th December 2020, DOI:10.18462/iir.gl.2020.1160).

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.

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.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CCCR-IITM.IITM-ESM.ssp126' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The IITM-ESM climate model, released in 2015, includes the following components: aerosol: prescribed MAC-v2, atmos: IITM-GFSv1 (T62L64, Linearly Reduced Gaussian Grid; 192 x 94 longitude/latitude; 64 levels; top level 0.2 mb), land: NOAH LSMv2.7.1, ocean: MOM4p1 (tripolar, primarily 1deg; 360 x 200 longitude/latitude; 50 levels; top grid cell 0-10 m), ocnBgchem: TOPAZv2.0, seaIce: SISv1.0. The model was run by the Centre for Climate Change Research, Indian Institute of Tropical Meteorology Pune, Maharashtra 411 008, India (CCCR-IITM) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.

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.

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).

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.CMCC.CMCC-CM2-SR5.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-CM2-SR5 climate model, released in 2016, includes the following components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.

<abstract> <p>The rising proportion of inverter-based renewable energy sources in current power systems has reduced the rotational inertia of overall microgrid systems. This may cause high-frequency fluctuations in the system leading to system instability. Several initiatives have been suggested concerning inertia emulation based on other integrated external energy sources, such as energy storage systems, to combat the ever-declining issue of inertia. Hence, to deal with the aforementioned issue, we suggest the development of an optimal fractional sliding mode control (FSMC)-based frequency stabilization strategy for an industrial hybrid microgrid. An explicit state-space industrial microgrids model comprised of several coordinated energy sources along with loads, storage systems, photovoltaic and wind farms, is considered. In addition to this, the impact of electric vehicles and batteries with adequate control of the state of charge was investigated due to their short regulation times and this helps to balance the power supply and demand that in turn brings the minimization of the frequency deviations. The performance of the FSMC controller is enhanced by setting optimal parameters by employing the tuning strategy based on an iterative teaching-learning-based optimizer (ITLBO). To justify the efficacy of the proposed controller, the simulated results were obtained under several system conditions by using a vehicle simulator in a MATLAB/Simulink environment. The results reveal the enhanced performance of the ITLBO optimized fractional sliding mode control to effectively damp the frequency oscillations and retain the frequency stability with robustness, quick damping, and reliability under different system conditions.</p> </abstract>

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).