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The advent of the COVID-19 pandemic led to an economic crisis of the construction industry and to an increasing of energy consumption in the residential sector for all the world. The European Union highlights the crucial role of building sector for both energy gains and economic growth, defining a “Renovation Wave” plan combining regulation, financing and technical support with the aim of greening the buildings, creating jobs and improving lives. In Italy a great support mechanism for energy refurbishment of existing buildings has been launched by means of tax deduction of 110% over 5 years. The present study aims to analyze this new funding mechanism, under energy, environmental and economic point of views. By means of a real case study, representative of highly widespread southern Italy HVAC-building system, it will be highlighting advantages and contradictions of the incentive mechanism developed, proposing possible future improvements. It is found that, if on one hand, the best refurbishment measure under energy/environmental point of view is the external insulation, windows replacement, electric heat pump and PV-system installation, with a global not renewable performance index reduction of 81%, on the other hand it is not the best solution considering the cost/saving ratio.

Abstract Grid-connected renewable energy systems are considered a viable solution for satisfying the swiftly growing demand. Nevertheless, the intermittent nature of renewable energy sources (RESs) hinders their performance and can not be efficiently utilized, rather imposes power quality and instability problem on the grid system. To alleviate this challenge, it is common practice to integrate RESs with efficient battery energy storage technologies. Lead-acid batteries were playing the leading role utilized as stationary energy storage systems. However, currently, there are other battery technologies like lithium-ion (Li-ion), which are used in stationary storage applications though there is uncertainty in its cost-effectiveness. In this paper, a state-of-the-art simulation model and techno-economic analysis of Li-ion and lead-acid batteries integrated with Photovoltaic Grid-Connected System (PVGCS) were performed with consideration of real commercial load profiles and resource data. The Hybrid Optimization Model for Electric Renewables (HOMER) was used for the study of the techno-economic analysis. Besides, the performance of these batteries is greatly affected by the rate of charge and discharge cycling effects which gradually degrades the capacity of the battery. This effect was also investigated with Matlab using a simplified equivalent circuit model by considering a typical stationary application datasheet. The techno-economic simulation output provided that the system with Li-ion battery resulted in a Levelized Cost of Energy (LCOE) of 0.32 €/kWh compared to the system with lead-acid battery with LCOE of 0.34 €/kWh. Besides, the Net Present Cost (NPC) of the system with Li-ion batteries is found to be €14399 compared to the system with the lead-acid battery resulted in an NPC of €15106. According to the result found, Li-ion batteries are techno-economically more viable than lead-acid batteries under the considered specifications and application profile.

Background: Phenolic compounds are food-derived bioactive compounds well-known for their antioxidant and anti-inflammatory properties. They are in the spotlight for the management of diabetes due to their positive effects on glucose homeostasis. Materials and methods: We have performed a literature review on the main topics related to the application of phenolic compounds as functional food ingredients. This includes extraction and purification from vegetable sources and agro-industrial by-products, encapsulation to improve their solubility and bioavailability, and preclinical and clinical evidence linking these compounds with anti-diabetic activity. Objectives: (1) provide an understanding of the role of phenolic compounds on diabetes; (2) identify green technologies for phenolic compounds extraction from agri-food by-products following a biorefinery scheme; (3) underline the relevance of encapsulation techniques using nanotechnology to improve their bioavailability; (4) discuss the therapeutic efficacy of polyphenols. Results: This review compiles recent relevant research on phenolic compounds extraction from renewable resources, their purification from agri-food by-products, and encapsulation strategies using eco-friendly processes. It also highlights the preclinical and clinical evidence on phenolic compounds’ antidiabetic activity, giving insight into their mechanisms of action. Conclusions: This review explores the latest advances in polyphenols and how their benefits in glucose homeostasis can be applied toward improving the health of patients with diabetes and related conditions.

Photovoltaic thermal (PVT) solar collectors can be an effective solution for system output improvement. Photovoltaic thermal collectors naturally have a more expensive receiver than simpler photovo ...

One of the most topical research areas currently concerns the identification and improvement of technologies against climate change, environmental pollution, exploitation of natural resources, and the economic crisis [...]

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.CMCC.CMCC-ESM2.ssp585' 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-ESM2 climate model, released in 2017, 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), ocnBgchem: BFM5.2, 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, ocnBgchem: 100 km, seaIce: 100 km.

This dataset contains the underlying data for the following publication: I. Sognnaes, A. Gambhir, D.-J. Van de Ven, A. Nikas, A. Anger-Kraavi, H. Bui, L. Campagnolo, E. Delpiazzo, H. Doukas, S. Giarola, N. Grant, A. Hawkes, A. Koberle, A. Kolpakov, S. Mittal, J. Moreno, S. Perdana, J. Rogelj, M. Vielle, & G.P. Peters. (2021). A multi-model analysis of long-term emissions and warming implications of current mitigation efforts. Nature Climate Change.

Dataset abstract This dataset contains a mask for the identification of cold and warm temperature advection along the Antarctic Circumnavigation Expedition (ACE) track based on a simple method using the difference between the sea surface and air temperature. This mask is a combination of measured air temperature during ACE and sea surface temperature fields from ECMWF operational analysis data. Dataset contents - coldwarm_mask_1h.csv, data file, comma-separated values - data_file_header.txt, metadata, text - README.txt, metadata, text Dataset license This cold and warm temperature advection mask dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0 The Antarctic Circumnavigation Expedition was made possible by funding from the Swiss Polar Institute and Ferring Pharmaceuticals.