Italy – Snow-clearing services – SERVIZIO DI MANUTENZIONE INVERNALE DELLE STRADE E DELLE PIAZZE DEL COMUNE DI LIVIGNO (SGOMBERO NEVE). ANNI 2026/2027 – 2027/2028 - 2028/2029 – 2029/2030. Lotto E – Zona Trepalle e piazzali Foscagno

Italy – Refuse disposal and treatment – SERVIZIO DI TRASPORTO E RECUPERO/SMALTIMENTO DI RIFIUTI CARATTERIZZATI DA CODICE EER 20.01.38 – 15.01.03 – 17.02.01 PROVENIENTI DA RACCOLTA DIFFERENZIATA DELLE PIATTAFORME ECOLOGICHE E CENTRI DI RACCOLTA GESTITI DA AEMME LINEA AMBIENTE SRL.

Italy – Refuse disposal and treatment – SERVIZIO GESTIONE DEI RIFIUTI SPECIALI PERICOLOSI E NON E PER I SERVIZI ECOLOGICI DEL CENTRO RICERCHE DELLA CASACCIA E DELLA SEDE LEGALE ENEA

Italy – Refuse disposal and treatment – Procedura aperta n. 36/2026 - Servizio di smaltimento rifiuti nell'ambito dei lavori Parco Sangone lotto A sub ambito 1 CO 4564 - CUP C17B17000060007

First awarded in fiscal year (FY) 2001, Recovery Land Acquisition grants promote State and Federal cooperation in listed species conservation by leveraging funds to acquire specific parcels of land, through fee simple or conservation easement, in support of U.S. Fish and Wildlife Service (FWS)-approved recovery plans and outlines. The Endangered Species Act (ESA) conveys the importance of recovery plans as a central organizing tool for guiding the recovery process by requiring their development for every listed species.

Germany – Snow-clearing services – Winterdienst und Störungsbeseitigung auf Bundes- und Landesstraßen im Landkreis Weimarer Land - Jahresvertrag 2027 - 2032

Italy – Road construction works – AT1848-26 APPALTO INTEGRATO RIORGANIZZAZIONE OPERA S-369 SS47 DELLA VALSUGANA NEL TRATTO TRA COSTELNUOVO E GRIGNO

The Great British Energy (GBE) Supply Chain Fund: Offshore Wind and Networks will award up to £300 million in capital grant funding to build UK manufacturing capacity for key constrained components in offshore wind and enabling electricity networks sectors. Funding must be used to construct new or extend existing manufacturing facilities in the UK. The application window will close 10 December 2026 (or earlier if the Fund's budget is fully allocated).

Silicon Carbide Cladding Lead Test Rod Development-Phase 1Research, development, and fabrication of Silicon Carbide cladding specimens for research reactor insertion, irradiation, and post-irradiation examinations by 2030. The objective of this program is to advance the scientific and technological maturity of silicon carbide cladding for nuclear fuel rods for future use in commercial light water reactors.

Expected Outcome: The successful proposal is expected to further contribute to the expected outcomes specified in topic HORIZON-CL6-2024-GOVERNANCE-02-01: European Partnership of Agriculture of Data, for continuation of the activities in line with already agreed outcomes. Scope: The objective of this action is to continue to provide support to the European partnership of Agriculture of Data identified in the Horizon Europe Strategic Plan 2021-2024 and first implemented under the topic HORIZON-CL6-2024-GOVERNANCE-02-01: European Partnership of Agriculture of Data, and in particular to fund additional activities (which may also be undertaken by additional partners) in view of its intended scope and duration, and in accordance with Article 24(2) of the Horizon Europe Regulation. The consortium which applied to and received funding under HORIZON-CL6-2024-GOVERNANCE-02-01: European Partnership of Agriculture of Data is uniquely placed to submit a proposal to continue the envisioned partnership. Not only did this consortium submit the proposal leading to the identification of the partnership in the Horizon Europe strategic planning 2021-2024, it has also been implementing the…

Expected Outcome: Projects are expected to contribute to all the following expected outcomes: Effective and innovative methods for gathering, sharing and using large data sets in energy applications for the purpose of training AI models while ensuring privacy and security. Advanced and - wherever possible - open-source AI foundation models to support the digitalisation of the energy system, through improved grid observability, forecasting of supply and demand, advanced storage and renewables integration, demand side flexibility and energy efficiency. Enhanced cooperation, knowledge sharing and interoperability among energy system actors for secure and seamless data exchange. Advanced methodologies for AI model development ensuring that the results are FAIR (Findable, Accessible, Interoperable, Reusable) beyond the project ending, open source and accommodating for technology evolution. Scope: The quality of AI models depends strongly on the amount, quality, and representativeness of the data used for their training. Projects are expected to focus on developing, training and testing AI foundation models, using extensive data sets to accelerate the energy transition in key focus…