The Energy Data Innovation Network (EDI-Net) will use smart energy and water meter data to accelerate the implementation of sustainable energy policy. It will do this by increasing the capacity of EU public authorities to act quickly and decisively. The capacity will be increased by the provision of just the right amount of intelligible information, by training and exchange of experiences of Public authorities and by provision of tools and support to implement and monitor their sustainable energy plans. To move beyond the traditional technical energy manager approach to use the information to engage with decision makers, finance mangers and building users. To make energy more “visible”. To make energy and water date “more exciting” to buildings users. Innovation in terms of using big data analytics to address issues at scale. Big data; thousands of EU public buildings; information for decision makers, finance managers and building users; benchmarking of EU public buildings; and monitoring implementation of Sustainable Energy Action Plans or local Climate Protection Plans. The core of EDI-NET is the analysis of smart meter data from buildings, from renewable energy systems and from building energy management systems (BEMS) using Big Data analytics technologies. The attractive fruit around this core is an online forum to spread knowledge and facilitate exchange of experience and best practice through peer to peer education in a friendly and useful way. The tree that supports and ripens the fruit is the existing European network of Climate Alliance that builds the capacity of EU public authorities to more effectively implement sustainable energy policies. We recognise the smart meter data, by themselves, will not implement sustainable energy policy. However, when combined with on-line discussion forum, local campaigns, awareness raising and peer to peer knowledge transfer it can achieve savings of between 5 and 15 percent; at least 16 GWh/yr, worth over 1.5 M€.

The Energy Performance Contracting (EPC) model has been successful in attracting investments in energy efficiency, but mainly for single, large projects. Energy efficiency programs, on the other hand, constitute an alternative path to scaling up the number of buildings that implement energy efficiency interventions, but the practice of rebates and incentives that are paid up front creates a need to rely on deemed energy savings and on complex and costly regulations that hinder innovation. SENSEI will propose a solution to this deadlock. Building on earlier successful experimentation outside of the EU, we will design concepts and business models that will help: (a) generate new sources of benefits that increase the value of an energy retrofit project by enabling the compensation of energy efficiency as an energy resource, and (b) turn the project’s value into an investable asset to attract private financing. The main concept underlying the SENSEI business models is pay-for-performance (P4P), which offers an effective way to engage both energy providers and third-party investorsin energy efficiency. SENSEI will first elaborate P4P schemes for financing energy efficiency that can be implemented across the EU, and then integrate these P4P schemes with the preparation and implementation stages of the EPC model, with the intention of increasing and/or financing the gains in a building’s value that are produced by energy efficiency improvements. The developed concepts will utilize actual building data and the consortium’s competences to carry out a series of negotiation games among all SENSEI parties – representing all links in the EPC and P4P chain. The project has planned a series of activities to both disseminate the insights from these games and to support stakeholders in using our recommendations with the goal of rolling out the first P4P pilots in the EU.

For improving the capabilities of general-purpose AI models and for extending their applicability to domains where the temporal dimension – among several others – is of importance, we will target the development of the next generation of Multimodal Space-Time Foundation Models (MSTFMs). These will combine spatio-temporal understanding, which is important even for modalities such as the visual one that have already been introduced in large generative models, with the effective management of new time-relevant modalities that are yet to be supported in foundation models, such as industrial time series data, remote sensing data and health-related measurements. Real and synthetic data, to mitigate data scarcity, will be leveraged for training general-purpose MSTFMs and for further adapting them for specific downstream tasks. Real data used for training will include data directly provided by members of the consortium as well as data from relevant European Data Spaces, while complementary synthetic data will be generated by exploiting existing generative AI capabilities as well as new ones developed in the project. European HPC infrastructure is directly included in the consortium to ensure the availability of the necessary computing resources.

Mountains cover 30% of the land area and are home to 17% of the EU´s population, meaning that every 6th EU citizen lives in mountainous areas. While we often associate mountains with breathtaking landscapes that offer perfect sites for relaxation, in truth, mountains are much more than that. In fact, mountains play a crucial role in our daily lives by providing vital resources and key community systems to the global population. Mountains like other areas face unprecedented challenges in terms of climate change (CC), however mountain ecosystems are more sensitive to CC. The harmful conditions provoked by CC are exacerbated by the significant deficits in adaptation responses mountainous areas have, stemming from several existing gaps, including shortcomings in CCA options, deficits in the uptake and the lack of coherence. MountResilience has been formulated to increase the adaptation capacity of mountainous regions and communities so as to strengthen climate resilience within the European mountainous biogeographical region (Alpine biogeographical region). The project aims to accelerate the climate resilient transformation of 10 of the most relevant communities and regions located in the mountains in 9 European countries. 6 of the regions will develop and test transformative CCA solutions (technological and social innovations with nature-based solutions at their core). These solutions will address policy, governance, societal needs and behaviours, technological requirements, public and financing targets, and CC risks typical of mountainous areas. Regional quadruple-helix partnerships will use open innovation, participatory decision-making, stakeholder engagement approaches, and effective communication to mobilise, engage, and reach out to key communities. The remaining 4 regions will serve as "replicator" regions, repurposing CCA solutions and lessons learned from the demo regions in their regions through special initiatives to improve their adaptive capacity.

Air pollution in European cities is still threatening human health, even though EU emission directives have been sharpened over the last 25 years. Adverse health effects of airborne particles are strongly linked to their size. A major fraction of outdoor ultrafine particles is traffic generated from road, rail, air, and sea transportation. The story that nPETS aims to communicate is the life of the sub 100 nm emissions from its creation to its potential path to human beings and animals. The nPETS consortium aims to improve the knowledge of transport generated exhaust and non-exhaust nanoparticle emissions and their impacts on health and new public policies. It aims to monitor and sample with state-of-the-art particle instruments the sub 100 nm transport generated emissions from shipping, road, rail, and aviation both in field and controlled laboratory environments. Both aged and fresh aerosols will be considered, including primary and secondary volatile and non-volatile particles. Characterising the emissions will be done from shipping, road, rail, and aviation by linking their sizes, chemical compositions, and morphologies to its specific emission sources such as engines, brakes, clutches, and tyres to increase the understanding of the mechanisms behind adverse risks posed by different types and sources of the identified sub 100 nm particles. The effects of nanoparticles from various transport modes and fuels, as well as specific emission sources, will be compared with a focus on markers of relevance for carcinogenesis and inflammation. Living cells will be exposed to collected and real-world primary and aged aerosols as well as primary and aged aerosols generated in the laboratory. Furthermore, it also aims to evaluate the possible future impact of new policies in this area on public health and linking the impacts with specific emission sources. This should lead to an understanding and quantification of the risks posed by different types and sources.