Climate change poses significant threats to human health and well-being, impacting not only the EU Boreal region but also Europe as a whole. The increasing frequency and severity of extreme events, like floods, wildfires, rising sea levels, and heatwaves have far-reaching consequences for local communities. The need to adapt to climate change's impacts and embrace transformative solutions has garnered recent political attention. Nevertheless, recent extreme incidents, such as the 2021 wildfires in the Boreal region and similar events in Europe, have underscored the imperative of systemic actions and revealed the disproportionate vulnerability of already marginalized populations. The AURORA project aims to enhance resilience against health risks stemming from climate change and contribute to the overarching Mission objectives. It seeks to achieve this by developing a suite of tools capable of: 1) Monitoring climate stressors, 2) Creating climate and epidemiological models 3) Generating forecasts via simulated scenarios 4) Identifying climate change risks and vulnerabilities in the Boreal region. These risks will be complemented by a reliable AI-driven technology that will 5) Issue early warnings and recommend adaptive measures and nature-based solutions. These components will form a robust Decision Support system providing specific recommendations. The AURORA consortium, with its vast experience in research projects, envisions active engagement with stakeholders throughout all project stages via Living Mission Labs. This engagement aims to foster behavioral change and showcase the project's solutions in 5 Demo cities (Riga, Tallinn, Vilnius, Tampere, Pori ) and 3 replicant cities (Klaipeda, Joniskis, Jurmala). The knowledge and insights generated by AURORA will be disseminated through clustering activities, ultimately empowering local policymakers to make evidence-based decisions, reassess strategies, and develop management plans for climate-resilient cities.

The TRIQUETRA project aims at creating an evidence-based assessment platform that allows precise risk stratification, and also creates a database of available mitigation measures and strategies, acting as a Decision Support Tool towards efficient risk mitigation and site remediation. The overall approach of Triquetra is based on three distinct steps: 1. Risk Identification 2. Risk Quantification 3. Risk Mitigation This “trifecta” approach (hence the name Triquetra) creates a framework of risk assessment and risk mitigation so as to tackle as many of these risks as possible, in the most efficient way available. This is further analysed in the following sections.

Space technology connected with Artificial Intelligence and machine learning techniques is one of the most rapidly developing field of science and also play a key role to control disaster by space like Covid-19 outbreak. While space technologies have been successfully applied to a small number of macroeconomy and heath care related matters over the last decade, there is neither a significant utilization of space elements nor a systematic analysis of needs for space assets in this sector yet. There are a significant number of indirect parameters observable from space that can be correlated to the impact on the economy of natural, health (including epidemic) and man-made disasters. Classical environment parameters (geographical, climatological and hydrogeological) and man induced impact on the environment (pollution, heat) can be combined with economic parameters of human activities impacted by the epidemic including transportation, industry, and commerce. Specific human activities can be directly correlated with the progression of the diseases i.e. increase of heat delivered by crematorium in the affected areas as well as in the dwelling areas due to lock-down restrictions. All these “observed parameters” need to be correlated to macro parameters related to the progress of the epidemic and its impact of the of the infection to the economy at different scales. At medium- and long-term time scale, this methodology enables the near real-time monitoring of macroeconomic parameters during the recovery phase following the end of the emergency outbreak. The project EYE intends to propose a prototype service based on Copernicus data, automatic image processing supported by artificial intelligence integrated with modelling and statistic and geospatial data into an IT platform able to provide econometric and epidemiologic nowcasting and forecasting data.

HARMONIA will leverage existing tools, services and novel technologies to deliver an integrated resilience assessment platform working on top of GEOSS, seeing the current lack of a dedicated process of understanding and quantifying Climate Change (CC) effects on urban areas using Satellite and auxiliary data available on GEOSS, DIAS, urban TEP, GEP etc. platforms. HARMONIA will focus on a solution for climate applications supporting adaptation and mitigation measures of the Paris Agreement. HARMONIA will test modern Remote Sensing tools and 3D-4D monitoring, Machine Learning/Deep Learning techniques and develop a modular scalable data-driven multi-layer urban areas observation information knowledge base, using Satellite data time series, spatial information and auxiliary data, in-situ observing systems, which will integrate detailed information on local level of neighborhoods/building blocks. HARMONIA focuses on two pillars: a) Natural and manmade hazards intensified by CC: urban flooding, soil degradation and geo-hazards (landslides, earthquake, ground deformation) and b) Manmade hazards: heat islands, urban heat fluxes, Air Quality, Gas emissions. Sustainable reconstruction of urban areas and the health of humans and ecosystems, are top priorities. HARMONIA will take into account the local ecosystems of European urban areas, following an integrated and sustainable approach by incorporating the active communities’ participation initiative, which will involve the use of a social platform. Paying extra attention to Sustainable Urban Development, one of the Societal Benefit Areas posits that use of EO is a crucial tool towards resilient cities and the assessment of urban footprints, to promote equity, welfare and shared prosperity for all, feed new indicators for the monitoring of progress towards the Sustainable Development Goals in an EU context.

D^2EPC ambitiously aims to set the grounds for the next generation of dynamic Energy Performance Certificates (EPCs) for buildings. The proposed framework sets its foundations on the smart-readiness level of the buildings and the corresponding data collection infrastructure and management systems. It is fed by operational data and adopts the ‘digital twin’ concept to advance Building Information Modelling, calculate a novel set of energy, environmental, financial and human comfort/ wellbeing indicators, and through them the EPC classification of the building in question. Under the project vision, the proposed indicators will render dynamic EPCs a realistic, accurate and comprehensive tool that can lead the transformation of the European building stock into zero-energy buildings and stimulate energy efficient behavioural change of the building occupants. To this direction, D^2EPC proposes a digital platform that will enable the issuance and update of new EPCs on a regular basis, integrate a GIS environment and provide, on top, value added services including user-centred recommendations for energy renovation, benchmarking and forecasting of buildings’ performance as well as performance verification services. The proposed scheme will contribute to the redefinition of EPC-related policies and to the update of current standards, along with guidance for their implementation and will introduce incentivisation and restriction practices into the EPC rationale. Additional benefits include enhanced user awareness and engagement on buildings’ energy efficiency, facilitated planning and decision making on local and regional policy level. To accomplish the above, the D^2EPC framework will be demonstrated in 6 sites, while its 12 partners coming from 7 European countries will collaborate and provide their expertise and resources within the 36 months of the project’s lifetime