Project

Enabling homes to realise zero pollution holds multiple health benefits for all Europeans – especially our children. This is the goal of the EU-funded INQUIRE project.

It will provide the knowledge, tools and measures needed to significantly enhance indoor air quality. Research on hazardous determinants and their sources, risk factors and effects will focus in particular on infants and young children up to 5 years old.

The work will include non-invasive sampling and monitoring of over 200 homes in eight countries over the course of 1 month. Results will inform evidence-based recommendations and support beneficial exploitation by industry and policymakers.

DOI 10.3030/101057499

Inquire in social media:

Project

Climate warming is driven by increased concentrations of greenhouse gasses (GHGs) e.g., CO2 and CH4, in the atmosphere. Existing observatories are able to capture GHG information for large-scale global assessments, but short-term natural variability and climate-driven changes in atmospheric CO2 and CH4 remain less known. There is also currently a lack of sufficiently precise, autonomous, and cost-efficient GHG sensors for GHG monitoring at sufficient spatial scale, and in hard-to-reach areas.

MISO will develop and demonstrate an autonomous in-situ observation platform for use in hard to reach areas (Arctic, wetlands), for detecting and quantifying carbon dioxide and methane gasses, using a combination of stationary and mobile (drone) solutions and requiring minimum on-site intervention when deployed.

To achieve this objective, MISO will improve detection limit and accuracy of a NDIR GHG sensor, which will then be used in three observing platforms (a static tower, a static chamber and a UAV-mounted sensor) operated with the help of a central base unit. All elements will be designed for operation in harsh environments and with minimum human intervention. The static observatories will be powered by a unique geothermal device.

Communication between the three observatories and a data cloud will use a combination of P2P, G4/G5/LTE, LORAWAN and wifi technologies. The specifications of the platform will be co-developed with stakeholders from academia, monitoring and measurement systems, industry and policy.

A clear DCE strategy and focus on short-term impact management and medium and long-term commercialization will target several user groups including industries and representatives of main monitoring systems and infrastructures (e.g., ICOS). This will support innovative governance models and science-based policy design, implementation and monitoring. Sustainability performance and competitiveness in the domains covered by HE Cluster 6 will be enhanced.

Project DOI: https://doi.org/10.3030/101086541

Project

The core objective of FAIRiCUBE is to enable players from beyond classic Earth Observation (EO) domains to provide, access, process, and share gridded data and algorithms in a FAIR and TRUSTable manner.

To reach this objective, we propose creating the FAIRiCUBE HUB, a crosscutting platform and framework for data ingestion, provision, analysis, processing, and dissemination, to unleash the potential of environmental, biodiversity and climate data through dedicated European data spaces.

Within this project, TRL 7 will be attained, together with the necessary governance aspects to assure continued maintenance of the FAIRiCUBE HUB beyond the project lifespan.

This project’s goal is to leverage the power of Machine Learning (ML) operating on multi-thematic datacubes for a broader range of governance and research institutions from diverse fields, who at present cannot easily access and utilize these potent resources.

Selected use cases will illustrate how data-driven projects can benefit from cube formats, infrastructure, and computational benefits. They will guide us in creating a user-friendly FAIRiCUBE HUB, which is tightly integrated to the common European data spaces, providing relevant stakeholders an overview of both data and processing modules readily available to be applied to these data sources.

Tools enabling users not intimately familiar with the worlds of EO and ML to scope the requirements and costs of their desired analyses will be implemented, easing uptake of these resources by a broader community. The FAIR sharing of results with the community will be fostered by providing easy to use tools and workflows directly in the FAIRiCUBE HUB.