Environmental systems and climate change

We create high-resolution environmental monitoring tools, including micro-climate sensors, remote-sensing devices, and ecological and chemical data collectors. These deployable systems deliver real-time air, water, and ecosystem data, supported by AI, IoT, and satellite communications. Using Digital Twin models, we dynamically track and manage natural resources, while designing sustainable, recyclable sensors for long-term environmental monitoring.

We study and manage water resources under climate and demographic pressures, reconstructing long-term environmental records, refining climate models, and predicting river basin responses. Our tools include real-time flood mapping, decision support systems, and scalable observatories, supported by European networks like eLTER for long-term eco-hydrological monitoring.

We predict and support species and ecosystem adaptation to climate change using advanced modeling and conservation biogeography. Focusing on vulnerable species like pollinators, we develop non-invasive AI-powered monitoring tools to track insects, generate high-resolution data, and ensure resilient, sustainable ecosystems.

We study and manage soil carbon dynamics to mitigate climate change and maintain soil health. Using tools like Environmental assessment of Dynamic Processes - considering time dependency in Life Cycle Assessment (DyPLCA) and LIST's MULTIfunctional SILViculture environmental and economic Assessment tool (Multisilva), we track carbon flows, assess land-use impacts, explore soil-based carbon capture, and support climate-smart land management and regenerative agriculture.