Climate and Environmental Digital Twins for Human Health: Leveraging Earth Observation for Compound Climate and Air Quality Extremes Early Warning

Climate resilience is a defining challenge of the 21st century, yet public health authorities continue to face difficulties in operationalising state-of-the-art geospatial and environmental science. In Portugal, as in Europe more broadly, extreme temperatures have already increased in frequency and severity, contributing to substantial excess mortality and morbidity. These impacts are often amplified by the simultaneous degradation of air quality. However, evidence has largely been event-specific, fragmented across case studies of individual heatwaves, cold waves, or air-quality episodes, limiting our ability to implement early-warning systems. The ESA-funded AIR4health project, developed under the Early Digital Twin Components initiative, addresses these gaps by designing innovative algorithms to predict human mortality and morbidity during compound extreme events. The project develops two Machine Learning (ML)–based AIR4health Risk Algorithms focusing on (1) Heat & Ozone and (2) Cold & Nitrogen Dioxide, using a two-decades-long, high-resolution healthcare database for mainland Portugal. These indicators will integrate EO data, in-situ air-quality records from the EEA, and CAMS/C3S model outputs. Satellite and model data are dynamically downscaled using approaches previously demonstrated for air-temperature modelling in Lisbon, enabling daily, spatially detailed (municipal-level) time series of compound extreme events. AIR4health advances beyond current country-level systems by implementing fully spatiotemporal exposure–response modelling. Its dynamic and continuous framework will deliver a prototype DTC capable of providing fine-scale early warning for combined climate and air-quality extremes. By benchmarking results against European-level datasets, AIR4health will support scalable pathways towards relevant practices in planetary health and climate-preparedness, while contributing to the broader European Digital Twin ecosystem.