SOURCE-LINKED INTELLIGENCE
AI-driven Early Warnings System for Compound Environmental Health Risks in Europe
AI-driven Early Warnings System for Compound Environmental Health Risks in Europe In recent years, rapid advances in artificial intelligence have revolutionised atmospheric forecasting, giving rise to AI-based weather prediction models (AIWPs) that collapse forecast runtimes from hours on supercomputers to minutes on a single GPU, while rivalling the skill of state-of-the-art numerical weather prediction models (NWPs). Yet this disruptive capacity remains largely untapped in public health, even as Europe faces escalating extremes of heat and air pollution. Crucially, hazards no longer occur in isolation: compound heat-air-pollution events are rising in frequency, duration and severity, disproportionately amplifying health inequalities. However, current health early warning systems (HEWS) still treat temperature and air pollution separately and issue uniform alerts, leaving those most at risk under-informed. It remains completely unexplored whether HEWS can deliver equally accurate warnings across popul
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 194074.56
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T05:31:32.981Z. This is not the publication date.