Innovative Earth observation services in support of maritime litter detection and ship source pollution policies
Funds one demonstration project up to EUR 5 million to build satellite-based tools that detect oil spills, chemical discharges and garbage at sea for EU pollution enforcement.
This is an Innovation Action, evaluated in a single-stage round and paid as a fixed lump sum, with the granting authority explicitly capped at funding one project. The topic follows the ISO 16290:2013 technology-readiness-level definition used specifically for the space sector, rather than the general Horizon Europe TRL scale, and funded work is expected to reach TRL 7-8 by the project's end. Any …
Proposals must develop and demonstrate space sensors — assessing their operational limits and technical confidence — for a defined set of detection cases: oil-spill volume, thickness and type (including in sea ice), chemical products under MARPOL Annex II, sewage under Annex IV, garbage under Annex V, and exhaust-gas-cleaning residue and single-vessel methane emissions under Annex VI, plus identifying the likely polluting vessel from its own spectral signature. Detecting other MARPOL Annex VI emissions is optional and counts as a plus rather than a requirement. Proposals must also design AI methods that identify spills, sewage and garbage with enough timeliness, automation and confidence to avoid false alerts, consulting the yearly-updated Copernicus Security Services Strategic Research Agenda while doing so. Unlike many Horizon Europe topics, this one only requires addressing the gender dimension in the research content if it is actually relevant to the topic's objectives.
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Guides for this application
All guides →Horizon Europe Grants for Startups: A Founder Guide
A practical guide to Horizon Europe grants for startups, including EIC, consortia, eligibility, Funding & Tenders, TRL, budgets, and EU strategy.
Start hereTRL Levels Explained for Deeptech Founders
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DocumentsGrant Work Plan Template: Work Packages, Gantt, Milestones, and Risks
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DocumentsProof-of-Concept Data for Grants: Evidence Examples for Deeptech Applications
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