2-P1 BlueOFS

Blue Carbon – a mission to maximise C storage in Danish marine ecosystems

Blue Carbon (BC) refers to organic carbon that is captured and stored by the oceans and coastal ecosystems, in Denmark particularly by vegetated coastal ecosystems: seagrass meadows and tidal marshes. Global interest in BC is rooted in its potential to mitigate climate change by carbon sequestration while achieving co-benefits, such as coastal protection, biodiversity increase and fisheries enhancement.

Blue carbon ecosystems could under optimal conditions remove 0.5% of current emissions, with co-benefits for local ecosystems and livelihoods. These include improved water quality; increased marine and terrestrial biodiversity; preservation of livelihoods, cultural practices, and values of local and traditional communities; and the protection of shorelines and their resilience in the face of climate change.

Carbon storage in the marine environment (blue carbon) requires identification of existing habitat coverage and suitable areas for restoration. Furthermore, to achieve climate meaningful scales, restoration and conservation actions must be upscaled to national and global level


4.508.465 DKK

Funding from IFD: 3.232.119 DKK
Financing from project partners: 1.276.346 DKK

Project lead

Paula Canal-Vergés


The project will identify the total carbon capture/storage capacity in Odense fjord under current conditions. However, due to the fjord’s eutrophication state, it is limited. Hence the project will locate NBS in the catchment area, to reduce nutrient loading to the fjord, hence increase blue carbon capacity. Odense fjord and catchment/sub-catchment area will be used as a pilot study for national upscaling. The project will run diverse possible scenarios in which we optimise and upscale the use of NbS inland and at the fjord to increase overall carbon capture/storage capacity.

The project will enable site and nature-based-solution selection to maximise spatial and temporal carbon capture, i.e., quantification the overall C capture/storage capacity for a selection of NBSs active at the studied catchment area.

  1. Combine machine learning techniques on satellite / aerial images with topographical data and monitored data.
  2. Quantify the modelled direct and indirect effects of the existing carbon hotspots.
  3. Simulate potential upscaling scenarios.
  4. Provide a road map on how to apply and/or scale up blue carbon capture.