Landslides and gravitational features mapped within French metropolitan EEZ at 1 : 250 000 in the framework of work-package 6 (Geological Events and Probabilities) of the european project EMODNet Geology. These datasets were delivered during the phase 2 of the project.

Wind analyses, estimated over the North Atlantic Ocean with a focus on some specific regions, are one the main ARCWIND (http://www.arcwind.eu/) project deliverables. They are estimated from various remotely sensed wind observations in combination with numerical model (WRF), with regular space (0.25deg in latitude and longitude), and time (00h:00, 06h:00, 12h:00, 18h:00 UTC), and based the method described in (Bentamy A., A. Mouche, A. Grouazel, A. Moujane, M. A. Ahmed. (2019): Using sentinel-1A SAR wind retrievals for enhancing scatterometer and radiometer regional wind analyses . International Journal Of Remote Sensing , 40(3), 1120-1147 . https://doi.org/10.1080/01431161.2018.1524174).

Sediment substrate maps at different scales, of the French metropolitan EEZ produced in the work-package 3 the European project EMODNet Geology (phase IV). Available scales : - 1 : 1 000 000 - 1 : 250 000 - 1 : 100 000 - 1 : 50 000 - 1 : 20 000 - 1 : 15 000 - 1 : 10 000 - 1 : 5 000 Bibliographic references : - Coltman, N., Gilliland, P. & van Heteren, S. 2007. What can I do with my map? In: MESH Guide to Habitat Mapping, MESH Project, 2007, JNCC, Peterborough. Available online at: (http://www.searchmesh.net/default.aspx?page=1900) - Foster-Smith, R., Connor, D. & Davies, J. 2007. What is habitat mapping? In: MESH Guide to Habitat Mapping, MESH Project, 2007, JNCC, Peterborough. Available online at: (http://www.searchmesh.net/default.aspx?page=1900) - Väänänen, T. (ed), Hyvönen, E., Jakonen, M., Kupila, J., Lerrsi, J., Leskinen, J., Liwata, P., Nevalainen, R., Putkinen, S., Virkki, H. 2007. Maaperän yleiskartan tulkinta- ja kartoitusprosessi. Maaperän yleiskartoitus –hankkeen sisäinen raportti. 17 p.

Sediment average grain size in the European North-East Atlantic and Mediterranean waters was generated from Euseamap 2023 sediment categories. This rough granulometry estimate may be used for habitat models at meso- and large scale.

Definition of Classified Shellfish Farming Areas. Boundaries are defined by prefectural classification decrees provided to the International Office for Water (OIEau) by the Departmental Offices for Maritime affairs (DDAM) Annual Layer created by OIEau.

90th percentile calculated during the productive period of the WFD (March-October) from 2015 to 2020, from the MODIS Chl-a algorithm processed by OC5 IFREMER/ARGANS (Gohin et al 2002, Gohin 2011).

A transitional water mass is a discrete and significant element of surface water located near the mouths of rivers or streams, which are partly saline because of their proximity to coastal waters but which are substantially influenced by freshwater currents, constituting the elemental aquatic boundaries destined for the evaluational unit of the DCE. Correspondence DCE reporting: This entity corresponds to the concept of Transitional Water Body (TWBODY) of the WISE.

Cost reductions in nascent forms of Renewable Energy Technology (RET) are essential for them to contribute to the energy mix. Policy intervention can facilitate this cost reduction; however, this may require a significant investment from the public sector. These cost reductions fall into two broad categories: (1) incremental cost reductions through continual improvements to existing technologies, and (2) radical innovation where technologies that significantly differ from the incumbents are developed. This study presents a modelling methodology to integrate radical innovation in RET experience curve and learning investment analysis, using wave energy as an example nascent RET. This aims to quantify the potential effects of radical innovation on the learning investment, allowing the value of successful innovation to be better analysed. The study highlights the value offered by radical innovations in long-term deployment scenarios for wave energy. This suggests that high-risk R&D efforts in nascent RET sectors, even with low success rates, could still present significant expected value in offsetting future revenue support.