Specification of the desirable and recommended products attributes for generating spatial layers of sea surface temperature for the last 10, 50 and 100 years for the Mediterranean basin and for each NUTS3 region along the coast.

This gridded product visualizes 1960 - 2014 water body dissolved oxygen concentration (umol/l) in the North Sea domain, for each season (winter: December – February; spring: March – May; summer: June – August; autumn: September – November). It is produced as a Diva 4D analysis, version 4.6.11: a reference field of all seasonal data between 1960-2014 was used; results were logit transformed to avoid negative/underestimated values in the interpolated results; error threshold masks L1 (0.3) and L2 (0.5) are included as well as the unmasked field. Every step of the time dimension corresponds to a 10-year moving average for each season. The depth dimension allows visualizing the gridded field at various depths.

This gridded product visualizes 1960 - 2014 water body ammonium concentration (umol/l) in the North Sea domain, for each season (winter: December – February; spring: March – May; summer: June – August; autumn: September – November). It is produced as a Diva 4D analysis, version 4.6.9: a reference field of all seasonal data between 1960-2014 was used; results were logit transformed to avoid negative/underestimated values in the interpolated results; error threshold masks L1 (0.3) and L2 (0.5) are included as well as the unmasked field. Every step of the time dimension corresponds to a 10-year moving average for each season. The depth dimension allows visualizing the gridded field at various depths.

Mediterranean Sea Climatology computed from the SeaDataNet V1.1 aggregated dataset . The version used for the DIVA software is the 4.6.9. The period covers 1900-2013. For data access please register at http://www.marine-id.org

Avec près de 1,4 millions d’hectares de surface agricole utilisée et 100 000 ha d'estives, l'agriculture occupe en 2010 près de 35 % du territoire aquitain. Par son assolement diversifié, elle contribue largement à la diversité des paysages et la structuration de l'espace régional. Toutefois, au cours de la dernière décennie, plus de 96 000 hectares ont quitté le giron de l'agriculture...

Etat d’avancement de la mise en place des Plan de Protection de l'Atmosphère (PPA) 8 mars 2013 (mis à jour le 24 septembre 2015) Afin de mieux répondre à l’urgence sanitaire causée par la pollution atmosphérique dans plusieurs zones du territoire national, une dynamique de mise en révision des Plans de Protection de l’Atmosphère existants et d’élaboration de nouveaux Plans a été lancée dans toutes les zones polluées de France. A l’heure actuelle : On compte 36 PPA en France, dont 28 signés 1 PPA sont en cours de révision 7 PPA sont en cours d’élaboration 47% de la population française est couverte par un PPA

SeaDataNet Temperature and Salinity historical data collection v2, including revised quality flags after quality control with ODV. For data access please register at http://www.marine-id.org

Specification of the desirable and recommended product attributes for generating spatial layers of annual avergae internal energy for the last 20 years.

This gridded product visualizes 1960 - 2014 water body chlorophyll-a (mg/m^3) in the North Sea domain, for each season (winter: December – February; spring: March – May; summer: June – August; autumn: September – November). It is produced as a Diva 4D analysis, version 4.6.11: a reference field of all seasonal data between 1960-2014 was used; results were logit transformed to avoid negative/underestimated values in the interpolated results; error threshold masks L1 (0.3) and L2 (0.5) are included as well as the unmasked field. Every step of the time dimension corresponds to a 10-year moving average for each season. The depth dimension allows visualizing the gridded field at various depths.

This gridded product visualizes 1960 - 2014 water body total nitrogen concentration (umol/l) in the North Sea domain, for each season (winter: December – February; spring: March – May; summer: June – August; autumn: September – November). It is produced as a Diva 4D analysis, version 4.6.11: a reference field of all seasonal data between 1960-2014 was used; results were logit transformed to avoid negative/underestimated values in the interpolated results; error threshold masks L1 (0.3) and L2 (0.5) are included as well as the unmasked field. Every step of the time dimension corresponds to a 10-year moving average for each season. The depth dimension allows visualizing the gridded field at various depths.