Assessing the potential for sea-based macroalgae cultivation and its application for nutrient removal in the Baltic Sea

Marine eutrophication is a pervasive and growing threat to global sustainability. Macroalgal cultivation is a promising circular economy solution to achieve nutrient reduction and food security. However, the location of production hotspots is not well known. In this paper the production potential of macroalgae of high commercial value was predicted across the Baltic Sea region. In addition, the nutrient limitation within and adjacent to macroalgal farms was investigated to suggest optimal site-specific configuration of farms. The production potential of Saccharina latissima was largely driven by salinity and the highest production yields are expected in the westernmost Baltic Sea areas where salinity is >23. The direct and interactive effects of light availability, temperature, salinity and nutrient concentrations regulated the predicted changes in the production of Ulva intestinalis and Fucus vesiculosus. The western and southern Baltic Sea exhibited the highest farming potential for these species, with promising areas also in the eastern Baltic Sea. Macroalgal farming did not induce significant nutrient limitation. The expected spatial propagation of nutrient limitation caused by macroalgal farming was less than 100–250 m. Higher propagation distances were found in areas of low nutrient and low water exchange (e.g. offshore areas in the Baltic Proper) and smaller distances in areas of high nutrient and high water exchange (e.g. western Baltic Sea and Gulf of Riga). The generated maps provide the most sought-after input to support blue growth initiatives that foster the sustainable development of macroalgal cultivation and reduction of in situ nutrient loads in the Baltic Sea.</p

Effects of Nutrient Management Scenarios on Marine Eutrophication Indicators: A Pan-European, Multi-Model Assessment in Support of the Marine Strategy Framework Directive

A novel pan-European marine model ensemble was established, covering nearly all seas under the regulation of the Marine Strategy Framework Directive (MSFD), with the aim of providing a consistent assessment of the potential impacts of riverine nutrient reduction scenarios on marine eutrophication indicators. For each sea region, up to five coupled biogeochemical models from institutes all over Europe were brought together for the first time. All model systems followed a harmonised scenario approach and ran two simulations, which varied only in the riverine nutrient inputs. The load reductions were evaluated with the catchment model GREEN and represented the impacts due to improved management of agriculture and wastewater treatment in all European river systems. The model ensemble, comprising 15 members, was used to assess changes to the core eutrophication indicators as defined within MSFD Descriptor 5. In nearly all marine regions, riverine load reductions led to reduced nutrient concentrations in the marine environment. However, regionally the nutrient input reductions led to an increase in the non-limiting nutrient in the water, especially in the case of phosphate concentrations in the Black Sea. Further core eutrophication indicators, such as chlorophyll-a, bottom oxygen and the Trophic Index TRIX, improved nearly everywhere, but the changes were less pronounced than for the inorganic nutrients. The model ensemble displayed strong consistency and robustness, as most if not all models indicated improvements in the same areas. There were substantial differences between the individual seas in the speed of response to the reduced nutrient loads. In the North Sea ensemble, a stable plateau was reached after only three years, while the simulation period of eight years was too short to obtain steady model results in the Baltic Sea. The ensemble exercise confirmed the importance of improved management of agriculture and wastewater treatments in the river catchments to reduce marine eutrophication. Several shortcomings were identified, the outcome of different approaches to compute the mean change was estimated and potential improvements are discussed to enhance policy support. Applying a model ensemble enabled us to obtain highly robust and consistent model results, substantially decreasing uncertainties in the scenario outcom

Copernicus Marine Service Ocean State Report

This is the final version. Available from Taylor & Francis via the DOI in this record

Copernicus Marine Service ocean state report, issue 4

This is the final version. Available from Taylor & Francis via the DOI in this record. FCT/MCTE

Dataset from long-term model simulation of the Gulf of Finland, the Baltic Sea

The dataset have been used to prepare the article &quot;Long-term mean, interannual and seasonal circulation in the Gulf of Finland — The wide salt wedge estuary or gulf type ROFI&quot; (https://doi.org/10.1016/j.jmarsys.2019.03.004). Citing that article would be appropriate way to credit this dataset. The dataset is derived from the hydrodynamical model simulation results of the Gulf of Finland.Model applied: 3D hydrodynamical model General Estuarine Transport Model (GETM). Horizontal resolution 1 nautical mile. Vertical resolution 40 adaptive layers. Simulation period 1966-2006.Model description and validation is described in Maljutenko and Raudsepp (2014).Climate Data Operators (CDO) toolbox have been used for statistical post-processing (history stored in files).Dataset contains 3 different NetCDF sub-datasets: 1. Average over simulation period 3D fields,2. Monthly mean 3D fields,3. Daily mean profiles from selected stations (folder &quot;Stations&quot;).3D variables are salinity (saltmean), temperature (tempmean), meridional velocity (vvmean), zonal velocity (uumean), vertical velocity (wmean), mean velocity (velmean) , layer thickness (hmean). 2D variables umean and vmean correspond to the barotropic velocity components. The vertical coordinates are given in variable layer heights, such that z-levels must be calculated from water depths (bathymetry) and vertical layer thicknesses (hmean). The location of selected stations can be obtained from the included coordinates in variables of lonc and latc

Dataset from long-term model simulation of the Gulf of Finland, the Baltic Sea

The dataset have been used to prepare the article "Long-term mean, interannual and seasonal circulation in the Gulf of Finland — The wide salt wedge estuary or gulf type ROFI". Citing that article would be appropriate way to credit this dataset. The dataset is derived from the hydrodynamical model simulation results of the Gulf of Finland. Model applied: 3D hydrodynamical model General Estuarine Transport Model (GETM). Horizontal resolution 1 nautical mile. Vertical resolution 40 adaptive layers. Simulation period 1966-2006. Model description and validation is described in Maljutenko and Raudsepp (2014). Climate Data Operators (CDO) toolbox have been used for statistical post-processing (history stored in files). Dataset contains 3 different NetCDF sub-datasets: 1. Average over simulation period 3D fields, 2. Monthly mean 3D fields, 3. Daily mean profiles from selected stations (folder "Stations"). 3D variables are salinity (saltmean), temperature (tempmean), meridional velocity (vvmean), zonal velocity (uumean), vertical velocity (wmean), mean velocity (velmean) , layer thickness (hmean). 2D variables umean and vmean correspond to the barotropic velocity components. The vertical coordinates are given in variable layer heights, such that z-levels must be calculated from water depths (bathymetry) and vertical layer thicknesses (hmean). The location of selected stations can be obtained from the included coordinates in variables of lonc and latc

Data of long-term model simulation on the Gulf of Finland, the Baltic Sea

The dataset have been used to prepare the article "Long-term mean and monthly circulation in the Gulf of Finland, the Baltic Sea". Citing that article would be appropriate way to credit this dataset. The dataset is derived from simulation results from the 40-year model run for the Gulf of Finland. Model applied: 3D hydrodynamical model General Estuarine Transport Model (GETM). Horizontal resolution 1 nautical mile. Vertical resolution 40 adaptive layers. Simulation period 1966-2006. Model description and validation is described in Maljutenko and Raudsepp (2014). Climate Data Operators (CDO) toolbox have been used for statistical post-processing (history stored in files). Dataset contains 3 different NetCDF sub-datasets: 1. Average over simulation period 3D fields, 2. Monthly mean 3D fields, 3. Daily mean profiles from selected stations (folder "Stations"). 3D variables are salinity (saltmean), temperature (tempmean), meridional velocity (vvmean), zonal velocity (uumean), vertical velocity (wmean), mean velocity (velmean) , layer thickness (hmean). 2D variables umean and vmean correspond to the barotropic velocity components. The vertical coordinates are given in variable layer heights, such that z-levels must be calculated from water depths (bathymetry) and vertical layer thicknesses (hmean). The location of selected stations can be obtained from the included coordinates in variables of lonc and latc