The Mediterranean is considered a hot-spot for plastic pollution, due to its semi-enclosed nature and heavily populated coastal areas. In the present study, a basin-scale coupled hydrodynamic/particle drift model was used to track the pathways and fate of plastics from major land-based sources (coastal cities and rivers), taking into account of the most important processes (advection, stokes drift, vertical and horizontal mixing, sinking, wind drag, and beaching). A hybrid ensemble Kalman filter algorithm was implemented to correct the near- surface circulation, assimilating satellite data (sea surface height, temperature) in the hydrodynamic model. Different size classes and/or types of both micro- and macroplastics were considered in the model. Biofouling induced sinking was explicitly described, as a possible mechanism of microplastics removal from the surface. A simplified parameterization of size-dependent biofilm growth has been adopted, as a function of bacterial biomass (obtained from a biogeochemical model simulation), being considered a proxy for the biofouling community. The simulated distributions for micro- and macroplastics were validated against available observations, showing reasonable agreement, both in terms of magnitude and horizontal variability. An 8-year simulation was used to identify micro- and macroplastics accumulation patterns in the surface layer, water column, seafloor and beaches. The impact of different processes (vertical mixing, biofouling, and wind/wave drift) was identified through a series of sensitivity experiments. For both micro- and macroplastics, distributions at sea surface were closely related to the adopted sources. The microplastics concentration was drastically reduced away from source areas, due to biofouling induced sinking, with their size distribution dominated by larger (>1 mm) size classes in open sea areas, in agreement with observations. High concentration patches of floating plastics were simulated in convergence areas, characterized by anticyclonic circulation. The distribution of macroplastics on beaches followed the predominant southeastward wind/wave direction. In the water column, a sub-surface maximum in microplastics abundance was simulated, with increasing contribution of smaller particles in deeper layers. Accumulation of microplastics on the seafloor was limited in relatively shallow areas (<500 m), with bottom depth below their relaxation depth due to defouling. The simulated total amount of floating plastics (∼3,760 tonnes) is comparable with estimates from observations.

The effect of Black Sea Water (BSW) inputs on the productivity and food web dynamics of the N. Aegean Sea was investigated, by means of sensitivity simulations, investigating the effect of the inflowing BSW, in terms of inorganic nutrients and dissolved organic matter. Considering the importance of the microbial loop in ecosystem functioning and the role of dissolved organics, the bacteria sub-model was appropriately revised, towards a more realistic representation of the Dissolved Organic Matter (DOM) pool. The importance of the microbial loop is highlighted by the simulated carbon fluxes, where almost 50% of carbon is channelled within it. The impact of DOM (in the inflowing to the Aegean Sea BSW) appears to be stronger than the impact of dissolved inorganic nutrients, showing a more extended effect over the N. Aegean. Bacterial production and biomass is more strongly affected in the simulations by modified DOM, while phytoplankton biomass and production are more dependent on inflowing nutrients and particularly phosphorus (inorganic and dissolved organic). As regards phytoplankton composition, the dinoflagellates appear to be affected most, being favoured by higher nutrient availability at the expense of all other groups, particularly picoplankton, indicating a shift to a more classical food chain.

A hybrid ensemble data assimilation scheme (HYBRID), combining a flow-dependent with a static background covariance, was developed and implemented for assimilating satellite (SeaWiFS) Chl-a data into a marine ecosystem model of the Mediterranean. The performance of HYBRID was assessed against a model free-run, the ensemblebased Singular Evolutive Interpolated Kalman (SEIK) and its variant with static covariance (SFEK), with regard to the assimilated variable (Chl-a) and non-assimilated variables (dissolved inorganic nutrients) HYBRID was found more efficient than both SEIK and SFEK, reducing the Chl-a error by more than 40% in most areas, as compared to the free-run. Data assimilation had a positive overall impact on nutrients, except for a deterioration of nitrates by SEIK in the most productive area (Adriatic), related to SEIK pronounced update in this area and the phytoplankton limitation on phosphate that lead to a built up of excess nitrates. SEIK was found more efficient in productive and variable areas, where its ensemble exhibited important spread. SFEK had mostly an effect on Chl-a, performing better than SEIK in less dynamic areas, adequately described by the dominant modes of its static covariance. HYBRID performed well in all areas, due to its "blended" covariance. Its flow-dependent component appears to track changes in the system dynamics, while its static covariance helps maintaining sufficient spread in the forecast. HYBRID sensitivity experiments showed that an increased contribution from the flow-dependent covariance results in a deterioration of nitrates, similar to SEIK, while the improvement of HYBRID with increasing flow-dependent ensemble size quickly levels off.

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 outcome.

A new approach for processing the remote sensing chlorophyll-α (Chl-α) before assimilating into an ecosystem model is applied in two contrasting, regarding productivity and nutrients availability, Mediterranean sites: the DYFAMED and POSEIDON E1-M3A fixed point open ocean observatories. The new approach derives optically weighted depth-distributed Chl-α profiles from satellite data based on the model simulated Chl-α vertical distribution and light attenuation coefficient. We use the 1D version of the operational ecological 3D POSEIDON model, based on the European Regional Seas Ecosystem Model (ERSEM). The required hydrodynamic properties are obtained (off-line) from the POSEIDON operational 3D hydrodynamic Mediterranean basin scale model. The data assimilation scheme is the Singular Evolutive Interpolated Kalman (SEIK) filter, the ensemble variant of the Singular Evolutive Extended Kalman (SEEK) filter. The performance of the proposed assimilation approach was evaluated against the Chl-α satellite data and the seasonal averages of available in-situ data for nitrate, phosphate and Chl-α. An improvement of the model simulated near-surface and subsurface maximum Chl-α concentrations is obtained, especially at the DYFAMED site. Model nitrate is improved with assimilation, particularly with the new approach assimilating depthdistributed Chl-α, while model phosphate is slightly worse after assimilation. Additional sensitivity experiments were performed, showing a better performance of the new approach under different scenarios of model Chl-α deviation from pseudo-observations of surface Chl-α.