Author(s): Dana Stuparu; Myra Van Der Meulen; Frank Kleissen; Dick Vethaak; Ghada El Serafy
Linked Author(s):
Keywords: Pollution; Plastic litter; Modeling; Probabilistic; North Sea
Abstract: As a result of the rising plastic usage worldwide, the abundance of plastic litter in the sea and ocean has steadily increased over the last few decades. However, there is considerable uncertainty regarding the occurrence and effects of plastic litter on the marine environment. This uncertainty is visible both at the level of physical impacts but also with respect to the adaptation measures to reduce the negative environmental consequences. Aiming for a better representation of this uncertainty, the EU Marine Strategy Framework Directive was published in 2008 and requires EU member states to achieve‘good environmental status’ (GES) in Europe’s seas by 2020. The present study aims to improve the knowledge regarding the distribution and possible accumulation of plastic litter in the North Sea. The litter transport in the North Sea is modeled by further development of the Delft3d software. By combining hydrodynamics with particle tracking concepts, the model calculates how the position of plastic particles evolves in time from their release (discharge from rivers such as the Rhine or the Meuse) until the end of the simulation. The settling velocity of the particles in the water system is dependent on the ambient conditions (temperature/salinity) as well as on the particle characteristics (density/size) . The results for micro-sized plastics are presented, while ongoing work is extending the concept for the larger macrosized plastic litter items. Different types (polyethylene, polystyrene, PET, PVC) and sizes (10µm, 330µm and 5 mm) of plastics were simulated. The results demonstrate that density is the main determining factor for plastic settlement and that size also has an effect on the final location of accumulation. Modeling results are then compared with field measurements in sediments as a validation step. This research demonstrates that modeling can provide a regional or global overview and aid in identifying monitoring questions.
Year: 2015