RESUMEN
Plastic litter is accumulating on pristine northern European beaches, including the European Arctic, and questions remain about the exact origins and sources. Here we investigate plausible fishery and consumer-related sources of beach littering, using a combination of information from expert stakeholder discussions, litter observations and a quantitative tool - a drift model - for forecasting and backtracking likely pathways of pollution. The numerical experiments were co-designed together with practice experts. The drift model itself was forced by operational ocean current, wave and weather forecasts. The model results were compared to a database of marine litter on beaches, collected every year according to the standardized monitoring program of the Oslo/Paris Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR). By comparing the heterogeneous beach observations to the model simulations, we are able to highlight probable sources. Two types of plastic are considered in the simulations: floating plastic litter and submerged, buoyant microplastics. We find that the model simulations are plausible in terms of the potential sources and the observed plastic litter. Our analysis results in identifiable sources of plastic waste found on each beach, providing a basis for stakeholder actions.
Asunto(s)
Playas , Plásticos , Monitoreo del Ambiente , Contaminación Ambiental , Residuos/análisisRESUMEN
[This corrects the article DOI: 10.1371/journal.pone.0201338.].
RESUMEN
The Norwegian government has decided that the aquaculture industry shall grow, provided that the growth is environmentally sustainable. Sustainability is scored based on the mortality of wild salmonids caused by the parasitic salmon lice. Salmon lice infestation pressure has traditionally been monitored through catching wild sea trout and Arctic char using nets or traps or by trawling after Atlantic salmon postsmolts. However, due to that the Norwegian mainland coastline is nearly 25 000 km, complementary methods that may be used in order to give complete results are needed. We have therefore developed an operational salmon lice model, which calculates the infestation pressure all along the coast in near real-time based on a hydrodynamical ocean model and a salmon lice particle tracking model. The hydrodynamic model generally shows a negative temperature bias and a positive salinity bias compared to observations. The modeled salmon lice dispersion correlates with measured lice on wild salmonids caught using traps or nets. This allows for using two complementary data sources in order to determine the infestation pressure of lice originating from fish farms on wild salmonids, and thereby provide an improved monitoring system for assessing risk and sustainability which forms the basis for knowledge-based advice to management authorities.