Identifying marine sources of beached plastics through a Bayesian framework: Application to southwest Netherlands
Duinen, B.; Kaandorp, M.L.A.; van Sebille, E. (2022). Identifying marine sources of beached plastics through a Bayesian framework: Application to southwest Netherlands. Geophys. Res. Lett. 49(4): e2021GL097214. https://dx.doi.org/10.1029/2021gl097214
In: Geophysical Research Letters. American Geophysical Union: Washington. ISSN 0094-8276; e-ISSN 1944-8007, meer
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| Auteurs | | Top |
- Duinen, B.
- Kaandorp, M.L.A.
- van Sebille, E.
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| Abstract |
Beaches are thought to be a large reservoir for marine plastics. To protect vulnerable beaches, it is advantageous to have information on the sources of this plastic. Here, we develop a universally applicable Bayesian framework to map sources of plastic arriving on a specific beach. In this framework, we combine Lagrangian backtracking simulations of drifting particles with estimates of plastic input from coastlines, rivers and fisheries. The advantage over traditional Lagrangian simulations is that the Bayesian framework can consider information on known sources, and thus facilitates spatiotemporal source attribution for plastic arriving at the specified beach. We show that the main sources for our target beach in southwest Netherlands are the east coast of the UK, the Dutch coast, the English Channel (fisheries) and the Thames, Seine, Rhine and Trieux (rivers). We also show that floating time is a major uncertainty in source attribution using backtracking. |
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