Articles | Volume 18, issue 1
https://doi.org/10.5194/os-18-269-2022
https://doi.org/10.5194/os-18-269-2022
Research article
 | Highlight paper
 | 
03 Mar 2022
Research article | Highlight paper |  | 03 Mar 2022

Using machine learning and beach cleanup data to explain litter quantities along the Dutch North Sea coast

Mikael L. A. Kaandorp, Stefanie L. Ypma, Marijke Boonstra, Henk A. Dijkstra, and Erik van Sebille

Related authors

Non-negligible impact of Stokes drift and wave-driven Eulerian currents on simulated surface particle dispersal in the Mediterranean Sea
Siren Rühs, Ton van den Bremer, Emanuela Clementi, Michael C. Denes, Aimie Moulin, and Erik van Sebille
EGUsphere, https://doi.org/10.5194/egusphere-2024-1002,https://doi.org/10.5194/egusphere-2024-1002, 2024
Short summary
Persistent climate model biases in the Atlantic Ocean's freshwater transport
René M. van Westen and Henk A. Dijkstra
Ocean Sci., 20, 549–567, https://doi.org/10.5194/os-20-549-2024,https://doi.org/10.5194/os-20-549-2024, 2024
Short summary
Similar North Pacific variability despite suppressed El Niño variability in the warm mid-Pliocene climate
Arthur Merlijn Oldeman, Michiel L. J. Baatsen, Anna S. von der Heydt, Frank M. Selten, and Henk A. Dijkstra
EGUsphere, https://doi.org/10.5194/egusphere-2024-766,https://doi.org/10.5194/egusphere-2024-766, 2024
Short summary
Mid-Pliocene not analogous to high-CO2 climate when considering Northern Hemisphere winter variability
Arthur Merlijn Oldeman, Michiel L. J. Baatsen, Anna S. von der Heydt, Aarnout J. van Delden, and Henk A. Dijkstra
Weather Clim. Dynam., 5, 395–417, https://doi.org/10.5194/wcd-5-395-2024,https://doi.org/10.5194/wcd-5-395-2024, 2024
Short summary
The (non)effect of personalization in climate texts on credibility of climate scientists
Anna Leerink, Mark Bos, Daan Reijnders, and Erik van Sebille
EGUsphere, https://doi.org/10.5194/egusphere-2024-543,https://doi.org/10.5194/egusphere-2024-543, 2024
Short summary

Cited articles

Alsina, J. M., Jongedijk, C. E., and van Sebille, E.: Laboratory Measurements of the Wave-Induced Motion of Plastic Particles: Influence of Wave Period, Plastic Size and Plastic Density, J. Geophys. Res.-Oceans, 125, e2020JC016294, https://doi.org/10.1029/2020JC016294, 2020. a
Andrades, R., Santos, R. G., Joyeux, J. C., Chelazzi, D., Cincinelli, A., and Giarrizzo, T.: Marine debris in Trindade Island, a remote island of the South Atlantic, Mar. Pollut. Bull., 137, 180–184, https://doi.org/10.1016/j.marpolbul.2018.10.003, 2018. a
Andrady, A. L.: Microplastics in the marine environment, Mar. Pollut. Bull., 62, 1596–1605, https://doi.org/10.1016/j.marpolbul.2011.05.030, 2011. a
Bachmaier, M. and Backes, M.: Variogram or Semivariogram? Variance or Semivariance? Allan Variance or Introducing a New Term?, Math. Geosci., 43, 735–740, https://doi.org/10.1007/s11004-011-9348-3, 2011. a
Balas, C. E., Ergin, A., Williams, A. T., and Koc, L.: Marine litter prediction by artificial intelligence, Mar. Pollut. Bull., 48, 449–457, https://doi.org/10.1016/j.marpolbul.2003.08.020, 2004. a
Download
Short summary
A large amount of marine litter, such as plastics, is located on or around beaches. Both the total amount of this litter and its transport are poorly understood. We investigate this by training a machine learning model with data of cleanup efforts on Dutch beaches between 2014 and 2019, obtained by about 14 000 volunteers. We find that Dutch beaches contain up to 30 000 kg of litter, largely depending on tides, oceanic transport, and how exposed the beaches are.