Articles | Volume 18, issue 1
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

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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,, 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,, 2018. a
Andrady, A. L.: Microplastics in the marine environment, Mar. Pollut. Bull., 62, 1596–1605,, 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,, 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,, 2004. a
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.