Articles | Volume 4, issue 2
https://doi.org/10.5194/ar-4-345-2026
https://doi.org/10.5194/ar-4-345-2026
Research article
 | 
20 Jul 2026
Research article |  | 20 Jul 2026

From seeding to detachment: leveraging deep learning to quantify the transport of tyre wear microplastics in a wind tunnel

Bashir Olasunkanmi Ayinde, Wolfgang Babel, Johannes Olesch, Daniel Wagner, Seema Agarwal, Christian Laforsch, Julian Brehm, Anke Nölscher, and Christoph Karl Thomas

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Cited articles

Arthur, C., Baker, J. E., and Bamford, H.: Proceedings of the International Research Workshop on the Occurrence, Effects, and Fate of Microplastic Marine Debris, 9–11 September 2008, University of Washington Tacoma, Tacoma, WA, USA, NOAA Technical Memorandum NOS-OR&R-30, National Oceanic and Atmospheric Administration, NOAA Institutional Repository record noaa:2509, 2009. a
Astorayme, M. A., Vázquez-Rowe, I., and Kahhat, R.: The use of artificial intelligence algorithms to detect macroplastics in aquatic environments: A critical review, Sci. Total Environ., 945, 173843, https://doi.org/10.1016/j.scitotenv.2024.173843, 2024. a
Ayinde, B. O., Musa, M. R., and Ayinde, A.-A. O.: Application of machine learning models and landsat 8 data for estimating seasonal pm 2.5 concentrations, Environmental Analysis, Health and Toxicology, 39, e2024011, https://doi.org/10.5620/eaht.2024011, 2024. a
Ayinde, B. O., Babel, W., Olesch, J., Agarwal, S., Wagner, D., Nölscher, A., and Thomas, C.: Quantifying the detachment dynamics of microplastic car tire-wear particles using a deep learning framework in a laboratory wind tunnel, EGU General Assembly 2025, Vienna, Austria, 27 April–2 May 2025, EGU25-11439, https://doi.org/10.5194/egusphere-egu25-11439, 2025. a
Ayinde, B. O., Wolfgang, B., Olesch, J., Wagner, D., Agarwal, S., Laforsch, C., Nölscher, A., and Thomas, C. K.: Dataset and script used for the publication: From seeding to detachment: leveraging deep learning to quantify the transport of tyre wear microplastics in a wind tunnel, Zenodo [data set], https://doi.org/10.5281/zenodo.20589718, 2026. a
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Short summary
The dynamics of how tyre wear particles behave prior to their entrainment are still poorly understood. In wind tunnel experiments, the particle detachment from an idealized glass substrate was monitored. For particle sizes above 80 μm, smaller and more rounded particles were mobilized by wind shear first, whereas larger and more angular particles require stronger wind shear, highlighting strong surface adhesion and particle morphology as the major factors influencing microplastic detachment.
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