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

Abstract. The transport dynamics of tire wear particles (TWPs) remain poorly understood despite their growing contribution to airborne microplastic (MP) pollution. This study addresses this gap by experimentally quantifying the TWP detachment rate and threshold friction velocities (u*th ) from an idealised reference surface. Detachment experiments were conducted in a boundary layer wind tunnel over glass substrates seeded with a near-monolayer of particles. Time resolved imaging at 0.1 Hz was combined with automatic particle detachment and segmentation using an open source You Only Look Once version 8 nano (YoloV8n) model, which allowed individual detachment events and particle size and shape to be tracked with a mean average precision at an intersection-over-union threshold of 0.5 (mAP@50) above 85 % for both the bounding box and mask outputs. For the detachment experiments, pristine tire wear particles generated on a laboratory test stand with passenger car (PC) test tire were supplied by Continental GmbH, providing a well characterised and idealised TWP source. Among the three deposition method tested, the low-cost pressurised seeding approach produced the most uniform and reproducible particle distribution for detachment analysis. Across the analysed size range (80 to 300 μm), larger and more irregularly shaped particles exhibited significantly higher detachment (u*th) than smaller and more rounded fragments. Ensemble fits yield a bulk u*th of approximately 0.36 m s−1, with size and shape resolved u*th values varying by roughly a factor of 1.5 between the most easily detached and most resistant classes. The application of the Shao and Lu semi-empirical fluid threshold model reproduced the size-dependent u*th of smooth PE microsphere, but underestimates the TWP u*th unless the effective cohesion and/or aerodynamic scaling parameter are increased beyond values typically used for dust and sand. This behaviour is consistent with TWPs experiencing stronger effective adhesion than smooth, spherical grains of similar size, due to their irregular morphology and multiple contact points with the substrate. The density differences between TWPs (∼1300 kg m−3) and microspheres (∼1025 kg m−3) showed negligible influence within the studied size range (106 to 125 μm). We conclude that particle morphology, incorporating both size and shape, plays a dominant role in controlling the aerodynamic detachment of TWPs on the idealised glass substrate, while density effects are secondary under the tested conditions. Because controlled laboratory studies using well defined particles and simplified surfaces are a neccessary step towards isolating these fundamental mechanisms, our findings provide insights for improving MP and TWP resuspension models and highlight the need for future studies on more realistic environmental surfaces and broader particle sizes and density ranges.