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Microplastic and tyre wear particles at a highway: a case study from Norway
Microplastics and Nanoplastics2025
Score: 38
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0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Researchers monitored microplastics and tire wear particles (tiny rubber fragments shed by vehicles) in air, road runoff, and road dust along a busy Norwegian highway, finding the highest concentrations in road dust and the lowest in air. The study demonstrates that traffic is a major source of microplastic pollution across multiple environmental pathways.
This study assessed the presence of microplastics (MPs), including tyre wear particles (TWPs), in three environmental compartments (air, road runoff, and road dust) collected near a heavily trafficked highway in southern Norway. Using micro-Fourier Transform Infrared Spectroscopy (µFTIR) and pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS), we characterised the polymer composition, particle sizes, and estimated mass across matrices. MP concentrations were highest in road dust (567–4250 counts/m2; 30.6–291.4 µg/m2), followed by road runoff (64.5–598.2 counts/L; 0.4–11.7 µg/L) and air (5.0–26.3 counts/day; 0.16–0.95 µg/day). TWP mass was below the detection limit in all air samples, while concentrations ranged from 270 to 1470 µg/L in road runoff and 33,500–178,777 µg/m2 in road dust. Polymer composition differed by matrix: polypropylene dominated in runoff and dust, whereas polyester and polyamide were most abundant in air samples. Particles < 100 µm were prevalent across matrices, reflecting the detection limits of the analytical methods. Although wind speed and precipitation varied during sampling, the limited number of air samples did not allow for statistical assessment of correlations with airborne MPs. Road runoff and road dust more directly reflected local traffic emissions, whereas air samples were more influenced by atmospheric transport and dispersion. These findings highlight the importance of multi-matrix monitoring to capture the spatial and environmental variability of traffic-derived MPs and to improve our understanding of MP behaviour in complex roadside environments.