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Correlation between py-GC-MS and microscopically determined tire wear concentration and tire wear-related markers in snowmelt and soil samples
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Researchers validated correlations between pyrolysis-GC-MS quantification and microscopy-based tire wear measurements using marker substances in snowmelt and soil samples, establishing whether lower-cost chemical marker approaches can serve as reliable proxies for expensive direct analytical methods in environmental tire abrasion monitoring.
Tire abrasion contributes significantly to the global microplastic problem. Nevertheless, precise and reliable quantification of tire abrasion is challenging and still associated with the use of cost-intensive analytical techniques such as pyrolysis-based GC-MS or spectroscopy-assisted microscopy. Alternatively, it is possible to estimate the tire abrasion load with the help of marker substances that are associated with tire material. The determination of these parameters can usually be carried out in laboratories with a more basic analytical equipment. In this work, the correlations between two selected inorganics and three organics related to vehicular abrasion and the mass and particular concentration of tire wear will be presented in detail. Therefore, four snow and seven soil samples from the vicinity of public roads, as well as presumably low-polluted reference samples were analysed for their contents of the corresponding markers and for their tire abrasion concentration. The inorganic parameters zinc and copper were determined using Microwave plasma atomic emission spectroscopy (MP-AES), the organic markers 1,3-diphenylguanidine, 2-hydroxybenzothiazole and 6-PPD-quinone by high-resolution UHPLC-MS/MS. SBR-based decomposition products are used for the determination by pyrolysis-GC-MS. The microscopic identification of the tire wear in the aqueous samples is performed by combining Raman microscopy and SEM-EDX. Preliminary results show that a correlation between zinc, copper, 6-PPD quinone, and the tire abrasion concentration can be assumed. For the corresponding sampling location, it's already apparent that samples with high expected tire wear load show increased concentrations of zinc, copper and 6-PPD-quinone. In our final presentation, we will present a multivariate regression model between our selected markers and the tire abrasion concentration. This model as well as the comparison between different techniques for the determination of tire abrasion will expand the knowledge about this type of microplastic pollution and can contribute to a standardization of the analysis of tire abrasion. Also see: https://micro2024.sciencesconf.org/559716/document
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Correlation between py-GC-MS and microscopically determined tire wear concentration and tire wear-related markers in snowmelt and soil samples
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