Automated identification and quantification of tire wear particles (TWP) in airborne dust: SEM/EDX single particle analysis coupled to a machine learning classifier

The share of non-exhaust particles, including tire wear particles (TWP), within the airborne dust and particularly within PM10 has increased in recent years due to a significant reduction of other particles including exhaust road traffic emissions. However, the quantification of TWP is a demanding task due to the non-specificity of tracers, and the fact that they are commonly contained in analytically challenging low concentrations (e.g. Zn, styrene, 1,3-butadiene, vinylcyclohexene). This difficulty is amplified by the chemical and morpho-textural heterogeneity of TWP resulting from the interaction between the tires and the road surface. In contrast to bulk techniques, automated single particle SEM/EDX analysis can benefit from the ubiquitous heterogeneity of environmental TWP as a diagnostic criterion for their identification and quantification. For this purpose, we follow a machine-learning (ML) approach that makes use of an extensive number (67) of morphological, textural (backscatter-signal based) and chemical descriptors to differentiate environmental particles into the following classes: TWP, metals, minerals and biogenic/organic. We present a ML-based model developed to classify airborne samples (trained by >100,000 environmental particles including 6841 TWP), and its application within a one-year monitoring campaign at two Swiss sites. In this study, the mass concentrations of TWP in the airborne fractions PM80-10, PM10-2.5 and PM2.5-1 were determined. Furthermore, the particle size distribution and shape characteristics of 5621 TWP were evaluated. A cut through a TWP by means of FIB-SEM evidences that the mineral and metal particles typically found in TWP are not only present on the particle surface but also throughout the complete TWP volume. At the urban background site, the annual average mass fraction of TWP and micro-rubber in PM10 was 1.8% (0.28 μg/m3) and 0.9%, respectively. At the urban kerbside site, the corresponding values were 6 times higher amounting to 10.5% (2.24 μg/m3) for TWP, and 5.0% for micro-rubber. [Display omitted] •The increasing share of TWP in airborne dust emphasizes the necessity of quantitative and reproducible methods.•Automated single particle SEM/EDX analysis in combination with ML is a reliable method to quantify TWP.•Size-resolved PM80-1 concentration of TWP and micro-rubber for an urban background and a kerbside site are presented.•Airborne dust is differentiated in tire wear, metals, minerals and biogenic/organi