Concentrations of tire wear microplastics and other traffic-derived non-exhaust particles in the road environment.

Tire wear particles (TWP) are assumed to be one of the major sources of microplastic pollution to the environment. However, many of the previously published studies are based on theoretical estimations rather than field measurements. To increase the knowledge regarding actual environmental concentrations, samples were collected and analyzed from different matrices in a rural highway environment to characterize and quantify TWP and other traffic-derived non-exhaust particles. The sampled matrices included road dust (from kerb and in-between wheeltracks), runoff (water and sediment), and air. In addition, airborne deposition was determined in a transect with increasing distance from the road. Two sieved size fractions (2-20 µm and 20-125 µm) were analyzed by automated Scanning Electron Microscopy/Energy Dispersive X-ray spectroscopy (SEM/EDX) single particle analysis and classified with a machine learning algorithm into the following subclasses: TWP, bitumen wear particles (BiWP), road markings, reflecting glass beads, metals, minerals, and biogenic/organic particles. The relative particle number concentrations (%) showed that the runoff contained the highest proportion of TWP (up to 38 %). The share of TWP in kerb samples tended to be higher than BiWP. However, a seasonal increase of BiWP was observed in coarse (20-125 µm) kerb samples during winter, most likely reflecting studded tire use. The concentration of the particle subclasses within airborne PM80-1 decreases with increasing distance from the road, evidencing road traffic as the main emission source. The results confirm that road dust and the surrounding environment contain traffic-derived microplastics in both size fractions. The finer fraction (2-20 µm) dominated (by mass, volume, and number) in all sample matrices. These particles have a high potential to be transported in water and air far away from the source and can contribute to the inhalable particle fraction (PM10) in air. This highlights the importance of including also finer particle fractions in future investigations.

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.

Constraining the formation of authigenic carbonates in a seepage-affected cold-water coral mound by lipid biomarkers.

Cold-water coral (CWC) mounds are build-ups comprised of coral-dominated intervals alternating with a mixed carbonate-siliciclastic matrix. At some locations, CWC mounds are influenced by methane seepage, but the impact of methane on CWC mounds is poorly understood. To constrain the potential impact of methane on CWC mound growth, lipid biomarker investigations were combined with mineralogical and petrographic analyses to investigate the anaerobic oxidation of methane (AOM) and authigenic carbonate formation in sediment from a seep-affected CWC mound in the Gulf of Cadiz. The occurrence of AOM was confirmed by characteristic lipids found within a semi-lithified zone (SLZ) consisting of authigenic aragonite, high-magnesium calcite and calcium-excess dolomite. The formation of high-Mg calcite is attributed to AOM, acting as a lithifying agent. Aragonite is only a minor phase. Ca-excess dolomite in the SLZ and upper parts may be formed by organoclastic sulphate reduction, favouring precipitation by increased alkalinity. The AOM biomarkers in the SLZ include isoprenoid-based archaeal membrane lipids, such as abundant glycerol dibiphytanyl glycerol tetraethers (GDGTs) dominated by GDGT-2. The δ13 C values of GDGT-2, measured as ether-cleaved monocyclic biphytanes, are as low as -100‰ versus V-PDB. Further, bacterial dialkyl glycerol diethers with two anteiso-C15 alkyl chains and δ13 C values of -81‰ are interpreted as biomarkers of sulphate-reducing bacteria. The lipid biomarker signatures and mineralogical patterns suggest that anaerobic methane-oxidizing archaea of the ANME-1 group thrived in the subsurface at times of slow and diffusive methane seepage. Petrographic analyses revealed that the SLZ was exhumed at some point (e.g. signs of bioerosion of the semi-lithified sediment), providing a hard substrate for CWC larval settlement. In addition, this work reveals that AOM-induced semi-lithification likely played a role in mound stabilization. Lipid biomarker analysis proves to be a powerful tool to disentangle early diagenetic processes induced by microbial metabolisms.