![]() Furthermore, the relative number concentration of the subclasses was similar in both analyzed size fractions (2–20 µm and 20–125 µm), with minerals as the most dominant subclass (2–20 µm x̄ = 78%, 20–125 µm x̄ = 74%) followed by tire and bitumen wear particles, TBiWP, (2–20 µm x̄ = 19%, 20–125 µm x̄ = 22%). The results showed that the method enabled differentiation between TWP and BiWP for particles > 20 µm with satisfying results. The method is non-destructive, rapid, repeatable, and enables information about the size, shape, and elemental composition of particles 2–125 µm. In this study, we further developed a machine-learning algorithm coupled to an automated scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDX) analytical approach to classify and quantify the relative number of the following subclasses contained in environmental road dust: tire wear particles (TWP), bitumen wear particles (BiWP), road markings, reflecting glass beads, metallics, minerals, and biogenic/organics. Tires, bitumen, and road markings are important sources of traffic-derived carbonaceous wear particles and microplastic (MP) pollution. On the other hand, the dust load and size distribution were more similar between the porous and dense pavements regarding loads and shapes, indicating a less pronounced but similar behaviour between the surfaces outside of the wheel tracks. The size distributions were more complex for the wheel tracks at the porous pavement, having primarily properties of a mixture model compared to the simple size distributions for the dense pavement. All locations showed a seasonal variation with higher dust loads during winter and early spring and declining loads towards summer. The results were also compared to previous studies using the same method on different dense pavements in Stockholm, Sweden. Results, when using the wet dust sampler (WDS) method, showed similar dust load dynamics for the dense and porous pavements. This led to the opportunity to investigate the temporal variation of the dust load dynamics and inherent size distributions over the winter and spring in comparison to those of an adjacent dense pavement. Linköping municipality, in Sweden, constructed a porous pavement to mitigate road traffic noise. Due to this durability problem, porous pavements are rarely used in the Nordic countries where, instead, dense pavements which are abrasion resistant are more common. Road traffic noise can be mitigated using porous pavements, but the use of studded tyres increases the abrasion wear of the pavement as well as increasing the noise emission. In addition, knowledge regarding the impact of pavement types on road dust load dynamics is limited. Limited studies imply that porous pavements can initially mitigate PM 10 emissions by acting as a dust trap, but the abrasion wear generates road dust and thus accelerates the clogging processes. Resuspension of road dust contributes to air quality issues with resulting health impacts. Finally, the WDS is found to perform well and is able to contribute to further knowledge regarding road dust implications for air pollution. Several tests are suggested to validate and improve on the mass balances. A theoretical particle mass balance shows small particle losses, while field measurements show higher losses. The largest loss was found to be water retained on the surface, and the dust measurements imply that this might not have as large impact on the sampled dust as could be expected. The results show that the WDS, when accounting for all losses, have a predictable and repeatable water performance, with no impact on performance based on the variety of asphalt surface types included in this study, given undamaged surfaces. To evaluate the WDS, the ejected water amount was measured, as well as water losses in different parts of the sampling system, together with indicative dust measurement using turbidity as a proxy for dust concentration. (2019), and in this paper, the latest version is presented together with an evaluation of its performance. The WDS has been used for some time and is presented in detail to the international scientific community as reported by Jonsson et al. The principle of operation is flushing high-pressurised water over a defined surface area and transferring the dust laden water into a container for further analyses. To quantify the dust at the road surface, a method-the wet dust sampler (WDS)-was developed allowing repeatable sampling also under wet and snowy conditions. ![]() In northern countries, the climate, and consequently the use of studded tyres and winter traction sanding, causes accumulation of road dust over winter and spring, resulting in high PM10 concentrations during springtime dusting events. ![]()
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