Resuspension of road dust contributes to air quality issues with resulting health impacts. Limited studies imply that porous pavements can initially mitigate PM₁₀ emissions by acting as a dust trap, but the abrasion wear generates road dust and thus accelerates the clogging processes. In addition, knowledge regarding the impact of pavement types on road dust load dynamics is limited. 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. 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. Linköping municipality, in Sweden, constructed a porous pavement to mitigate road traffic noise. 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. Results, when using the wet dust sampler (WDS) method, showed similar dust load dynamics for the dense and porous pavements. The results were also compared to previous studies using the same method on different dense pavements in Stockholm, Sweden. All locations showed a seasonal variation with higher dust loads during winter and early spring and declining loads towards summer. 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. 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.

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. 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. 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. The WDS has been used for some time and is presented in detail to the international scientific community as reported by Jonsson et al. ( 2008 ) and Gustafsson et al. ( 2019 ), and in this paper, the latest version is presented together with an evaluation of its performance. 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. 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. 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. A theoretical particle mass balance shows small particle losses, while field measurements show higher losses. Several tests are suggested to validate and improve on the mass balances. Finally, the WDS is found to perform well and is able to contribute to further knowledge regarding road dust implications for air pollution.

An experimentally based prediction model of road abrasion wear due to studded tyres is available in Sweden and has been found to work well. However, it has not been validated since 2007, and since then road surfaces and tyre design have developed, and the question has arisen regarding the model’s current validity. The abrasion wear model is used in the NORTRIP emission model (NOn-exhaust Road Traffic Induced Particle emission modelling), and the effect of a recalibrated abrasion wear model on the emission model is shown. In this paper, the abrasion wear model is compared to full-scale field measurements at several recently constructed roads in Sweden to investigate its validity, while also proposing changes to allow for continued use. It is concluded that the model overestimates the wear and an update is suggested. In addition, the impact on NORTRIP emission predictions is briefly investigated. There were also indications that NORTRIP is affected by the abrasion model overestimating the contribution of pavement wear to the particle emissions.

Non-exhaust emissions from the wear of brakes, tyres, and roads have become an increasing concern in recent years, already surpassing exhaust emissions by mass in many countries. However, there is a lack of studies in the scientific literature on test methods that include both real tyre and road materials. This is crucial for accurately replicating the tribological mechanisms and resulting emissions that occur during real-world driving. This study therefore employs a scaled experimental approach to investigate the influence of representative urban load and sliding speed conditions on tyre and road wear particle generation using commercial tyre and road materials. Friction, wear, and emissions were analysed using a pin-on-disc tribometer within a controlled environment, enabling the measurement of both airborne and non-airborne wear particles. The results demonstrate that under moderate test conditions, airborne tyre and road wear particle concentrations remained almost zero, with reasonable coefficients of friction and estimated non-airborne emission factors. However, under harsher contact conditions, the coefficients of friction, airborne tyre and road wear concentrations and estimated emission factors increased significantly, leading to excessive material detachment from both the tyre and road surface. These extreme wear conditions are not representative of real-world tyre–road interactions, emphasising the sensitivity and necessity of using more realistic test conditions in future studies.