Measuring and characterizing airborne particulate matter (PM) is an important research area because PM can lead to impacts on health and to visibility reduction, material damage and groundwater pollution. In regard to road dust, suspension and re-suspension and the contribution of non-exhaust PM to total traffic emissions are expected to increase as a result of predicted climate scenarios. European environmental regulations have been enforced to reduce exhaust particle emissions from road traffic, but little attention has been paid to reducing non-exhaust coarse particle emissions due to traffic. Therefore, a monitoring program for coarse PM has been initiated in early 2013 to assess the predicted increase in the abundance of non-exhaust particles. Particle sampling was performed with the passive-sampler technique Sigma-2. The subsequent single-particle analysis allows for characterization of individual particles, determination of PM size distribution, and calculation of PM mass concentrations. Two motorways n ear Cologne (Koeln), Germany were selected as sampling sites, and the experimental setup in the field was realized with a so-called twin-site method. The present study reports single-particle analysis data for samples collected between May 31, 2013 and May 30, 2014. Coarse PM, generated through multi-source mechanisms, consists of, e.g., tire-wear, soot aggregates, and mineral dust. The highest mass concentration occurs at both motorways in spring, and the observed PM mainly contains traffic-abrasion particles. The field measurements show that the minimum PM concentration was found in the 5 to 12-°C temperature range, whereas the maximum concentration was observed in both the "5 to 5-°C and the 12 to 24-°C ranges, in agreement with previous laboratory measurements. Correlation between super-coarse (d p 10"80 μm, geometric equivalent diameter) PM concentration and precipitation displays a significant increase in concentration with decreasing number of precipitation events (dry weather periods).

Road authorities, freight, and logistic industries face a multitude of challenges in a world changing at an ever growing pace. While globalization, changes in technology, demography, and traffic, for instance, have received much attention over the bygone decades, climate change has not been treated with equal care until recently. However, since it has been recognized that climate change jeopardizes many business areas in transport, freight, and logistics, research programs investigating future threats have been initiated. One of these programs is the Conference of European Directors of Roads (CEDR) Transnational Research Programme (TRP), which emerged about a decade ago from a cooperation between European National Road Authorities and the EU. This paper presents findings of a CEDR project called CliPDaR, which has been designed to answer questions from road authorities concerning climate-driven future threats to transport infrastructure. Pertaining results are based on two potential future socio-economic pathways of mankind (one strongly economically oriented "A2" and one more balanced scenario "A1B"), which are used to drive global climate models (GCMs) producing global and continental scale climate change projections. In order to achieve climate change projections, which are valid on regional scales, GCM projections are downscaled by regional climate models. Results shown here originate from research questions raised by European Road Authorities. They refer to future occurrence frequencies of severely cold winter seasons in Fennoscandia, to particularly hot summer seasons in the Iberian Peninsula and to changes in extreme weather phenomena triggering landslides and rutting in Central Europe. Future occurrence frequencies of extreme winter and summer conditions are investigated by empirical orthogonal function analyses of GCM projections driven with by A2 and A1B pathways. The analysis of future weather phenomena triggering landslides and rutting events requires downscaled climate change projections. Hence, corresponding results are based on an ensemble of RCM projections, which was available for the A1B scenario. All analyzed risks to transport infrastructure are found to increase over the decades ahead with accelerating pace towards the end of this century. Mean Fennoscandian winter temperatures by the end of this century may match conditions of rather warm winter season experienced in the past and particularly warm future winter temperatures have not been observed so far. This applies in an even more pronounced manner to summer seasons in the Iberian Peninsula. Occurrence frequencies of extreme climate phenomena triggering landslides and rutting events in Central Europe are also projected to rise. Results show spatially differentiated patterns and indicate accelerated rates of increases.