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Urban areas constitute a major hotspot of litter, including plastic litter, that stormwater can wash off towards waterways. However, few studies quantified and characterized litter densities in urban areas and fluxes transported by stormwater networks. Moreover, little information is available on litter transport dynamics in stormwater, and on the factors driving this transport. This study aims at characterizing and quantifying litter amounts transported by stormwater of two nested French urban catchments (total surface area of 105 ha). Litter densities relative to land uses and rain events were investigated in the same catchments as in a compagnon paper (Ledieu et al., 2024). The present study explores the impact of rain events on the transport of urban litter in stormwater. Litter collection and characterization combined with a capture/recapture experiment using tagged litter placed in stormwater inlets show total litter fluxes of 29 kg/year, in which 14 kg/year are plastics, exported at the stormwater outlet. These fluxes confirm that stormwater runoff is a considerable pathway from urban surfaces to waterways, especially regarding small plastic litter (< 2.5 cm). Item transport dynamic is however not linear and only 0.3% of the urban litter appear remobilized. Litter transport dynamics depends on several factors (urban litter densities, hydrometeorological parameters, item composition and morphologies, and stormwater management systems) that should be considered in global models., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This article aims at modeling the impact of road characteristics and local spatial environment on road (un)safety. The study applies to Belgium where some 1,500 people are killed annually on the roads. This statistic corresponds to one of the highest risks in Europe. Road unsafety is expressed here as whether an hectometer of road belongs to a black zone; a black zone is defined as a segment of road where roads accidents are concentrated. Logistic modeling including spatial autocorrelation is used and compared to non-spatial regression. It is shown that a spatial model is needed to avoid biased estimated parameters. Results show that local environment and road infrastructure play a substantial role in the co-occurrence of road accidents. Hence, education and enforcement cannot be the only measures taken to reach a sustainable road safety. To attain their objectives of accident reduction, public authorities should also take their responsibilities in the matter of securing road infrastructure.

This article aims to determine the location and the length of road sections characterized by a concentration of accidents (black zones). Two methods are compared: one based on a local decomposition of a global autocorrelation index, the other on kernel estimation. After explanation, both methods are applied and compared in terms of operational results, respective advantages and shortcomings, as well as underlying conceptual elements. The operationality of both methods is illustrated by an application to one Belgian road.