Cyclists constitute a population particularly exposed to atmospheric and noise pollution in urban environments; at the same time, they contribute to its reduction. For about ten years now, more and more studies have been completed to assess cyclists' exposure, comparing this mode of transportation with others, quantifying its impacts in term of individual and collective health, understanding cyclists' perceptions regarding their exposure, etc. Though some literature reviews have examined some of these specific issues, none have yet proposed a general overview of this field of study. Therefore, this mapping literature review fills this gap by jointly analysing 205 articles and identifying elements of consensus and disagreement, as well as existing gaps. Among others, our results indicate that the cities in the South and exposure to noise are under-studied and that cyclists' ventilation is still too rarely accounted for, regardless of the type of studies. Modelling studies regarding exposure are too heterogeneous methodologically to allow a generalisation of their results. Conversely, intermodal comparison studies clearly indicate overexposure for cyclists compared to other modes. Also, health studies conclude that, either individually or collectively, the benefits of cycling surpass the costs of exposure to atmospheric pollution. The knowledge produced by this research trend remains difficult to exploit by urban planners, but the recent work done seems to offer more practical perspectives to professionals.
Cyclists are particularly exposed to air and noise pollution because of their higher ventilation rate and their proximity to traffic. However, few studies have investigated their multi-exposure and have taken into account its real complexity in building statistical models (nonlinearity, pseudo replication, autocorrelation, etc.). We propose here to model cyclists’ exposure to air and noise pollution simultaneously in Paris (France). Specifically, the purpose of this study is to develop a methodology based on an extensive mobile data collection using low-cost sensors to determine which factors of the urban micro-scale environment contribute to cyclists’ multi-exposure and to what extent. To this end, we developed a conceptual framework to define cyclists’ multi-exposure and applied it to a multivariate generalized additive model with mixed effects and temporal autocorrelation. The results show that it is possible to reduce cyclists’ multi-exposure by adapting the planning and development practices of cycling infrastructure, and that this reduction can be substantial for noise exposure.
According to the World Health Organization, high levels of exposure to road traffic noise are associated with adverse health effects. Earlier studies suggest that cyclists are exposed to higher noise levels than motorists. Other studies have demonstrated that cyclists' exposure to noise could vary significantly according to their routes. The aim of this study is to compare cyclists' exposure to noise and their determinants in three cities. Three participants cycled equipped with noise dosimeters and GPS watches: 1823, 967, and 1362 km in Copenhagen, Paris, and Montreal, respectively. We fitted three generalized additive mixed model with an autoregressive term models to predict the cyclists' exposure to noise according to the type of route and bicycle infrastructure after controlling for the day of the week, as well as spatial and temporal trends. The overall noise means were 73.4, 70.7, and 68.4 dB(A) in Paris, Montreal, and Copenhagen, respectively. The exposure to road traffic noise is strongly associated with the type of bicycle infrastructure taken by the cyclist; riding on a cycleway significantly decreases it, while riding in a shared lane has no impact. Our findings demonstrate that it is possible to achieve a substantial reduction in cyclists exposure by adopting new practices that include noise exposure in the planning of future cycling infrastructure.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.