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Open AccessArticle

Modelling Cyclists’ Multi-Exposure to Air and Noise Pollution with Low-Cost Sensors—The Case of Paris

Institut National de la Recherche Scientifique, Centre Urbanisation Culture Société, Montréal, QC H2X 1E3, Canada
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Atmosphere 2020, 11(4), 422; https://doi.org/10.3390/atmos11040422
Received: 5 March 2020 / Revised: 17 April 2020 / Accepted: 19 April 2020 / Published: 22 April 2020
(This article belongs to the Special Issue Air Pollution and Environment in France)
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. View Full-Text
Keywords: cyclist; exposure; multi-exposure; noise; air pollution; NO2; Bayesian modelling; spatial analysis; Paris cyclist; exposure; multi-exposure; noise; air pollution; NO2; Bayesian modelling; spatial analysis; Paris
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MDPI and ACS Style

Gelb, J.; Apparicio, P. Modelling Cyclists’ Multi-Exposure to Air and Noise Pollution with Low-Cost Sensors—The Case of Paris. Atmosphere 2020, 11, 422.

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