From regional “strategic” maps to microscopic scale models: multi-scales approaches to improve the assessment of exposure to pollutants due to transportation

Invited paper

Xavier Olny


Tuesday 2 june, 2015, 11:40 - 12:00

0.3 Copenhagen (49)

Because land transportation remains the first source of noise in urban environment, lots of efforts have been put into the development of computational tools for the prediction of traffic noise and air pollutions. Strategic noise maps are well suited for global assessment of noise levels. However, when accurate exposure estimation is required, at infra-communal level, improved modeling methods should be considered, such as: coupling between microscopic traffic modeling and noise or pollutants imissions prediction, computation of temporal, statistical or dynamical indicators, better knowledge of population mobility behavior. On the basis of real experiments performed in the Rhône-Alpes Region, this paper outlines the interest of using coherent multi-scale approaches, with the view to better qualify and quantify exposure to environmental pollutions (noise and air). The paper is divided into three main parts corresponding to three geographical zoom levels. In a first part, the regional observatory ORHANE, designed to host homogeneous data (transport infrastructure characteristics, buildings, noise barriers and pavements, population data,…) is presented. This platform is used to produce coherent air plus noise pollution maps at a global scale in order to prioritize territorial issues, and to guide more detailed investigations. Different synthetic populationXexposure indicators estimated from this data base are presented. In a second part, considering a reduced geographic area (agglomeration of Lyon), we show how accounting for household travel surveys and realistic localization of population, can dramatically modify the exposure assessment. The third and final zoom deals with microscopic traffic flow models, coupled with dedicated noise emission laws and a propagation model. These technical solutions advantageously complement the range of predicting tools, overpassing the limits of static average approaches unable to esteem the effects of local traffic-regulation measures or planning.

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