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Conference_programme: 10.4 - Noise indicators for impact assessment

Lecture: Probabilistic modeling framework to predict traffic sound distribution

Author(s): Aumond Pierre, Can Arnaud

The dramatic impact of sound events on health issues such as awakenings, demonstrated in a plethora of studies in the last decades, invites to reconsider the sound prediction modeling frameworks to enable their estimation. In this paper, a stochastic modeling approach is described, which enables the estimation of sound level distributions and sound event indicators such as the number of noise events, within a classical sound mapping environment. The base modeling used in this study is developed under the open-source GIS software Noisemodeling. The stochastic approach consists in distributing the sources locations through a large set of runs over which statistics are done. The example is illustrated for road traffic noise, and evaluated over measurements performed in Paris. The further improvements for specific indicator calculations are discussed. The GIS environment opens the door to a potential coupling with dwellings spatial distribution for exposure assessments, thus facilitating the evaluation of the links between sound event indicators and health impacts.

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Corresponding author

Name: Dr Pierre Aumond

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Country: France