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Assessing residential exposure to urban noise using environmental models: does the size of the local living neighborhood matter?


Environmental epidemiological studies rely on the quantification of the exposure level in a surface defined as the subject’s exposure area. For residential exposure, this area is often the subject’s neighborhood. However, the variability of the size and nature of the neighborhoods makes comparison of the findings across studies difficult. This article examines the impact of the neighborhood’s definition on environmental noise exposure levels obtained from four commonly used sampling techniques: address point, façade, buffers, and official zoning. A high-definition noise model, built on a middle-sized French city, has been used to estimate LAeq,24h exposure in the vicinity of 10,825 residential buildings. Twelve noise exposure indicators have been used to assess inhabitants’ exposure. Influence of urban environmental factors was analyzed using multilevel modeling. When the sampled area increases, the average exposure increases (+3.9 dB), whereas the SD decreases (−1.6 dB) (P<0.01). Most of the indicators differ statistically. When comparing indicators from the 50-m and 400-m radius buffers, the assigned LAeq,24h level varies across buildings from –9.4 to +22.3 dB. This variation is influenced by urban environmental characteristics (P<0.01). On the basis of this study’s findings, sampling technique, neighborhood size, and environmental composition should be carefully considered in further exposure studies.

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Quentin Tenailleau is a Ph.D student supported by a grant from the city of Besançon. We would like to thank the city services, the urban community of Besançon (CAGB), the Besançon Urban Development Agency (AUDAB), and the Departmental Public Works Directorate (DDE) for their technical support.

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Correspondence to Frédéric Mauny.

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Tenailleau, Q., Bernard, N., Pujol, S. et al. Assessing residential exposure to urban noise using environmental models: does the size of the local living neighborhood matter?. J Expo Sci Environ Epidemiol 25, 89–96 (2015).

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  • environmental exposure assessment
  • GIS
  • models
  • neighborhood
  • sampling surface
  • urban noise

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