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Application of land use regression modelling to assess the spatial distribution of road traffic noise in three European cities

Journal of Exposure Science & Environmental Epidemiology volume 25, pages 97–105 (2015)Cite this article

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Abstract

Noise prediction models and noise maps are used to estimate the exposure to road traffic noise, but their availability and the quality of the noise estimates is sometimes limited. This paper explores the application of land use regression (LUR) modelling to assess the long-term intraurban spatial variability of road traffic noise in three European cities. Short-term measurements of road traffic noise taken in Basel, Switzerland (n=60), Girona, Spain (n=40), and Grenoble, France (n=41), were used to develop two LUR models: (a) a “GIS-only” model, which considered only predictor variables derived with Geographic Information Systems; and (b) a “Best” model, which in addition considered the variables collected while visiting the measurement sites. Both noise measurements and noise estimates from LUR models were compared with noise estimates from standard noise models developed for each city by the local authorities. Model performance (adjusted R2) was 0.66–0.87 for “GIS-only” models, and 0.70–0.89 for “Best” models. Short-term noise measurements showed a high correlation (r=0.62–0.78) with noise estimates from the standard noise models. LUR noise estimates did not show any systematic differences in the spatial patterns when compared with those from standard noise models. LUR modelling with accurate GIS source data can be a promising tool for noise exposure assessment with applications in epidemiological studies.

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Acknowledgements

The study was supported by ADEME (French Environment and Energy Management Agency; TRI-TABS study contract 0966C0304). Inmaculada Aguilera holds a postdoctoral fellowship awarded from the Catalan Agency for Management of University and Research Grants (BP-DGR-2011-00214). We thank Alex Ineichen (SwissTPH), Marta Cirach (CREAL), and Cécile Fontagné (Air Rhône-Alpes) for their assistance in deriving the GIS variables; n-Sphere (Zürich, Switzerland) and Acoucité Noise Observatory (Lyon, France) for providing the modelled noise estimates in Basel and Grenoble, respectively; and La Métro city council (Grenoble) for providing access to local data.

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Authors and Affiliations

  1. Swiss Tropical and Public Health Institute, Basel, Switzerland

    Inmaculada Aguilera, Elisabetta Corradi, Harish C Phuleria, Martina S Ragettli & Nino Künzli

  2. University of Basel, Basel, Switzerland

    Inmaculada Aguilera, Elisabetta Corradi, Harish C Phuleria, Martina S Ragettli & Nino Künzli

  3. Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain

    Maria Foraster & Xavier Basagaña

  4. CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain

    Maria Foraster & Xavier Basagaña

  5. Grup de Recerca en Enginyeria de Fluids, Energia i Medi Ambient (GREFEMA), University of Girona, Girona, Spain

    Alexandre Deltell

  6. INSERM U823, Institut Albert Bonniot, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, Grenoble, France

    Xavier Morelli & Rémy Slama

  7. Université Joseph Fourier (UJF), Grenoble, France

    Xavier Morelli & Rémy Slama

  8. Centre for Environmental Science and Engineering, Indian Institute of Technology Bombay, Mumbai, India

    Harish C Phuleria

  9. University of Montreal Hospital Research Center (CRCHUM), Montreal, Canada

    Marcela Rivera

  10. Air Rhône-Alpes, Grenoble, France

    Alexandre Thomasson

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  1. Inmaculada Aguilera
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  2. Maria Foraster
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  9. Marcela Rivera
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Correspondence to Inmaculada Aguilera.

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Supplementary Information accompanies the paper on the Journal of Exposure Science and Environmental Epidemiology website

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Aguilera, I., Foraster, M., Basagaña, X. et al. Application of land use regression modelling to assess the spatial distribution of road traffic noise in three European cities. J Expo Sci Environ Epidemiol 25, 97–105 (2015). https://doi.org/10.1038/jes.2014.61

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  • DOI: https://doi.org/10.1038/jes.2014.61

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