edoc

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

Aguilera, Inmaculada and Foraster, Maria and Basagaña, Xavier and Corradi, Elisabetta and Deltell, Alexandre and Morelli, Xavier and Phuleria, Harish C. and Ragettli, Martina S. and Rivera, Marcela and Thomasson, Alexandre and Slama, Rémy and Künzli, Nino. (2015) Application of land use regression modelling to assess the spatial distribution of road traffic noise in three European cities. Journal of exposure science and environmental epidemiology, Vol. 25, H. 1. pp. 97-105.

Full text not available from this repository.

Official URL: http://edoc.unibas.ch/dok/A6337703

Downloads: Statistics Overview

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 R(2)) 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. Betr. Lärmbelastung in Basel
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Former Units within Swiss TPH > Exposure Science (Tsai)
UniBasel Contributors:Phuleria, Harish Chandra and Ragettli, Martina and Künzli, Nino
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Nature Publishing Group
ISSN:1559-0631
Note:Publication type according to Uni Basel Research Database: Journal article
Related URLs:
Identification Number:
Last Modified:06 Nov 2015 10:21
Deposited On:06 Feb 2015 09:59

Repository Staff Only: item control page