Estimation of Spatial Variations in Urban Noise Levels with a Land Use Regression Model

Sophie Goudreau,Allan Brand,Michel Fournier,Audrey Smargiassi,Céline Plante,Yann Roche

doi:10.5539/ep.v3n4p48

Abstract

Background: Outdoor noise is a source of annoyance and health problems in cities worldwide. Objective: We developed a land-use regression using a GAM Model to estimate the spatial variation of noise levels in Montreal. Methods: Noise levels were measured over a two week period during the summer of 2010 at 87 sites and during the winter of 2011 at 62 sites. A land use regression model was produced for both seasons to estimate noise levels as LAeq24h (resolution of 20 m). A leave one out cross-validation (LOOCV) was performed. Results: LAeq24h measured range from 53.4 to 73.7 dBA for the summer and from 54.1 to 77.7 dBA for the winter. The land use regression models explained 64 % of spatial variability for the summer and 40 % for the winter. The main predictors are the Normalized Difference Vegetation Index; the length of vehicular arteries, highways, and bus lines; and the proximity to an international airport. The Root mean square error ??from the LOOCV was 3.3 and 4.5 dBA for the summer and the winter respectively. Conclusion: The model explained a large part of the variability in noise levels and the RMSE remain relatively important on the noise levels scale.

Highlights

The model explained a large part of the variability in noise levels and the RMSE remain relatively important on the noise levels scale
Prolonged exposure to high environmental noise levels has been associated with annoyance, learning difficulties in children, sleep disturbances, hypertension, and other cardiovascular outcomes (Basner et al, 2014; Sørensen et al, 2012; Huss et al, 2010; Basner et al, 2006; Jarup et al, 2005; Stansfeld et al, 2005)
Spatial variations of noise levels have been observed in urban areas (Zuo et al, 2014; Seto et al, 2007; Alberola et al, 2005)

Summary

Introduction

Spatial variations of noise levels have been observed in urban areas (Zuo et al, 2014; Seto et al, 2007; Alberola et al, 2005) These spatial differences have been associated with main emission sources and with characteristics of the built environment (Zuo et al, 2014). Main emission sources of noise in urban environments include road, aerial, and railroad traffic; public and construction works; industries, domestic noise, and noise from leisure activities (Berglund et al, 1999). Among these sources, road traffic is the greatest contributor in urban settings (Makarewicz, 1993).

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Conclusion