title: Statistical modeling of the spatial variability of environmental noise levels in Montreal, Canada, using noise measurements and land use characteristics.
abstract: The availability of noise maps to assess exposure to noise is often limited, especially in North American cities. We developed land use regression (LUR) models for LAeq24h, Lnight, and Ldento assess the long-term spatial variability of environmental noise levels in Montreal, Canada, considering various transportation noise sources (road, rail, and air). To explore the effects of sampling duration, we compared our LAeq24hlevels that were computed over at least five complete contiguous days of measurements to shorter sampling periods (20 min and 24 h). LUR models were built with General Additive Models using continuous 2-min noise measurements from 204 sites. Model performance (adjusted R2) was 0.68, 0.59, and 0.69 for LAeq24h, Lnight, and Lden, respectively. Main predictors of measured noise levels were road-traffic and vegetation variables. Twenty-minute non-rush hour measurements corresponded well with LAeq24hlevels computed over 5 days at road-traffic sites (bias: -0.7 dB(A)), but not at rail (-2.1 dB(A)) nor at air (-2.2 dB(A)) sites. Our study provides important insights into the spatial variation of environmental noise levels in a Canadian city. To assess long-term noise levels, sampling strategies should be stratified by noise sources and preferably should include 1 week of measurements at locations exposed to rail and aircraft noise.
authors.affiliation: Department of Environmental and Occupational Health, School of Public Health, University of Montreal, Montreal, Quebec, Canada.|Quebec Institute of Public Health, Public Health Department of Montreal, Montreal, Quebec, Canada.|Swiss Tropical and Public Health Institute, Basel, Switzerland.|University of Basel, Basel, Switzerland.
authors.forename: Martina S
authors.initials: MS
authors.lastname: Ragettli
authors.affiliation: Quebec Institute of Public Health, Public Health Department of Montreal, Montreal, Quebec, Canada.
authors.forename: Sophie
authors.initials: S
authors.lastname: Goudreau
authors.affiliation: Quebec Institute of Public Health, Public Health Department of Montreal, Montreal, Quebec, Canada.
authors.forename: Céline
authors.initials: C
authors.lastname: Plante
authors.affiliation: Quebec Institute of Public Health, Public Health Department of Montreal, Montreal, Quebec, Canada.
authors.forename: Michel
authors.initials: M
authors.lastname: Fournier
authors.affiliation: Department of Civil Engineering and Applied Mechanics, McGill University, Montreal, Quebec, Canada.
authors.forename: Marianne
authors.initials: M
authors.lastname: Hatzopoulou
authors.affiliation: Quebec Institute of Public Health, Public Health Department of Montreal, Montreal, Quebec, Canada.
authors.forename: Stéphane
authors.initials: S
authors.lastname: Perron
authors.affiliation: Department of Environmental and Occupational Health, School of Public Health, University of Montreal, Montreal, Quebec, Canada.|National Institute of Public Health of Quebec, Montreal, Quebec, Canada.|Public Health Research Institute of the University of Montreal (IRSPUM), Montreal, Quebec, Canada.
authors.forename: Audrey
authors.initials: A
authors.lastname: Smargiassi
mesh_terms: D000401:Aircraft; D004781:Environmental Exposure / Q000032:analysis*; D004784:Environmental Monitoring / Q000379:methods; D040362:Geographic Information Systems; D006801:Humans; D015233:Models, Statistical; D009624:Noise, Transportation; D011792:Quebec; D011890:Railroads; D012044:Regression Analysis; D014887:Weather