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Exploring nighttime road traffic noise: A comprehensive predictive surface for Toronto, Canada

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journal contribution
posted on 2018-03-01, 18:53 authored by Christopher Drudge, James Johnson, Elaina MacIntyre, Ye Li, Ray Copes, Stanley Ing, Steven Johnson, Sunil Varughese, Hong Chen

Road traffic noise can adversely impact the health of city residents, particularly when it occurs at night. The objective of this study was to evaluate nighttime traffic ambient noise in Toronto, Canada using measured and model-estimated noise levels. Road traffic noise was measured at 767 locations over 3 seasonal sampling campaigns between June 2012 and October 2013 to fully capture noise variability in Toronto. Temporal and campaign-specific spatial models, developed using the noise measurements, were used to build a final predictive surface. The surface was capable of estimating noise across the city over a 24-hr time frame. Measured and surface-estimated noise levels were compared with guidelines from the World Health Organization and the Province of Ontario to identify areas where noise may pose a health risk. Measured mean nighttime noise in Toronto exceeded World Health Organization (40 dBA) guidelines and mean daytime noise exceeded provincial (55 dBA) guidelines. The final predictive surface, incorporating spatial variables and daily cycles in noise levels, provides noise estimates geocoded for the entire study area. This tool could be used for epidemiological studies and to inform noise mitigation efforts. Based on surface-estimated noise levels during the quietest time of night (2 a.m.–2:30 a.m.), 100% of Toronto has nighttime noise exceeding 40 dBA (mean = 57 dBA, range = 49–110 dBA). A predictive surface was developed to estimate geocoded noise levels and facilitate further study of noise in Toronto. This tool can be used to assess road traffic noise, particularly at night, as an environmental health hazard.

Funding

This research was funded by Public Health Ontario.

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