title: Using city-wide mobile noise assessments to estimate bicycle trip annual exposure to Black Carbon.
abstract: Several studies have shown that a significant amount of daily air pollution exposure, in particular Black Carbon (BC), is inhaled during bicycle trips. Previously, the instantaneous BC exposure of cyclists was modeled as the sum of a background concentration and a local traffic related component based on a local assessment of traffic noise. We present a fast and low cost methodology to achieve a city-wide assessment of yearly average BC exposure of cyclists along their trips, based on a city-wide mobile noise sensing campaign. The methodology requires participatory sensing measurements of noise, partially combined with BC and/or other air pollutants sensitive to local traffic variations. The combined measurements cover the spatial and meteorological variability and provide the data for an instantaneous exposure model. The mobile noise-only measurements map the full city; and yearly meteorology statistics are used to extrapolate the instantaneous exposure model to a yearly average map of in-traffic air pollution exposure. Less than four passages at each segment along the network with mobile noise equipment are necessary to reach a standard error of 500 ng/m(3) for the yearly average BC exposure. A strong seasonal effect due to the BC background concentration is detected. The background contributes only 25% to the total trip exposure during spring and summer. During winter the background component increases to 50-60%. Engine related traffic noise along the bicyclist's route is a valid indicator of the BC exposure along the route, independent of the seasonal background. Low exposure route selection results in an exposure reduction of 35% in winter and 60% in summer, sensitive to the weather conditions, specific trip attributes and the available alternatives. The methodology is relevant for further research into the local effects of air pollution on health. Mobile noise mapping adds local traffic data including traffic dynamics into the air pollution exposure assessments. Local policy makers and urban planners can use the results to support the implementation of low exposure infrastructure, create awareness through route planners and achieve behavioral changes toward active travel modes.
authors.affiliation: Information Technology, Acoustics Group, Ghent University, St-Pietersnieuwstraat 41, 9000 Ghent, Belgium. Electronic address: luc.dekoninck@intec.ugent.be.
authors.forename: Luc
authors.initials: L
authors.lastname: Dekoninck
authors.affiliation: Information Technology, Acoustics Group, Ghent University, St-Pietersnieuwstraat 41, 9000 Ghent, Belgium. Electronic address: dick.botteldooren@intec.ugent.be.
authors.forename: Dick
authors.initials: D
authors.lastname: Botteldooren
authors.affiliation: Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium; Transportation Research Institute (IMOB) Hasselt University, Wetenschapspark 5 Bus 6, 3590 Diepenbeek, Belgium. Electronic address: luc.intpanis@vito.be.
authors.forename: Luc
authors.initials: L
authors.lastname: Int Panis
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000706:statistics & numerical data; D001530:Belgium; D001642:Bicycling; D002244:Carbon; D002947:Cities; D004781:Environmental Exposure; D004784:Environmental Monitoring / Q000379:methods*; D006801:Humans; D008962:Models, Theoretical; D009622:Noise; D053260:Soot / Q000032:analysis*
chemical_list: D000393:Air Pollutants; D053260:Soot; D002244:Carbon
keywords: Active mobility; Black Carbon; Cyclists; Personal exposure; Traffic; Vehicle noise