Sound Sensor Network based Assessment of Traffic, Noise, and Air Pollution

Invited paper

Luc Dekoninck

Ghent University

Wednesday 3 june, 2015, 11:00 - 11:20

0.8 Rome (118)

All traffic related environmental burdens have a common source: traffic on nearby major roads and on the local roads near the dwelling. The actual exposure to traffic is typically relying on external data from the mobility field, in general government related public offices. The traffic data quality at the high density roads is in most countries very good. Much less effort and by consequence much lower temporal and spatial resolution is available for the lower density roads and the off-peak hours. Traffic data quality is hence low where most people are exposed. Recent developments have also shown that the air pollution exposure and more specifically the particulate matter exposure is spatially and temporally varying with similar resolution as the noise exposure. The lack of data at low density roads is hampering health evaluations in both disciplines. Exposure at the low density roads can be improved by performing mobile and fixed noise monitoring. Mobile noise measurements by bicycle provide a new view on the local variability of both noise and air pollution exposure. For air pollution exposure using instantaneous noise monitoring as a proxy for exposure to traffic enables the disentanglement of the variability to changing traffic conditions and changing meteorological conditions. Several noise assessments techniques are compiled to increase the spatial and temporal resolution of the traffic attribution. Noise based air pollution exposure models will be illustrated, enabling the prediction of the exposure to black carbon and ultrafine particles while being in-traffic and while staying at home.

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