Sound Sensor Network based Assessment of Traffic, Noise, and Air Pollution
Invited paper
Ghent University
Wednesday 3 june, 2015, 11:00 - 11:20
0.8 Rome (118)
Abstract:
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.