Article

The application of a notice-event model to improve classical exposure-annoyance estimation.

Division of Social Medicine, Medical University of Innsbruck, Sonnenburgstrasse 16, A-6010 Innsbruck, .
The Journal of the Acoustical Society of America (impact factor: 1.55). 04/2012; 131(4):3223. DOI:10.1121/1.4708019 pp.3223
Source: PubMed

ABSTRACT Sound perception of humans is determined by a variety of factors such as intensity, frequency, temporal structure, masking and localization. Furthermore, a wide range of non-acoustical factors determine whether certain sounds are perceived as annoying. However, classical exposure-response determination for the assessment of annoyance and health effects is based on average sound levels - sometimes with applied penalties for evening and night noise (Lden). A research collaboration between Ghent University and the Medical University Innsbruck focuses on the improvement of exposure-annoyance modeling by including characteristics of the temporal structure and the attention of the involved human subjects. The basis for this work is the developed "notice-event-model" (De Coensel B et al. 2009). Intensive traffic modeling as input for extended individual noise mapping per dwelling allows to test the additional impact by the inclusion of derived acoustical indicators of the temporal pattern (Fluctuation, emergence) of the main sources (highway, main road, railway) and the human activity pattern to accommodate for masking and habituation (e.g. Notice Sound Exposure Level, notice time). This improved exposure assessment is compared with the existing classical exposure-response information from two large-scale surveys in Austrian alpine valleys. The results show that this approach is promising - but further development is needed.

0 0
 · 
0 Bookmarks
 · 
17 Views

Keywords

acoustical indicators
 
classical exposure-response determination
 
De Coensel B
 
existing classical exposure-response information
 
exposure-annoyance modeling
 
human activity pattern
 
individual noise
 
Intensive traffic modeling
 
involved human subjects
 
large-scale surveys
 
main road
 
main sources
 
Medical University Innsbruck
 
night noise
 
Notice Sound
 
notice time
 
notice-event-model
 
Sound perception
 
temporal structure
 
wide range