The development and validation of a model for dynamic traffic noise prediction is presented. The model is composed of a GIS-based traffic microsimulation part coupled with an emission model, and a beamtrace-based 2.5D propagation part, which takes into account multiple reflections and diffractions. The model can be used to analyze the influence of real urban traffic situations (e.g., traffic flow management, road saturation) in the usual equivalent sound level maps. However, it also allows to calculate and visualize statistical noise levels and indicators derived from them. Novel descriptors based on the power spectrum of noise level fluctuations can be obtained. A part of Gentbrugge, Belgium, is taken as a validation area; different traffic demand scenarios are simulated.

The influence of noise on the quality of the urban living environment has traditionally been studied focusing on negative effects on man, such as noise annoyance and sleep disturbance. Recently a more holistic approach, including positive and negative aspects as well as non-residential functions of the urban environment, has gained renewed interest. The label ''urban soundscape'' is often used to refer to this approach. Research towards quantification of the acoustic descriptors of the urban soundscape is, however, still in an early stage. This paper draws on the analogy with music to propose an indicator for studying the temporal structure of the urban soundscape. The link to self-organized criticality of the underlying system is drawn. The influence on the new indicator of road traffic noise, an important soundscape disturber in urban areas, is analyzed in detail. r

An approach is proposed to shed light on the mechanisms underlying human perception of environmental sound that intrudes in everyday living. Most research on exposure-effect relationships aims at relating overall effects to overall exposure indicators in an epidemiological fashion, without including available knowledge on the possible underlying mechanisms. Here, it is proposed to start from available knowledge on audition and perception to construct a computational framework for the effect of environmental sound on individuals. Obviously, at the individual level additional mechanisms (inter-sensory, attentional, cognitive, emotional) play a role in the perception of environmental sound. As a first step, current knowledge is made explicit by building a model mimicking some aspects of human auditory perception. This model is grounded in the hypothesis that long-term perception of environmental sound is determined primarily by short notice-events. The applicability of the notice-event model is illustrated by simulating a synthetic population exposed to typical Flemish environmental noise. From these simulation results, it is demonstrated that the notice-event model is able to mimic the differences between the annoyance caused by road traffic noise exposure and railway traffic noise exposure that are also observed empirically in other studies and thus could provide an explanation for these differences.

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