A Model of Sound Scattering by Atmospheric Turbulence for Use in Noise Mapping Calculations

Sound scattering due to atmospheric turbulence limits the noise reduction in shielded areas. An engineering model is presented, aimed to predict the scattered level for general noise mapping purposes including sound propagation between urban canyons. Energy based single scattering for homogeneous and isotropic turbulence following the Kolmogorov model is assumed as a starting point and a saturation based on the von Karman model is used as a first-order multiple scattering approximation. For a single shielding obstacle the scattering model is used to calculate a large dataset as function of the effective height of the shielding obstacle and its distances to source and receiver. A parameterisation of the dataset is used when calculating the influence of single or double canyons, including standardised air attenuation rates as well as facade absorption and Fresnel weighting of the multiple facade reflections. Assuming a single point source, an aver aging over three receiver positions and that each ground reflection causes energy doubling, the final engineering model is formulated as a scattered level for a shielding building without canyon plus a correction term for the effect of a single or a double canyon, assuming a flat rooftop of the shielding building. Input parameters are, in addition to geometry and sound frequency, the strengths of velocity and temperature turbulence

Urban background noise mapping: The multiple-reflection correction term

Mapping of road traffic noise in urban areas according to standardized engineering calculation methods systematically results in an underestimation of noise levels at areas shielded from direct exposure to noise, such as inner yards. In most engineering methods, road traffic lanes are represented by point sources and noise levels are computed utilizing point-to-point propagation paths. For a better prediction of noise levels in shielded urban areas, an extension of engineering methods by an attenuation term Acan has been proposed, including multiple reflections of the urban environment both in the source and in the receiver area. The present work has two main contributions for the ease of computing Acan. Firstly, it is shown by numerical calculations that Acan may be divided into independent source and receiver environment terms, As and Ar. Based on an equivalent free field analogy, the distance dependence of these terms may moreover be expressed analytically. Secondly, an analytical expression is proposed to compute As and Ar for 3D configurations from using 2D configurations only. The expression includes dependence of the street width-to-height ratio, the difference in building heights and the percentage of facade openings in the horizontal plane. For the expression to be valid, the source should be separated from the receiver environment by at least four times the street width. © S. Hirzel Verlag EAA

Classifying urban public spaces according to their soundscape

Cities are composed of many types of outdoor spaces, each with their distinct soundscape. Some of these soundscapes can be extraordinary, others are often less memorable. However, most locations in a city are not visited with the purpose of experiencing the soundscape. Consequently, the soundscape will not necessarily attract attention. Existing methods based on the circumplex model of affect classify soundscapes according to the pleasure and arousal they evoke, but do not fully take into account the goals and expectations of the listener. Therefore, in earlier work, a top-level hierarchical classification method was developed, which distinguishes between spaces based on the degree to which the soundscape creates awareness of the acoustical environment, matches expectations and arouses the listener. This paper presents the results of an immersive laboratory experiment, designed to validate this classification method. The experiment involved 40 participants and 50 audiovisual recordings drawn from the Urban Soundscapes of the World database. It is shown that the proposed classification method results in clearly distinct classes, and that membership to these classes can be explained well by physical parameters, extracted from the acoustical environment as well as the visual scene