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Exploring spatial patterns of environmental noise and perceived sound source dominance in urban areas. Case study: the city of Athens, Greece

Dimitris MARKOU Downloads: 312

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Published: 2022/04/15 DOI:

Open Access

Keywords: Noise mapping, Perceived sound source dominance, Acoustic environment, Urban areas, Athens


The aim of the present study is to map spatial patterns related to noise pollution and the acoustic environment -in a broader context- in the urban area of Athens, Greece. The primary goal of this thesis is to present a comprehensive approach that combines elements of two basic methodologies related to acoustic environment studies: a) noise mapping and b) the soundscape approach. The main inputs are environmental noise measurements and perceptual sound source-related observations. The results feature three noise pollution maps (LAeq,30 sec, L10, and L90 indices) and three sound source maps which reflect the way in which the human ear perceives the presence of sounds. Additionally, the question of whether the spatial distribution of sound source dominance can be explained by the dispersion of environmental noise levels was examined using geographically weighted regressions (GWR). The GWR models showed that sound source-related observations are explained to a significant extent by all three indicators. Four important findings emerge from the analysis. Firstly, areas with high levels of noise pollution are characterized by high to moderate presence of technological and absence of anthropic and natural sounds. Secondly, regions, where there is a simultaneous presence of all sound sources, are characterized by moderate to low noise levels. Thirdly, the absence of technological sounds is observed in quiet areas. Finally, areas featuring a moderate presence of technological and natural sounds are mostly urban green spaces built-in proximity to the main road network.

Highlights:- Comprehensive methodology combining elements of noise mapping and soundscape approach - Using Kriging Spatial Interpolation and Geographically Weighted Regression techniques - Sound source dominance is explained to a significant extent by noise levels - Absence of anthropic and natural sounds in high noise-affected areas - Absence of technological sounds in quiet areas

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