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Differences between Outdoor and Indoor Sound Levels for Open, Tilted, and Closed Windows.

Barbara LocherAndré PiquerezManuel HabermacherMartina RagettliMartina S RagettliMark BrinkChristian CajochenDanielle VienneauMaria ForasterUwe MüllerJean Marc Wunderli
Published in: International journal of environmental research and public health (2018)
Noise exposure prediction models for health effect studies normally estimate free field exposure levels outside. However, to assess the noise exposure inside dwellings, an estimate of indoor sound levels is necessary. To date, little field data is available about the difference between indoor and outdoor noise levels and factors affecting the damping of outside noise. This is a major cause of uncertainty in indoor noise exposure prediction and may lead to exposure misclassification in health assessments. This study aims to determine sound level differences between the indoors and the outdoors for different window positions and how this sound damping is related to building characteristics. For this purpose, measurements were carried out at home in a sample of 102 Swiss residents exposed to road traffic noise. Sound pressure level recordings were performed outdoors and indoors, in the living room and in the bedroom. Three scenarios-of open, tilted, and closed windows-were recorded for three minutes each. For each situation, data on additional parameters such as the orientation towards the source, floor, and room, as well as sound insulation characteristics were collected. On that basis, linear regression models were established. The median outdoor-indoor sound level differences were of 10 dB(A) for open, 16 dB(A) for tilted, and 28 dB(A) for closed windows. For open and tilted windows, the most relevant parameters affecting the outdoor-indoor differences were the position of the window, the type and volume of the room, and the age of the building. For closed windows, the relevant parameters were the sound level outside, the material of the window frame, the existence of window gaskets, and the number of windows.
Keyphrases
  • air pollution
  • particulate matter
  • minimally invasive
  • healthcare
  • public health
  • mental health
  • climate change
  • health information
  • big data
  • human health
  • data analysis