Spatial and temporal determinants of A-weighted and frequency specific sound levels-An elastic net approach

Environ Res. 2017 Nov;159:491-499. doi: 10.1016/j.envres.2017.08.034. Epub 2017 Sep 18.

Abstract

Background: Urban sound levels are a ubiquitous environmental stressor and have been shown to be associated with a wide variety of health outcomes. While much is known about the predictors of A-weighted sound pressure levels in the urban environment, far less is known about other frequencies.

Objective: To develop a series of spatial-temporal sound models to predict A-weighted sound pressure levels, low, mid, and high frequency sound for Boston, Massachusetts.

Methods: Short-term sound levels were gathered at n = 400 sites from February 2015 - February 2016. Spatial and meteorological attributes at or near the sound monitoring site were obtained using publicly available data and a portable weather station. An elastic net variable selection technique was used to select predictors of A-weighted, low, mid, and high frequency sound.

Results: The final models for low, mid, high, and A-weighted sound levels explained 59 - 69% of the variability in each measure. Similar to other A-weighted models, our sound models included transportation related variables such as length of roads and bus lines in the surrounding area; distance to road and rail lines; traffic volume, vehicle mix, residential and commercial land use. However, frequency specific models highlighted additional predictors not included in the A-weighted model including temperature, vegetation, impervious surfaces, vehicle mix, and density of entertainment establishments and restaurants.

Conclusions: Building spatial temporal models to characterize sound levels across the frequency spectrum using an elastic net approach can be a promising tool for noise exposure assessments within the urban soundscape. Models of sound's character may give us additional important sound exposure metrics to be utilized in epidemiological studies.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Boston
  • Environmental Monitoring*
  • Models, Theoretical
  • Noise, Transportation
  • Urban Health*