↓ Skip to main content

A Review of the Possible Perceptual and Physiological Effects of Wind Turbine Noise

Overview of attention for article published in Trends in Hearing, August 2018
Altmetric Badge

Mentioned by

blogs
3 blogs
policy
2 policy sources
twitter
21 X users
facebook
1 Facebook page

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
36 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A Review of the Possible Perceptual and Physiological Effects of Wind Turbine Noise
Published in
Trends in Hearing, August 2018
DOI 10.1177/2331216518789551
Pubmed ID
Authors

Simon Carlile, John L. Davy, David Hillman, Kym Burgemeister

Abstract

This review considers the nature of the sound generated by wind turbines focusing on the low-frequency sound (LF) and infrasound (IS) to understand the usefulness of the sound measures where people work and sleep. A second focus concerns the evidence for mechanisms of physiological transduction of LF/IS or the evidence for somatic effects of LF/IS. While the current evidence does not conclusively demonstrate transduction, it does present a strong prima facia case. There are substantial outstanding questions relating to the measurement and propagation of LF and IS and its encoding by the central nervous system relevant to possible perceptual and physiological effects. A range of possible research areas are identified.

X Demographics

X Demographics

The data shown below were collected from the profiles of 21 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 31%
Student > Master 4 11%
Student > Bachelor 3 8%
Student > Ph. D. Student 3 8%
Student > Postgraduate 2 6%
Other 3 8%
Unknown 10 28%
Readers by discipline Count As %
Engineering 6 17%
Energy 4 11%
Medicine and Dentistry 2 6%
Neuroscience 2 6%
Psychology 2 6%
Other 7 19%
Unknown 13 36%