Noise from wind turbine blades is five times more likely to be heard at night, according to two new studies.
Researchers at Flinders University, Australia, are using machine learning and other signal processing techniques to characterise annoying noise features from wind farms.
The new studies found that night-time ‘swoosh’ sound – technical referred to as amplitude modulation (AM) from wind turbines – is likely to be heard by neighbouring residents up to five times more often than during daylight hours, depending on wind direction, season and wind farm distance.
Flinders University PhD candidate Phuc Nguyen said: “We found that the amount of amplitude modulation present during the daytime versus night-time varies substantially occurring two to five times more often during the night-time compared to the daytime.
“The noise seems to worsen after sunset when amplitude modulation can be detected for up to 60% of the night-time at distances around 1 km from a wind farm.
“At greater than 3 km, amplitude modulation also occurs for up to 30% of the night-time.”
The Wind Farm Noise Study, based at the Adelaide Institute for Sleep health at Flinders University, is investigating noise characteristics and sleep disturbances at residences located near wind farms.
The association between wind turbine noise and adverse effects on humans is an ongoing debate.
Acoustic expert Dr Kristy Hansen, who also worked on the studies, said the directional nature of wind turbine noise means residents living in downwind and crosswind conditions are likely to be more disturbed by wind turbines.
She said: “We found that AM occurs most often during these wind directions.
“Using these recent advances in machine learning, we have been able to develop an AM detection method that has a predictive power close to the practical limit set by a human listener.
“This includes the noise that increases and decreases as the blades rotate, or AM, including a ‘swoosh’ sound, which further contributes to the negative effects of wind turbine noise.
“These studies advance our ability to measure and monitor the noise from wind turbines that is likely to be more annoying that other noise types at the same level.”