Resource Documents: Noise (630 items)
Documents presented here are not the product of nor are they necessarily endorsed by National Wind Watch. These resource documents are provided to assist anyone wishing to research the issue of industrial wind power and the impacts of its development. The information should be evaluated by each reader to come to their own conclusions about the many areas of debate.
Author: Marcillo, Omar; et al.
Infrasound from a 60‐turbine wind farm was found to propagate to distances up to 90 km under nighttime atmospheric conditions. Four infrasound sensor arrays were deployed in central New Mexico in February 2014; three of these arrays captured infrasound from a large wind farm. The arrays were in a linear configuration oriented southeast with 13, 54, 90, and 126 km radial distances and azimuths of 166°, 119°, 113°, and 111° from the 60 1.6 MW turbine Red Mesa Wind Farm, Laguna Pueblo, New Mexico, USA. Peaks at a fundamental frequency slightly below 0.9 Hz and its harmonics characterize the spectrum of the detected infrasound. The generation of this signal is linked to the interaction of the blades, flow gradients, and the supporting tower. The production of wind‐farm sound, its propagation, and detection at long distances can be related to the characteristics of the atmospheric boundary layer. First, under stable conditions, mostly occurring at night, winds are highly stratified, which enhances the production of thickness sound and the modulation of other higher‐frequency wind turbine sounds. Second, nocturnal atmospheric conditions can create low‐altitude waveguides (with altitudes on the order of hundreds of meters) allowing long‐distance propagation. Third, night and early morning hours are characterized by reduced background atmospheric noise that enhances signal detectability. This work describes the characteristics of the infrasound from a quasi‐continuous source with the potential for long‐range propagation that could be used to monitor the lower part of the atmospheric boundary layer.
Omar Marcillo, Philip Blom, Earth and Environmental Science, Los Alamos National Laboratory, Los Alamos, New Mexico
Stephen Arrowsmith, Kyle Jones, Sandia National Laboratories, Albuquerque, New Mexico
Journal of Geophysical Research: Atmosphere, 120, 9855–9868, doi:10.1002/2014JD022821.
Observation and comparison of tower vibration and underwater noise from offshore operational wind turbines in the East China Sea Bridge of Shanghai
Author: Yang, Chun-Mei; Liu, Zong-Wei; Lü, Lian-Gang; et al.
[Abstract] Underwater operational turbine noise emitted by China’s first offshore wind farm in the East China Sea Bridge of Shanghai was measured and analyzed in this study. Two sensors were used in the measurement: a hydrophone recording the underwater sound and an accelerometer placed in the turbine tower detecting the tower vibrations. Measurements were performed at two different types of wind turbines: a Sinovel 3 MW SL3000 turbine and a Shanghai Electric 3.6 MW W3600 turbine. The two turbines show similar tower vibration characteristics, characterized by a number of tonal components, mainly in the low-frequency domain (30-500 Hz). The peak vibration frequencies changed with the wind speed until the turbine approached its nominal power rating. Spectral analysis of the underwater acoustic data showed that the amplitude spectra had a strong correlation with the spectra of the turbine vibration intensity level, indicating that the measured underwater noise was generated by the tower mechanical vibration.
Chun-Mei Yang, Zong-Wei Liu, Lian-Gang Lü, Guang-Bing Yang, Long-Fei Huang, and Ying Jiang
Key Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, State Oceanic Administration, Qingdao, China
Journal of the Acoustic Society of America 2018 Dec;144(6):EL522. doi: 10.1121/1.5082983.
Author: Nguyen, Duc-Phuc; Hansen, Kristy; and Zajamsek, Branko
[ABSTRACT] In addition to the overall noise level, periodic variations in the loudness of wind turbine noise, known as Amplitude Modulation (AM), also significantly contribute to the annoyance experienced by residents living near wind farms. Due to the high dependence of AM on meteorological conditions and the type of wind turbines, the level and duration of AM are hard to predict. These characteristics have an important impact on the annoyance response of residents. The level of annoyance is expected to depend on the AM depth, the number of AM occurrences and the AM continuity. The aim of this paper is to investigate AM characteristics in the vicinity of two wind farms in South Australia. It has been found that to successfully quantify tonal AM based on the Reference Method proposed by the UK Institute of Acoustics, removing the A-weighting, changing the range of band-pass filter frequency and reducing the prominence ratio are also necessary. AM density at night-time is much higher than at day time (25% versus 15%). However, there is not significant difference between AM depth at night-time and day time. Furthermore, AM is more likely to occur when the wind turbines are operating significantly below their maximum rated power.
Duc-Phuc Nguyen, Kristy Hansen
College of Science and Engineering
Adelaide Institute for Sleep Health
Flinders University, Bedford Park, Adelaide, SA, Australia
Download original document: “Characterizing tonal amplitude modulation of wind farm noise” (22 MB)
Author: Higher Regional Court of Munich
‘The defendant is ordered to cease operation of the wind power plant erected and operated on Plot no. 146 in the township of Ammerfeld, brand ENERCON E-82n, 2 MW capacity, hub height 138 metres, rotor diameter 82 metres, total height 179 metres, during the period of 22:00 hours to 06:00 hours, at a night emission rate of more than 45 dB(A) that is measurable at the residential building of the plaintiffs in 1) and 2) at 86688 Marxheim, St.-Gertraud-Straße 15.’
Higher Regional Court of Munich, Augsburg, August 14, 2012
Download original document: “Sanders and Rosskopfs versus Bavaria Windpark”
[translated by Simone Gabbay, translator for All Languages, Toronto, Ontario, paid for by a citizen of Ontario]