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  Table of Contents    
Year : 2011  |  Volume : 13  |  Issue : 54  |  Page : 333-339
Evaluating the impact of wind turbine noise on health-related quality of life

1 Department of Psychology, School of Public Health, Auckland University of Technology, Auckland, NewZealand
2 Department of Preventive and Social Medicine, University of Otago, Dunedin, NewZealand
3 School of Population Health, The University of Auckland, Auckland, NewZealand

Click here for correspondence address and email
Date of Web Publication28-Sep-2011

We report a cross-sectional study comparing the health-related quality of life (HRQOL) of individuals residing in the proximity of a wind farm to those residing in a demographically matched area sufficiently displaced from wind turbines. The study employed a nonequivalent comparison group posttest-only design. Self-administered questionnaires, which included the brief version of the World Health Organization quality of life scale, were delivered to residents in two adjacent areas in semirural New Zealand. Participants were also asked to identify annoying noises, indicate their degree of noise sensitivity, and rate amenity. Statistically significant differences were noted in some HRQOL domain scores, with residents living within 2 km of a turbine installation reporting lower overall quality of life, physical quality of life, and environmental quality of life. Those exposed to turbine noise also reported significantly lower sleep quality, and rated their environment as less restful. Our data suggest that wind farm noise can negatively impact facets of HRQOL.

Keywords: Amenity, annoyance, health-related quality of life, sleep quality, wind turbine noise

How to cite this article:
Shepherd D, McBride D, Welch D, Dirks KN, Hill EM. Evaluating the impact of wind turbine noise on health-related quality of life. Noise Health 2011;13:333-9

How to cite this URL:
Shepherd D, McBride D, Welch D, Dirks KN, Hill EM. Evaluating the impact of wind turbine noise on health-related quality of life. Noise Health [serial online] 2011 [cited 2023 Dec 10];13:333-9. Available from: https://www.noiseandhealth.org/text.asp?2011/13/54/333/85502

  Introduction Top

Wind turbines transform wind energy into electricity, a practice dating back over 100 years. However, in the last decade industrial-scale harvesting of wind energy has increased, driven by a desire to generate sustainable energy and to lessen the impact of fossil fuel depletion. Whether located in isolation or as components of a "wind farm", wind turbines were initially welcomed by many communities due to their environmental credentials, though reference to the mainstream media shows that public opposition to wind turbines has increased substantially in the past few years. [1] Complaints against established wind farms, or concern elicited by proposed wind farms, focus on the noise they produce, or the visual impact they have on the environment.

The desire to maximize electricity production while minimizing transmission costs means that in many countries wind farms have been constructed in semirural areas (also known as "greenbelt" or "life-style" areas) close to major towns and cities. Noise from wind farms located in semirural areas is of interest because it is typically a low amplitude noise impeding on a well-characterized and generally cherished soundscape. Consequently, there has been considerable debate over whether wind farm noise poses a significant health threat to those living in their vicinity. It has been suggested that wind turbines can directly impact health via the emission of low-frequency sound energy (i.e., infrasound below 20 Hz), though this is currently an area of controversy. [2],[3] Additionally, wind turbines may compromise health by producing sound that is annoying and/or can disturb sleep. In this respect, it can be classified as community noise along side industrial or transportation noise. When built in semirural settings, the visual impact of wind farms can also degrade amenity and interact with wind turbine noise to exacerbate annoyance reactions, [4] possibly due to a violation of the landscape--soundscape continuum constructed by those who choose to live in these areas. [5]

[Figure 1] represents a simple model informed by the literature [6],[7] demonstrating that, in the semirural context, there are feasible mechanisms by which wind turbine exposure can degrade health and well-being. Turbine noise can lead directly to annoyance and sleep disturbance (primary health effects), or can induce annoyance by degrading amenity. Additionally, the trait of noise sensitivity, which describes individuals who are more likely to pay attention to sound, evaluate sound negatively, and have stronger emotional reactions to noise, [8] constitutes a major risk factor. The secondary heath effects would be immediate reductions in general well-being, with stress-related disease emerging from chronic annoyance and sleep disturbance. Irrespective of source, chronic noise exposure is a psychosocial stressor that can induce maladaptive psychological responses and negatively impact health via interactions between the autonomic nervous system, the neuroendocrine system, and the immune system. [7] A chronic stress response will, in turn, degrade quality of life [Figure 1].
Figure 1: A schematic representation of the relationship between wind turbines and health in a semirural setting. The multiplicity of relationships emerges due to variability in the response of individuals to noise

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Quantifying the impact of wind turbines on individual health will inform wind turbine operational guidelines, and in this respect constitutes an important process that is currently not far advanced. A variety of outcome measures have been proposed to assess the impacts of community noise, including annoyance, sleep disturbance, cardiovascular disease, and cortisol levels. [9] An alternative approach to health assessment involves the subjective appraisal of health-related quality of life (HRQOL), a concept that measures general well-being and well-being in the physical, psychological, and social domains. Because changes in HRQOL are expected to closely co-vary with changes in health, the WHO recommends the use of HRQOL measures as an outcome variable, arguing that the effects of noise are strongest for those outcomes classified under HRQOL rather than illness. [9] HRQOL is related to health by the WHO (1948) definition of health as "a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity," and can be considered as an operationalization of the well-being concept. [10]

There is scientific evidence linking community noise to health problems. [7],[9],[10] The WHO reports that chronic noise-induced annoyance and sleep disturbance can compromise health and HRQOL. [9],[11],[12] However, there has been little research examining the relationship between noise and HRQOL. An exception is Dratva et al., [13] who, using the Short Form (SF36) health survey, reported an inverse relationship between annoyance from traffic noise and HRQOL. They argued that HRQOL would be expected to co-vary more with annoyance than with noise level as level is generally a poor predictor of the human response to noise, and its role in health is commonly overemphasized. As alternatives to noise level, other factors associated with the listener should be considered, [6] including the perceived control a person has over the noise, as well as their attitudes, personality, and age (all of which could be added to [Figure 1] as moderators).

This exploratory study examines the association between HRQOL and proximity to an industrial wind farm in a semirural area, adding to the small number of peer-reviewed studies into the health impacts of wind turbines that are only beginning to appear in the literature. Case studies supported by qualitative analyses [2],[14],[15] suggest a negative relationship between wind turbine noise and well-being. There have been no previous quantitative investigations of the impact of wind farms on HRQOL, though correlations have been observed between wind turbine noise, annoyance, and sleep disruption. [16],[17] Given these findings, and with reference to [Figure 1], it would be expected that both mean amenity and sleep satisfaction scores would be lower in individuals residing around turbines, and that the proportion of individuals annoyed by noise would be greater for those exposed to turbines than those not. Additionally, lowered amenity and greater annoyance should result in lower mean HRQOL domains in those residing close to wind turbines.

  Materials and Methods Top


A nonequivalent comparison group posttest-only study design was utilized. Strict socioeconomic matching was undertaken using the New Zealand Deprivation Index 2006, [18] as described elsewhere. [19] Both areas are classified as semirural, [20] with a population density of less than 15 people per square kilometer.


Samples were drawn from two demographically matched areas differing only in their distances from a wind farm in the Makara Valley, a coastal area 10 km west of New Zealand's capital city, Wellington. The Makara Valley is characterized by hilly terrain, with long ridges running 250-450 m above sea level, on which 66 125 m high wind turbines are positioned as part of the "West Winds" project. [Figure 2] is a map showing the positions of a subset of wind turbines relative to some of the houses in valley. The first sample (the Turbine group) was drawn from residents in the South Makara Valley who resided in 56 houses located within 2 km of a wind turbine. A comprehensive noise survey of the area was undertaken independently, indicating intrusive elements of the turbine noise such as the "rumble-thump." [21] The Makara turbines, operational since May 2009, have measured levels that are consistent with levels reported in European studies, [17] in which typical noise exposures from wind turbines ranged from between 24 dB(A) and 54 dB(A). Long-term measurements undertaken by the wind farm developers at various residences show that while average outdoor levels (L 95 (10 min) dB(A)) are largely compliant with consent conditions, they still range between 20 dB(A) and 50 dB(A) depending on meteorological conditions. [22] The second sample (the Comparison group) was taken from residents in 250 houses in a geographically and socioeconomically matched area, but which were located at least 8 km from any wind farm in the region.
Figure 2: Map showing a part of the Makara Valley and the relative distances between houses and 14 of the 66 turbines. The wind turbines (Siemens SWT-2.3-82 VS) have 68 m high towers and rotor diameters of 82 m (Map generated by Rachel Summers, and displayed with permission).

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The coversheet of the questionnaire bore the title 2010 Well-being and Neighbourhood Survey, designed to mask the true intent of the study. Each house received two copies of the questionnaire. Potential participants were invited to participate in the research investigating their place of living and their well-being if they resided at the address to which the questionnaire had been delivered and if they were 18 years or older. The order of the questions was a prime consideration: HRQOL (26 items), amenity (2 items), neighbourhood problems (14 items), annoyance (7 items), demographic information (7 items), and a single item probing noise sensitivity. All scale items were presented on a numbered five-point scale with appropriate descriptors anchoring the terminals. Self-reported HRQOL was measured using the abbreviated version of the WHOQOL-BREF which affords composite measures of physical (7 items), psychological (6 items), and social (3 items) HRQOL. Additionally, the WHOQOL-BREF has two generic items asking about general health and overall quality of life, and an additional domain measuring and environmental QOL (8 items). The two amenity items were: "I am satisfied with my neighbourhood/living environment" and "My neighbourhood /living environment makes it difficult for me to relax at home." A modified neighbourhood problem scale [23] consisted of 14 distracter items that were not relevant to the current study and were not included in the analysis. Seven items on annoyance were included, four distracter items asking about air quality, and three items probing annoyance to traffic, other neighbours, or other noise (please specify). Additionally, participants were asked if they were not noise sensitive, moderately noise sensitive, or very noise sensitive. The questionnaire terminated with an open-ended item asking "If you would like to share any comments relating to your neighbourhood or this survey then please do so in the box below." Participants were asked to respond to all items and to return surveys by post in the prepaid envelopes provided.


Self-reported age and sex measures were obtained and self-reported level of educational status used as a further indicator of socioeconomic status. Additionally, participants were asked what their current employment status was, and whether they were currently ill or had a medical condition. Participants were also asked how long they had lived at their current residence.

Statistical analysis

Analysis commenced after an evaluation of each scale's psychometric properties, including inspection for floor and ceiling effects and tests of internal consistency (Cronbach's alpha) and to validate dimensionality (corrected item-total correlations). Differences in HRQOL and amenity between the turbine and comparison groups were calculated using univariate analysis of covariance (ANCOVA), with length of residence selected a priori as a covariate. All testing was undertaken in accordance with Tabachnick and Fidell's [24] guidelines for testing between groups with unequal sample sizes, and Bonferroni corrections were applied where appropriate. Because of the unequal sizes between the two groups the assumptions of normality and homogeneity of variance were assessed carefully. Five cases were excluded from the comparison group because they were multivariate outliers as defined by extreme Mahalanobis distances, with response set acquiescence clearly evident in all five cases.

  Results Top

The response rates, 34% and 32% from the turbine and comparison groups, respectively, are typical for this type of research (e.g., van den Berg and colleagues [17] report a 37% response rate). [Table 1] presents demographic information for the comparison and turbine groups. Prior to analyses the data were screened to identify potential confounds. The proportions of males and females in each area were equivalent (χ2 (1) = 0.001, P = 0.967), while a Mann--Whitney U indicated no age difference between the two areas (U(n1 = 158 , n2 =39) = 16022.5, P0 = 0.802). Education (χ2 (2) = 2.474, P = 0.291), noise sensitivity (χ2 (2) = 0.553, P = 0.758), and self-reported illness (χ2 (1) = 0.414, P = 0.562) were not associated with area.
Table 1: Demographic profile of the turbine and comparison groups

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[Table 2] displays correlation coefficients (Pearson's r) between noise-related and health-related variables for both groups. Of remark is the negative correlation between annoyance and self-rated health for both groups, and a different pattern of correlations between noise sensitivity and annoyance across the two groups. Separate ANCOVA's revealed differences and similarities between the two areas in terms of HRQOL [Table 3]. Firstly, the turbine group reported a lower (F(1,194) = 5.816 , P = 0.017) mean physical HRQOL domain score than the comparison group. Scrutiny of the seven facets of the physical domain showed a difference in perceived sleep quality between the two areas (t(195) = 3.089, P = 0.006), and between self-reported energy levels (t(195)= 2.217, P = 0.028). Secondly, the turbine group had lower (F(1,194) = 5.694 , P = 0.018) environmental QOL scores than the comparison group. This domain is the sum of eight items, and further analysis of these revealed that the turbine group considered their environment to be less healthy (t(195)= 3.272, P < 0.007) and were less satisfied with the conditions of their living space (t(195)= 2.176, P = 0.031). Thirdly, there were no statistical differences in social (F(1,194) = 0.002 , P = 0.963) or psychological (F(1,194) = 3.334, P = 0.069) HRQOL, although the latter was marginal and the mean for the turbine group was lower. Of the two generic WHOQOL-BREF items, the mean of the self-rated general health item was equivalent between turbine and comparison groups (t(195) = 0.374, P = 0.709), while the mean ratings for an overall quality of life item was lower (t(195) = 2.364, P = 0.019) in the turbine group.
Table 2: Pearson product-moment correlation coefficients (r) for noise-related and HRQOL variables. Statistics to the right of the major diagonal are for the comparison group, while those to the left are for the turbine group

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Table 3: Mean (M) and standard deviation (SD) statistics for the four HRQOL domains of the WHOQOL-BREF and amenity total scores, presented for both the comparison group and the turbine group

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The turbine group reported lower amenity than the comparison group (F(1,194) = 18.88, P < 0.001). There were no differences between groups for traffic (t(195) = 0.568, P = 0.154) or neighborhood (t(195) = 1.458, P = 0.144) noise annoyance. A comparison between ratings of turbine noise was not possible, but the mean annoyance rating for turbine group individuals who specifically identified wind turbine noise as annoying (n=23) was 4.59 (SD = 0.65), indicating that the turbine noise was perceived as extremely annoying. For the comparison group, seven "other" annoying noises were identified: barking dogs (x2), farm machinery (x2), and racing cars (x3).

  Discussion Top

Our results link exposure to wind turbines to degraded HRQOL, a finding that is consistent with the model described in [Figure 1]. Specifically, those residing in the immediate vicinity of a wind farm scored worse than a matched comparison group in terms of physical HRQOL and environmental QOL, and HRQOL in general. No differences were found in terms of psychological and social HRQOL, or in self-rated health. The high incidence of annoyance from turbine noise in the turbine group is consistent with the theory that exposure to wind turbine noise is the cause of these differences. Importantly, we also found a reduction in sleep satisfaction ratings, suggesting that both annoyance and sleep disruption may mediate the relationship between noise and HRQOL. These findings are consistent with those reported in relation to aviation noise [25] and traffic noise. [10],[11]

Of further interest are the likely mechanisms involved in the degradation of HRQOL when exposed to turbine noise. Studies show that the level of turbine noise is a poor predictor of human response, and dose-response relationships typically explain little of the association between turbine noise and annoyance. [26] Pedersen et al. [4],[26] and van den Berg et al. [15] show that, for equivalent noise levels, people judge wind turbine noise to be of greater annoyance than aircraft, road traffic, or railway noise. This may be due to the unique characteristics of turbine noise, that is, clusters of turbines present a cumulative effect characterized by a dynamic or modulating sound as turbines synchronise. The characteristic swishing or thumping noise associated with larger turbines [21] is audible over long distances, up to 5 km and beyond in some reports. [1]

van den Berg [17] showed that sound is the most annoying aspect of wind turbines, and is more of a problem at night. A large proportion (23/39) of respondents from the turbine group identified turbine noise as a problem and rated it to be extremely annoying. It should be noted that, in contemporary medicine, annoyance exists as a precise technical term describing a mental state characterized by distress and aversion, which if maintained, can lead to a deterioration of health and well-being. [25] A Swedish study [26] reported that, for respondents who were annoyed by wind turbine noise, feelings of resignation, violation, strain, and fatigue were statistically greater than for respondents not annoyed by turbine noise. An attempt at constructing dose-response relationships between turbine noise level and annoyance in a European sample suggests that at calculated noise levels of 30-35 dB(A), 10% of the sample was rather or very annoyed at wind turbine sound, increasing to 20% at 35-40 dB(A) and 25% at 40-43 dB(A). [15]

We also observed lower sleep satisfaction in the turbine group than in the comparison group, a finding which is consistent with previous research. [2],[4],[17] One study directly related to wind turbine noise reported that 16% of respondents experiencing 35 dB(A) or more of noise suffered sleep disturbances due to turbine noise. [4] Another study investigating the effects of wind turbine noise on sleep showed that 36% of respondents who were annoyed at wind turbine noise also reported that they suffered disturbed sleep (versus 9% of those not annoyed). [15] A case-study approach examining exposure to turbine noise likewise identified turbine noise as an agent of sleep disturbance. [11] In relation to turbine noise levels, one study reported that even at the lowest noise levels (≈25 dB(A)), 20% of respondents reported disturbed sleep at least one night per month, [17] and that interrupted sleep and difficulty in returning to sleep increased with calculated noise level. Demonstrably, our data have also captured the effects of wind turbine noise on sleep, reinforcing previous studies suggesting that the acoustic characteristics of turbine noise are well suited to disturb the sleep of exposed individuals.

While strong correlations exist between the sound level and the perceived loudness of a sound, there is no clear relationship between level and the psychological responses that individuals have to a sound. Noise sensitivity is one psychological factor that is increasingly being related to noise annoyance in literature. [8] We found that, for the turbine group, noise sensitivity is a strong predictor of noise annoyance and is correlated with facets of HRQOL, supporting other studies suggesting that annoyance mediates the relationship between noise sensitivity and HRQOL. [25] Other studies show that noise sensitivity has a large impact on noise annoyance ratings, lowering annoyance thresholds by up to 10 dB. [8] The lack of statistical significance in the comparison group may indicate that, in the absence of annoying noise, the impact of noise sensitivity on HRQOL may be underestimated.

Another finding emerging from our data is that living close to wind turbines is associated with degraded amenity. This is consistent with previous research showing that wind turbine noise was judged incongruent with the natural soundscape of the area. [23] Amenity values are based upon what people feel about an area, its pleasantness, or some other value that makes it a desirable place to live. There is an expectation of "peace and quiet" when living in a rural area, and most choose to live in rural areas for this reason. [25] Furthermore, those who live in rural areas have different expectations about community noise than those living elsewhere. [4] Other studies [27],[28] report that wind turbines are viewed as eyesores and visual spoilers of the environment, and from an aesthetic perspective, those who view the wind turbines as ugly are likely to disassociate them from the landscape and react more strongly to turbine noise. The measurement of the perceived visual impact of the wind farm was beyond the scope of the current study, specifically due to the masking of the study's intent. Scrutiny of the comments provided by the turbine group, however, revealed no mention of the impact of turbines on the landscape, reinforcing suggestions made by others, [5] that wind farm noise is more dominant than their visual aspects.

Strengths and limitations

A strength of this study is the masking of the primary intent of the questionnaire by giving the impression that general neighborhood factors (e.g., street lighting, rubbish collection), and not wind turbine exposure, constituted the study's core aims. Concealing the study's objectives should reduce response bias, and our placing of the HRQOL items at the beginning of the survey, well before the three items probing noise annoyance, would serve to elicit subjective ratings of HRQOL without first being primed with potentially upsetting noise items. A further strength is the use of a nationally validated inventory that adopts a multidimensional approach to HRQOL.

The main limitation of the study, partly forced by our desire to conceal the aim of the survey, was that coincident noise measurements were not obtained. While independent estimates of wind farm noise in the Makara Valley have been reported, [21],[22] it would have been desirable to undertake measurements in both the turbine and the control areas. That said, on the basis of the very few noise complaints made by those in the control areas (as described in the Results section), we are confident that the control areas provide typical semirural soundscapes that are not encroached by intrusive noise. An additional limitation of the study is the sample size of the turbine group. While the response rate compares favorably to other wind turbine research reported in the literature, [17] the sparsely populated locales surrounding wind farms in rural New Zealand presents a recruitment challenge. A larger sample of residents exposed to wind turbines would have afforded more analytical options. However, that the effects were found with such a modest sample size may be indicative of genuine differences between the two groups.

Any future adoption of the model presented in [Figure 1] should increase the number of moderators, and include factors such as attitudes to the noise source and individual coping strategies. For example, the conflict between the Makara community and the wind farm developers could also potentially reduce HRQOL or amplify annoyance reactions and sleep difficulties. A telephone complaint line, set up by the wind farm developer as a condition of consent, attracted over 1000 noise complaints in the first year. Such conflict would induce stress and emotional reactions that would be expected to degrade psychological HRQOL, though this was not found to be different from the control group. An explanation of this null result on the psychological domain may be derived from the open-ended comments from the control group, which reveal that they themselves are in conflict with local governance bodies attempting to increase residential dwellings in the area.

  Conclusion Top

A thorough investigation of wind turbine noise and its effects on health is important given the prevalence of exposed individuals, a nontrivial number that is increasing with the popularity of wind energy. [29] For example, in the Netherlands it is reported that 440,000 inhabitants (2.5% of the population) are exposed to significant levels of wind turbine noise. [30] Additionally, policy makers are demanding more information on the possible link between wind turbines and health in order to inform setback distances. Our results suggest that utility-scale wind energy generation is not without adverse health impacts on nearby residents. Thus, nations undertaking large-scale deployment of wind turbines need to consider the impact of noise on the HRQOL of exposed individuals. Along with others, [31] we conclude that night-time wind turbine noise limits should be set conservatively to minimize harm, and, on the basis of our data, suggest that setback distances need to be greater than 2 km in hilly terrain.

  Acknowledgments Top

We are grateful to our colleagues and others whose reviews substantially improved the manuscript. We are especially grateful for the thorough review undertaken by Professor Rex Billington, who as the WHO Director of Mental Health in the 1990s oversaw the development of the WHO's program into quality of life, health and the environment.

  References Top

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Correspondence Address:
Daniel Shepherd
School of Public Health, Auckland University of Technology, Private Bag 92006, Auckland 1142
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/1463-1741.85502

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  [Table 1], [Table 2], [Table 3]

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Noise Mapping. 2022; 9(1): 67
[Pubmed] | [DOI]
5 Music improves the therapeutic effects of bevacizumab in rats with glioblastoma: Modulation of drug distribution to the brain
Oxana Semyachkina-Glushkovskaya, Sergey Diduk, Eroshova Anna, Dosadina Elina, Kruglov Artem, Alexander Khorovodov, Alexander Shirokov, Ivan Fedosov, Alexander Dubrovsky, Inna Blokhina, Andrey Terskov, Nikita Navolokin, Arina Evsukova, Daria Elovenko, Viktoria Adushkina, Jürgen Kurths
Frontiers in Oncology. 2022; 12
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6 Association between UBAC2 gene polymorphism and the risk of noise-induced hearing loss: a cross-sectional study
Liu Wan, Ludi Zhang, Peng Sun, Lei Han, Hengdong Zhang, Baoli Zhu, Boshen Wang
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7 Adverse environmental impacts of wind farm installations and alternative research pathways to their mitigation
Nasimul Eshan Chowdhury, Mahmudul Alam Shakib, Fei Xu, Sayedus Salehin, Md Rashidul Islam, Arafat A. Bhuiyan
Cleaner Engineering and Technology. 2022; : 100415
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8 Soft-Median Selection: An adaptive feature smoothening method for sound event detection
Fengnian Zhao, Ruwei Li, Xin Liu, Liwen Xu
Applied Acoustics. 2022; 192: 108715
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9 Is it safe to live near wind turbines? Reviewing the impacts of wind turbine noise
Evangelia Karasmanaki
Energy for Sustainable Development. 2022; 69: 87
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10 Aeroelastic investigation and stability of small- and mid-scale wind turbine blades
Widad Yossri, Samah Ben Ayed, Abdessattar Abdelkefi
International Journal of Mechanics and Materials in Design. 2022;
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11 Renewable and Sustainable Energy Reviews: Environmental impact networks of renewable energy power plants
Viktor Sebestyén
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12 Health-Related Quality of Life across a Variety of Community Contexts
Daniel Shepherd, David Welch, David McBride, Kim N. Dirks
International Journal of Community Well-Being. 2021; 4(1): 17
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13 Noise vulnerability of stone mining and crushing in Dwarka river basin of Eastern India
Swades Pal, Indrajit Mandal
Environment, Development and Sustainability. 2021; 23(9): 13667
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14 Map Optimization Fuzzy Logic Framework in Wind Turbine Site Selection with Application to the USA Wind Farms
Gorg Abdelmassih, Mohammed Al-Numay, Abdelali El Aroudi
Energies. 2021; 14(19): 6127
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15 Perceptions of Wind Turbine Noise and Self-Reported Health in Suburban Residential Areas
Fei Qu, Aki Tsuchiya
Frontiers in Psychology. 2021; 12
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16 Evaluation of offshore wind power in the China sea
Yu-chi Tian, Lei kou, Yun-dong Han, Xiaodong Yang, Ting-ting Hou, Wen-kai Zhang
Energy Exploration & Exploitation. 2021; 39(5): 1803
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17 Impact of Bauxite Mining on Quality of Life: An Analysis of Road Users
N Rosli, R A Rahman, I S M Razelan, A Ismail, M Hasan
IOP Conference Series: Earth and Environmental Science. 2021; 682(1): 012040
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18 Experimental Investigation of Turbulence Effects on Aerodynamics Noise of Channeled NACA 0012 Airfoil
Hussein K. Mohammad, Latif Ibraheem, Viktor Kilchyk, Bade Shrestha
Journal of Solar Energy Engineering. 2021; 143(6)
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19 Health effects of wind turbines: a review of the literature between 2010-2020
Asli Ata Teneler, Hur Hassoy
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20 Acoustic Positioning System for 3D Localization of Sound Sources Based on the Time of Arrival of a Signal for a Low-Cost System
Dídac D.Tortosa, Iván Herrero-Durá, Jorge E. Otero
Engineering Proceedings. 2021; 10(1): 15
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21 Amplitude modulated wind farm noise relationship with annoyance: A year-long field study
Kristy L. Hansen, Phuc Nguyen, Gorica Micic, Bastien Lechat, Peter Catcheside, Branko Zajamšek
The Journal of the Acoustical Society of America. 2021; 150(2): 1198
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22 Noise pollution: acute noise exposure increases susceptibility to disease and chronic exposure reduces host survival
Numair Masud, Laura Hayes, Davide Crivelli, Stephen Grigg, Jo Cable
Royal Society Open Science. 2020; 7(9): 200172
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23 Phenomenon of music-induced opening of the blood-brain barrier in healthy mice
O. Semyachkina-Glushkovskaya, A. Esmat, D. Bragin, O. Bragina, A. A. Shirokov, N. Navolokin, Y. Yang, A. Abdurashitov, A. Khorovodov, A. Terskov, M. Klimova, A. Mamedova, I. Fedosov, V. Tuchin, J. Kurths
Proceedings of the Royal Society B: Biological Sciences. 2020; 287(1941): 20202337
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24 A laboratory study on the effects of wind turbine noise on sleep: results of the polysomnographic WiTNES study
Michael G Smith, Mikael Ögren, Pontus Thorsson, Laith Hussain-Alkhateeb, Eja Pedersen, Jens Forssén, Julia Ageborg Morsing, Kerstin Persson Waye
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25 Public perspectives on reducing the environmental impact of onshore wind farms: a discrete choice experiment in South Korea
Hye-Jeong Lee, Seung-Hoon Yoo, Sung-Yoon Huh
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26 Acceptance of wind power development and exposure – Not-in-anybody's-backyard
Anders Dugstad, Kristine Grimsrud, Gorm Kipperberg, Henrik Lindhjem, Ståle Navrud
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27 A Review of the Potential Impacts of Wind Turbine Noise in the Australian Context
John Laurence Davy, Kym Burgemeister, David Hillman, Simon Carlile
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28 Association Between Long-Term Exposure to Wind Turbine Noise and the Risk of Stroke: Data From the Danish Nurse Cohort
Elvira V. Bräuner, Jeanette T. Jørgensen, Anne Katrine Duun-Henriksen, Claus Backalarz, Jens E. Laursen, Torben H. Pedersen, Mette K. Simonsen, Zorana J. Andersen
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29 Clinical correlates of noise sensitivity in patients with acute TBI
Daniel Shepherd, Jason Landon, Mathew Kalloor, Alice Theadom
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30 Using residential proximity to wind turbines as an alternative exposure measure to investigate the association between wind turbines and human health
Rebecca Barry, Sandra I. Sulsky, Nancy Kreiger
The Journal of the Acoustical Society of America. 2018; 143(6): 3278
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31 Nuisances sanitaires des éoliennes terrestres
Patrice Tran ba Huy
Bulletin de l'Académie Nationale de Médecine. 2017; 201(4-6): 529
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32 Indoor noise annoyance due to 3–5 megawatt wind turbines—An exposure–response relationship
Valtteri Hongisto, David Oliva, Jukka Keränen
The Journal of the Acoustical Society of America. 2017; 142(4): 2185
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33 Lessons learned from Ontario wind energy disputes
Stewart Fast, Warren Mabee, Jamie Baxter, Tanya Christidis, Liz Driver, Stephen Hill, J. J. McMurtry, Melody Tomkow
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34 Personal and situational variables associated with wind turbine noise annoyance
David S. Michaud, Stephen E. Keith, Katya Feder, Sonia A. Voicescu, Leonora Marro, John Than, Mireille Guay, Tara Bower, Allison Denning, Eric Lavigne, Chantal Whelan, Sabine A. Janssen, Tony Leroux, Frits van den Berg
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35 Exposure to wind turbine noise: Perceptual responses and reported health effects
David S. Michaud, Katya Feder, Stephen E. Keith, Sonia A. Voicescu, Leonora Marro, John Than, Mireille Guay, Allison Denning, D'Arcy McGuire, Tara Bower, Eric Lavigne, Brian J. Murray, Shelly K. Weiss, Frits van den Berg
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36 Wind Turbines: A Different Breed of Noise?
Nate Seltenrich
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37 The Link between Health Complaints and Wind Turbines: Support for the Nocebo Expectations Hypothesis
Fiona Crichton,Simon Chapman,Tim Cundy,Keith J. Petrie
Frontiers in Public Health. 2014; 2
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38 Wind Turbines and Health
Robert J. McCunney,Kenneth A. Mundt,W. David Colby,Robert Dobie,Kenneth Kaliski,Mark Blais
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39 Developing a GIS-Based Visual-Acoustic 3D Simulation for Wind Farm Assessment
Madeleine Manyoky,Ulrike Wissen Hayek,Kurt Heutschi,Reto Pieren,Adrienne Grêt-Regamey
ISPRS International Journal of Geo-Information. 2014; 3(1): 29
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40 Social responses to wind energy development in Ontario: The influence of health risk perceptions and associated concerns
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41 Implications of Wind Power Generation: Exposure to Wind Turbine Noise
Pedro M. Arezes,C.A. Bernardo,Estefania Ribeiro,Hernâni Dias
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42 Creating and testing a survey to assess the impact of renewable energy technologies on quality of life
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44 Mass Transit Ridership and Self-Reported Hearing Health in an Urban Population
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45 Do Quiet Areas Afford Greater Health-Related Quality of Life than Noisy Areas?
Daniel Shepherd,David Welch,Kim Dirks,David McBride
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46 Mapping Ontario’s Wind Turbines: Challenges and Limitations
Tanya Christidis,Jane Law
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47 Sustainable development and wind farms [Zrównoważony rozwój a fermy wiatrowe]
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Problemy Ekorozwoju. 2013; 8(2): 113-122
48 Adverse health effects of industrial wind turbines [Effets indésirables sur la santé des éoliennes industrielles]
Jeffery, R.D. and Krogh, C. and Horner, B.
Canadian Family Physician. 2013; 59(5): 473-475+e218
49 Mass transit ridership and self-reported hearing health in an urban population
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Journal of Urban Health. 2013; 90(2): 262-275
50 Do quiet areas afford greater health-related quality of life than noisy areas?
Shepherd, D. and Welch, D. and Dirks, K.N. and McBride, D.
International Journal of Environmental Research and Public Health. 2013; 10(4): 1284-1303
51 Energy and human health
Smith, K.R. and Frumkin, H. and Balakrishnan, K. and Butler, C.D. and Chafe, Z.A. and Fairlie, I. and Kinney, P. and Kjellstrom, T. and Mauzerall, D.L. and McKone, T.E. and McMichael, A.J. and Schneider, M.
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52 A review of wind turbine noise perception, annoyance and low frequency emission
Doolan, C.
Wind Engineering. 2013; 37(1): 97-104
53 A Review of Wind Turbine Noise Perception, Annoyance and Low Frequency Emission
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54 Energy and Human Health
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55 Effects of industrial wind turbine noise on sleep and health
Nissenbaum, M.A. and Aramini, J.J. and Hanning, C.D.
Noise and Health. 2012; 14(60): 237-243
56 Wind turbine noise
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BMJ (Online). 2012; 344(7853)
57 Wind farms and health: Who is fomenting community anxieties?
Shepherd, D.
Medical Journal of Australia. 2012; 196(2): 108