Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A Review of the Potential Impacts of Wind Turbine Noise in the Australian Context

A Review of the Potential Impacts of Wind Turbine Noise in the Australian Context This manuscript describes a range of technical deliberations undertaken by the authors during their work as members of the Australian Government’s Independent Scientific Committee on Wind Turbines. Central to these deliberations was the requirement upon the committee to improve understanding and monitoring of the potential impacts of sound from wind turbines (including low frequency and infrasound) on health and the environment. The paper examines existing wind tur- bine sound limits, possible perceptual and physiological effects of wind turbine noise, aspects of the effects of wind turbine sound on sleep health and quality of life, low-frequency noise limits, the concept of annoyance including alternative causes of it and the potential for it to be affected by low-frequency noise, the influence of amplitude modulation and tonality, sound measurement and analysis and management strategies. In so doing it provides an objective basis for harmonisation across Australia of provisions for siting and monitoring of wind turbines, which currently vary from state to state, contributing to contention and potential inequities between Australians, depending on their place of residence. Keywords Wind turbines · Wind farms · Noise · Annoyance · Health · Sleep 1 Introduction While renewable energy from wind turbines can have a posi- tive environmental impact, wind turbines can also be visu- ally imposing and are a source of audible sound and infra- sound. If turbines are placed near to where people live, the * John Laurence Davy johnldavy@gmail.com wind turbine sound can potentially be loud enough to be a source of disturbance, potentially adversely affecting wake- Kym Burgemeister kym.burg@arup.com ful activities and/or sleep with resulting irritability, nega- tivity and cognitive disturbance. It is held by some people David Hillman hillo@it.net.au that the audible sound and infrasound may also have more specific effects on health and well-being, including potential Simon Carlile carlile.simon@gmail.com effects on non-auditory function of the inner ear [1 ]. Further- more, the visual impact of wind turbines may cause individ- Royal Melbourne Institute of Technology (RMIT) ual concern, both in terms of their appearance and, in some University, GPO Box 2476, Melbourne, VIC 3001, Australia cases, shadow flicker. Added to these concerns, individuals Infrastructure Technologies, CSIRO, Private Bag 10, may develop negative perceptions regarding a perceived lack Clayton South, VIC 3169, Australia of fairness in planning decisions regarding siting of turbines Arup, Sky Park, One Melbourne Quarter, 699 Collins Street, in proximity to their dwellings. These negative reactions to Docklands, VIC 3008, Australia wind turbine presence have been encapsulated in concept of Centre for Sleep Science, University of Western Australia, ‘annoyance’ [2]. Thus, there is a logical basis for now deriv- Crawley, WA 6009, Australia ing a wind turbine sound limit based on limiting annoyance. Faculty of Medicine, University of Sydney, Camperdown, In order to manage potential impacts from wind turbine Australia sound, governments and regulators have established wind [X] The Moonshot Factory, Mountain View, CA 94043, USA Vol.:(0123456789) 1 3 182 Acoustics Australia (2020) 48:181–197 turbine sound limits that place an upper limit on the sound being a good practical value [4]. These values are similar to level that wind farms can generate and effectively place a the lower maximum design limits already adopted, or pro- limit on how close wind turbines can be placed to dwellings posed for use in Australia of 35, 37 and 40 dB L . Aeq (10 min) and population centres. There is some disparity in approach Thus, this study provides a method for harmonisation of to this issue and this manuscript describes deliberations by future wind farm sound limits in Australia based on direct the Australian Government’s Independent Scientific Com- assessments of human response to wind farm sound. It mittee on Wind Turbines (‘the committee’) aimed at opti- should be noted that all sound pressure levels in this paper mising the approach to determining their minimum distance are A-weighted and given as dB(A) unless otherwise stated. from noise-sensitive receivers and their management. It The World Health Organisation (WHO) [5] released examines aspects of the effects on sleep health and qual- Environmental Noise Guidelines for the European Region ity of life, low-frequency noise limits, alternative causes of in 2018. This publication conditionally recommends reduc- annoyance, annoyance attributed to low-frequency noise, ing outdoor noise levels produced by wind turbines to which management strategies, amplitude modulation, measure- people are exposed to below an L of 45 dB(A). This is den ment of wind farm tonality, wind farm sound measurement based on four studies which show that 10% of the population and analysis, and the statistical power of wind turbine noise were highly annoyed with wind turbines when exposed to studies. outdoor wind turbine noise levels of L equals 45 dB(A). den The purpose of publishing these deliberations is, by mak- Like the National Health and Medical Research Council ing them available to technical experts for their considera- (NHMRC) [6], WHO rated the evidence used to determine tion and feedback, to facilitate and promote harmonisation this wind turbine noise limit as being of low quality and across Australian states of the provisions for siting and that is the reason why the recommendation is conditional. monitoring of wind turbines. This manuscript sits along- An L of 45 dB(A) is equivalent to an L of 38.6 dB(A). den Aeq side reports from the committee of a less technical nature, This conversion assumes that the distribution of wind tur- including its reports to parliament and fact sheets it intends bine sound levels is the same during the day, evening and to make available on its website. night [7]. This is close to the wind turbine noise limit of L Aeq of 37 dB(A) determined by the committee [3] using the same requirement of keeping the percentage of the exposed popu- 2 Wind Turbine Sound Limits lation who are highly annoyed with wind turbines to less than 10%. In fact, reading the L to the nearest 0.1 dB from den Committee members recently undertook a detailed review both the mean average European curve and the Japanese of the existing wind turbine sound limits in Australian states curve in the Fig. 16 of the WHO report [5] at which 10% of and several other countries with similar constraints, how people are highly annoyed with wind turbines gives 43.7 dB these were established and a method that could facilitate L which is equal to 37.3 dB L . It appears that the WHO den Aeq their harmonisation [3]. It was found that most existing wind sound level limit was rounded to the nearest 5 dB. The WHO farm sound limits appear to have been adopted to avoid sleep analysis did not include the 2016 results of Michaud et al. disturbance but were developed using data derived from [8–11]. If the committee’s sound level limit [3] is deter- sound sources other than wind turbines. This seems to have mined to the nearest 0.1 dB, rather than the nearest 1 dB, been a reasonable approach at the time of their adoption the limit is 35.3 dB L , which is equal to 37.3 dB A90(10min) because of the paucity of other suitable data. More recently, L , and is equal to the WHO value to the nearest 0.1 dB. Aeq the concept of ‘annoyance’ has been used to encapsulate Note however that the uncertainty limits are large. The WHO negative reactions to wind turbine sound. Given that many report found six studies which it rated as low quality, and studies have now demonstrated a significant relationship which did not reveal consistent results about effects of wind between annoyance and wind turbine sound level, regardless turbine noise on sleep disturbance. The WHO report found of whether sound was the major source of the annoyance, no studies on the effects of wind turbine noise on the preva- there is a logical basis for now deriving a wind turbine sound lence of ischaemic heart disease, hypertension, permanent limit based on annoyance. hearing impairment, and reading skills and oral comprehen- The committee’s analysis suggests that an appropriate sion in children. noise limit to ensure that no more than 10% of the popula- The committee recommends that state and territory gov- tion are ‘highly annoyed’ when exposed to wind farm noise ernments consider harmonising their wind turbine sound is between 34 and 40 dB L outside the residence, limits by adopting the limits proposed in their paper [3]. It Aeq (10 min) with a mean value of 37 dB L [3]. The cut-off of would also like to see more uniformity in sound measure- Aeq (10 min) 10% is somewhat arbitrary and itself could be a subject of ment and compliance requirements. Although the committee informed debate. The corresponding measurement limits in believes that wind turbine sound level should be the primary L are between 1.5 and 2.5 dB lower with 2 dB lower determinant of how close residences can be to wind turbines, A90(10 min) 1 3 Acoustics Australia (2020) 48:181–197 183 there should also be a minimum setback distance. This mini- or not of wind turbine noise (WTN), they do demonstrate mum distance may be varied under particular circumstances, that such sounds are encoded by the human nervous system. such as when the residences are exposed to the same high The committee concluded, consistent with other stud- winds as the wind turbines themselves. This produces high ies by the NHMRC, that the quality of data relating to the background noise levels at the residences and allows the potential health effects of WTN was not good. The review residences to be exposed to a higher level of wind turbine identifies a range of research questions that would be appro- noise and hence to be effectively closer to the wind turbines priate for further detailed study in order to address the many than would normally be the case. With current wind turbine outstanding scientific questions. In brief, these included: technology, this minimum distance should be in the range between the 1 km adopted by the Victorian Government and 1. Characterization and modelling of the sound generated the 1.5 km recommended by the National Health and Medi- by modern windfarms focusing on the blade-passing cal Research Council and adopted by the Queensland Gov- frequency (BPF) and higher harmonics along with the ernment. These minimum distances may need to be revised effects of terrain and atmospheric conditions, etc.; in the future due to technology changes. 2. The development of a more complete understanding of the interactions between WTN and the built structures in which people live and sleep; 3 Possible Perceptual and Physiological 3. New methods need to be developed for measuring acute Eec ff ts of Wind Turbine Infrasound and chronic exposure (dosimetry); and Low‑Frequency Noise 4. Structural and aeronautic engineering research to mini- mize the sound pressure level at the BPF; In a further publication, the committee [12] recognised 5. Effects of IS/LF on the cochlea and vestibular apparatus; and responded to the need to review the scientific litera - 6. A better understanding of the neural connectivity of the ture relating to possible perceptual and physiological effects inner ear and an understanding of the neural and behav- of infrasound and low-frequency sound (IS/LF). Previous ioural consequences of their possible activation by IS/ reviews [13–21] have mostly relied on an epidemiological LF; approach providing meta-analysis of the existing population- 7. Studies of individuals who report susceptibility to WTN based research. As outlined in Appendix, the sensitivity of for dysfunction or pathology that mediates susceptibil- this approach appears quite low. By contrast, the committee ity (e.g. superior semicircular canal dehiscence or lym- focussed on physiological mechanisms at the level of the phatic hydrops). individual to determine if there was evidence of an effect of IS/LF sound energy on the organism. The committee believes that further scientific research is Studies of the generation and propagation of IS/LF sound needed to discover why some people complain about being by wind turbines demonstrate that the acoustical energy per badly ae ff cted by wind turbine noise. It recommends that the unit frequency at the blade-passing frequency (BPF) and at NHMRC and ARC consider the research agenda outlined its harmonic frequencies below 10–15 Hz is greater than above for increased priority funding as one means to address at higher frequencies. Propagation models and field studies this potentially important public health and policy, energy have indicated that sound at these IS/LF frequencies can security and scientific issue. propagate with less attenuation with distance than higher frequencies because of their lower sound absorption during passage through the air and on reflection from the ground 4 Eec ff ts on Sleep Health and Quality of Life [12, 22–28]. Added to this is uncertainty regarding the effec- tiveness of sound insulation of houses at infrasound and low Most of the wind turbine noise limits that were described frequencies [29]. Given these uncertainties, there was a pau- in the committee’s earlier manuscript [3] were set to city of data relating to the potential exposure of individuals avoid sleep disturbance using generic noise studies and in the vicinity of wind turbines, particularly within dwellings the sound insulation provided by partially open windows. where they work and sleep. Thus, it makes sense to look at what evidence there is for Reviews of physiological transduction and neural excita- a relationship between wind turbine noise levels and sleep tion provided a strong prima facia case for the transduction disturbance. of IS/LF [12, 30, 31] and stimulation of the human nervous The NHMRC [6] stated that there is inconsistent, poor system consistent with studies demonstrating perceptual sen- quality direct evidence of an association between sleep dis- sitivity to high levels of IS/LF sounds and to neural (cortical) turbance and wind farm noise. They observed that sleep dis- activation at more moderate sound levels [12, 32–34]. While turbance was not objectively measured in the studies and that these data do not by themselves, speak to the health effects a range of other factors could explain the associations that 1 3 184 Acoustics Australia (2020) 48:181–197 were observed. Michaud et al. [11] used both self-reported This statement was re-enforced by the Health Canada study and objective measures of sleep quality. They concluded that [10]. However, it should be noted that the NHMRC [6] also there was no association between the exposure to outdoor stated that the evidence is of poor quality. Because of the con- wind turbine noise of up to 46 dB(A) and sleep disturbance. cern expressed by some people, they recommended further Micic et al. [35] have pointed out the limitations of this high-quality research into the possible health effects of wind study and the other studies discussed in this section. It the farms. To be clear, in a situation where data quality is poor, it case of the Michaud et al. study, these limitations included is not possible to draw a secure positive or negative conclusion the use of actigraphy for the objective measure of sleep and with respect to the question of the association between wind the use of calculated sound levels which ignored special turbine noise and health effects. audible characteristics. For instance, according to Feder et al. [43], there have van den Berg [36] stated that Janssen et al. [37] had ana- been a few studies on the relationship between quality of lysed the sleep disturbance data from two Swedish and one life and wind turbine noise level and the findings are incon- Dutch study whose annoyance data were used in the com- sistent. One group [44, 45] showed that quality of life mittee’s paper [3]. Janssen et al. only found a statistically improved with closer proximity to a wind farm, suggesting significant relationship between sleep disturbance and wind other factors apart from sound levels, influence this. On the turbine noise level when they excluded persons who received other hand, Shepherd et al. [46] found that the quality of economic benefit from the wind turbines [36, 37]. When all life decreased when the wind farm noise level increased. residents were included, there was no statistically significant Onakpoya et al. [19] cites this and several other studies to relationship. However, there may be a small percentage of support the relationship, but they noted some that did not the population with individual sensitivities which would not and they were unable to conduct a meta-analysis because be discovered by a study of this size. It should be noted that of inconsistency in the quality of life measures used across the sleep disturbance was not necessarily from wind turbine these studies. Given the absence of consistent data regarding noise. the effects of wind turbine noise on quality of life data, it Bakker et al. [38] further analysed the data on residents appears that quality of life measures alone cannot currently from the Dutch study who received no economic benefit. be recommended to set wind turbine noise limits. They found no statistically significant relationship between Most of these studies used very small numbers of partici- sleep disturbance and wind turbine noise level. There was a pants, which deprives the analyses of an appropriate level statistically significant relationship between annoyance and of statistical power to detect small influences in the larger sleep disturbance. In the quieter rural areas, there was also a population (see “Appendix”). These studies do not provide statistically significant relationship between annoyance and consistent evidence regarding the influence of wind turbine wind turbine noise level. noise on sleep health and quality of life or distinguish these Pedersen [39] re-analysed the data from the two Swedish influences from others in helping determine reasonable wind and one Dutch study. Pedersen found that there was a statis- turbine noise limits. This lack of consistency suggests that tically significant relationship between wind turbine noise some effects may only be experienced by a small propor - levels and sleep disturbance for the first Swedish study [40] tion of the population making their detection problematic and the Dutch study [41]. The second Swedish study [42] where studies with low participant numbers are used to highlights other factors, in addition to sound levels that influ- detect them. ence perception of and annoyance with wind turbine noise The committee supports the conclusions of the National including individual characteristics, such as noise sensitivity Health and Medical Research Council that there is currently and attitude to the source, and the influence of dissimilar no consistent evidence regarding the effects of wind farms environments, including the influence of terrain. Hence it on human health and their call for high quality research appears too simplistic to use analysis of sleep disturbance into the matter, particularly where close proximity (within in terms of wind turbine noise levels alone to set limits for 1500 m) is involved [6]. The committee notes that the wind wind turbine noise, as other factors are also involved. turbine industry is a very large and growing industry world- van den Berg [36] has concluded that audible noise from wide and such an investment could provide significant wind turbines may cause annoyance which aggravates sleep advantage to Australian industry. problems. Hence wind turbine noise limits which prevent annoyance may also prevent sleep disturbance. Thus, an alternative approach may be to set wind turbine noise lim- 5 Low‑Frequency Noise Limits its using the percentage of people who are highly annoyed given the current state of knowledge. Because of the concern that has been expressed about The NHMRC [6] concluded that there is no consistent evi- the possible effects of low-frequency noise from wind dence that wind farms cause adverse health effects in humans. turbines, it is appropriate to review existing or proposed 1 3 Acoustics Australia (2020) 48:181–197 185 low-frequency noise limits from around the world. Table 1 criteria [55]. L is the A-weight noise in the 10 to 160 Hz A, LF shows reference curves which have been used or suggested third octave bands. The Danish evening and night time third to be used for the control of generic low-frequency noise. octave band sound levels must be sufficiently below the Table 1 is taken from Leventhall et al. [47] and the reference 20 dB(A) contour values shown in Table 1, so that the com- curve recommended to DEFRA in the UK by Moorhouse bination of these third octave band values does not exceed et al. [48] has been added to the table. The ISO 226 values 20 dB(A). The value of the 20 dB(A) contour for each third are the threshold of human hearing sound levels taken from octave band is the sound pressure level in that third octave a version of ISO 226 [49] which is no longer current. Except band which on its own has a sound level of 20 dB(A). The for the Polish and Danish night values which are based on infrasound criterion is not greater than 85 or 90 dB(G) [55], A-weighted values, the values are similar to the human which wind turbine noise is well known to easily satisfy. threshold values at 50 Hz and below. This means that the A 5 dB penalty is added to the measured values for impul- creators of these limits considered that low-frequency noise sive noise such as single blows from a press or drop forge close to the hearing threshold could be annoying. Zajamšek hammer. et al. [26] have shown that indoor third octave band sound The Polish requirement is that noise is considered to be pressure levels of wind turbine noise below 50 Hz are signif- annoying if any third octave band level is greater than the icantly below the human hearing threshold. This leads some 10 dB(A) contour shown in Table 1 and greater than 10 dB researchers to believe that wind turbine noise below 50 Hz is for tonal noise or 6 dB for broadband noise above the third not a problem [50–53]. However, as noted in the committee’s octave band background noise level. This is the reason why previously published analysis [12], not all researchers agree the Polish curve is 10 dB lower than the Danish curve. The that this is the case [25, 30, 31, 54]. value of the 10 dB(A) contour for each third octave band is It should be noted that these criterion curves are applied the sound pressure level in that third octave band which on in different ways. Table  2 shows the Danish indoor noise its own has a sound level of 10 dB(A). Table 1 Low-frequency noise criterion curves Frequency Hz Poland Germany Netherlands Denmark Night Sweden UK ISO 226 10 dB(A) contour DIN 45680 dB NSG dB 20 dB(A) contour dB DEFRA dB dB 8 103 10 80.4 95 90.4 92 12.5 83.4 87 93.4 87 16 66.7 79 76.7 87 20 60.5 71 74 70.5 74 74.3 25 54.7 63 64 64.7 64 65 31.5 49.3 55.5 55 59.4 56 56 56.3 40 44.6 48 46 54.6 49 49 48.4 50 40.2 40.5 39 50.2 43 43 41.7 63 36.2 33.5 33 46.2 41.5 42 35.5 80 32.5 28 27 42.5 40 40 29.8 100 29.1 23.5 22 39.1 38 38 25.1 125 26.1 36.1 36 36 20.7 160 23.4 33.4 34 34 16.8 200 20.9 32 13.8 250 18.6 11.2 Table 2 Danish generic noise Infrasound L Low-frequency Normal noise limit L (dB) G A criteria (dB) noise (dB) Dwelling, evening and night 85 20 30 dB/25 dB Dwelling, day 85 25 30 dB-day and evening Classroom, office etc. 85 30 40 dB Other rooms in enterprises 90 35 50 dB 1 3 186 Acoustics Australia (2020) 48:181–197 According to Leventhall [47], in the application of the presence of people within a space. The levels of low fre- Swedish method, the noise may be considered a nuisance quency noise at the two wind farm locations, which were if its level exceeds the criterion curve in any third octave approximately 1.5 kilometres away from the nearest wind band. In the Dutch method, the LF sound is considered audi- turbine, were low in comparison with the urban areas and ble and potentially annoying if the equivalent third octave were not noticeably higher than at the other two rural sound pressure level is above the reference curve at one or locations. It should be noted that although this study did more frequencies [56]. The DEFRA method [48] requires give the time of day and the wind speed when the meas- any third octave band L which exceeds the criterion curve urements were made, it did not give the power output or eq to be investigated. The criterion curve is relaxed by 5 dB if other meteorological data. The low frequency levels at one the noise occurs only during the day or if the noise is not location remained below the Danish and DEFRA criteria fluctuating. at all times. The outdoor levels remained below 60 dB(C) Leventhall [47] has described the German DIN 45680 during the night-time periods. The Danish 20 dB(A) night- method. The difference (dB(C) − dB(A)) > 20 dB is used time criterion was exceeded for 10% of the measurement as an initial indication of the presence of low-frequency time at another location. This was believed to be due to noise. The noise is then measured in third octaves over the construction of the house rather than the contribution specified time periods and compared with the threshold of noise from Clements Gap Wind Farm. There were very curve in Table 1. The main frequency range is from 10 Hz occasional exceedances of the night-time DEFRA crite- to 80 Hz. Frequencies of 8 Hz and 100 Hz are used only if ria at this site, but the percentage of exceedances was no the noise has many components within the range 10 Hz to greater than at two other locations with no wind turbines 80 Hz. DIN 45680 assumes that the great majority of low- within 10 kilometres. Hansen et al. [64] measured wind frequency noise problems from industrial sources are tonal farm noise in the 50 Hz third octave which was well above and that thus the 8 Hz and 100 Hz third octave bands will the DEFRA limit. only rarely be used. If the level in a third octave band is 5 dB Organised shutdowns showed that the contribution of the or more above the level in the two neighbouring bands, the Bluff Wind Farm to low frequency noise levels at one loca- noise is described as tonal. For tonal noises, the level of the tion was negligible. There may have been a relatively small tone above the hearing threshold is found. All the limits are contribution of low frequency noise levels at this location reduced by 5 dB during night-time. from the Clements Gap Wind Farm at frequencies of 100 Hz Other possible low-frequency noise requirements are and above. However, Hansen et al. [65] did find a substantial upper outdoor limits of L equals 65 dB(C) during the day reduction in the low frequency noise levels during a shut- Ceq and 60 dB(C) during the night [57, 58]. As stated above, down of the Waterloo Wind Farm relative to levels during the difference (dB(C) − dB(A)) > 20 dB is also sometimes operation. used as an initial indication of the presence of low-frequency It is worth noting that the frequency ranges considered noise. Broner and Leventhall [59] have proposed the use of by all the standards discussed above do not extend to the Low-Frequency Noise Rating (LFNR) curves. Inukai et al. blade-passing frequencies and the early harmonics (approxi- [60] developed a new weighting curve for low-frequency mately 0.5–8.0 Hz) which represent the largest components noise. Vercammen [61, 62] developed low-frequency noise of IS and LF energy emitted by wind turbines. As discussed limits which appear to be the forerunner of the Danish limits. under ‘Possible perceptual and physiological effects of In urban environments, Evans et  al. [63] found that wind turbine noise’ above, there is a prima facia case for A-weighted low-frequency noise levels at all locations regu- the somatic and/or neural transduction of these frequencies, larly exceed the night time residential criteria of 20 dB(A) and Zajamšek et al. [26] found that wind turbine noise did used in Denmark (between 16 and 86% of the time). These increase the infrasonic and low frequency noise during quiet excluded periods affected by people’s daily activities. The night time periods. DEFRA night-time low frequency noise criteria were also The committee is unable to recommend low frequency regularly exceeded at the urban locations. sound or infrasound limits for wind farms in the absence In rural environments Evans et al. [63] found a lower of definite evidence of the health effects of low frequency level of low frequency noise in the environment at the four sound or infrasound from wind turbines. There would also rural locations relative to the seven urban locations. The need to be a reliable method of measuring low frequency measured night-time L levels at four rural locations noise and infrasound before a limit could be imposed. One A,LF exceeded the 20 dB(A) Danish criterion for only 10% of possible method is described in ANSI/ASA S12.9-2016/ the time or less. This 20 dB(A) criterion was not exceeded Part 7 [66]. The committee recommends that research on at one of the rural locations. The levels of low frequency the possible impact of low frequency sound and infrasound noise were correlated to wind speed at the measurement on humans from industrial sources including wind turbines site. At some locations, they were also affected by the is continued. 1 3 Acoustics Australia (2020) 48:181–197 187 Michaud et al. [8] further observed that personal ben- 6 Alternative Causes of Annoyance efit was not retained in their unrestricted modelling of the relationship between wind turbine noise and annoyance, It has been demonstrated experimentally that people suffer although this was probably due to the small number of par- more health problems if they are led to believe that wind ticipants in this category. Personal benefit was found to be turbines are harmful (nocebo effect) [67– 69]. This is an statistically significant in their restricted model, although example of the well-known psychological bias referred the associated increase in R with addition of this variable to as the ‘demand characteristic’ in perceptual and social was only 3%. Together with Pedersen et al. [41], these find- psychological research. ings support the distribution of direct or indirect personal Michaud et al. [8] examined the statistically significant benefits to participants living in close proximity to wind variables related to annoyance with wind turbines using a power projects. multiple logistic regression model. The importance of each The finding that wind turbine noise level alone is not a variable was ranked using the Nagelkerke pseudo R . The particularly strong predictor of annoyance with wind tur- closer the Nagelkerke pseudo R is to 100%, the better the bines suggests that other actions should be undertaken in multiple logistic regression model equation predicts the conjunction with the setting of wind turbine noise limits in observed probability of occurrence. Wind turbine noise order to reduce annoyance. Furthermore, it needs to be rec- level had an R equal to 9%. This increased to 11% when ognized that even small effects can be important as they may the location in Canada was added to form the base model. reflect the influence of a limited number of individuals with Addition of further variables including those related to particular sensitivities that need to be accounted for [47]. other wind turbine annoyance, personal benefit, noise The committee recommends that wind farm develop- sensitivity, physical safety concerns, property ownership ers educate, consult with and provide some resources to and the location within Canada of the operation lifted the the local community in order to identify and minimise the R value to 58% (meaning that 58% of the variance in diverse potential sources of annoyance with wind farms. the relationship of annoyance to wind turbines could be explained by them). This suggests that wind turbine noise alone is not a powerful predictor of annoyance, and that 7 Annoyance Attributed to Low Frequency many other factors contribute to the problem. Noise In further analysis Michaud et al. [8] noted that while they failed to find a relationship between wind turbine In various settings around the world, a small percentage of noise levels and sleep disturbance, the strongest associa- people report being annoyed by what they perceive as per- tion with annoyance was identifying wind turbines as the sistent low frequency noise, usually from an unknown or source of noise that led to window closing because it was undiscovered source as obvious sources have been elimi- disturbing sleep. They suggested that closing the window nated. This phenomenon is often referred to as ‘The Hum’. may be an expression of the annoyance towards WTN and/ It is helpful to examine reports of ‘The Hum’ because its or a coping strategy that protects against sleep disturbance. reported symptoms are similar to some of the symptoms Given that closing the window reduces the indoor WTN reported by some people living near wind turbines [47, level and hence improves sleep, this action may conceiv- 70–73]. The Hum is perceived as a low frequency noise ably explain the absent association between WTN levels which is often described as a throbbing noise. It is proba- and sleep disturbance. bly, but not necessarily, caused by low frequency noise from Michaud et al. [8] also noted that concern for physical industrial or other anthropogenic noise sources. There have safety due to the presence of wind turbines was a significant been several attempts to find the cause of the Hum recorded predictor of annoyance in both the unrestricted and restricted in the literature [70, 72, 73]. However, Leventhall (2004) models suggesting that actions (such as education and com- notes that ‘No widespread Hum has been unequivocally munity consultation) which address this concern during the traced to specific sources, although suspicion has pointed at planning stages of a wind project may reduce community industrial complexes, especially fans’. Even when low fre- annoyance toward wind turbine noise. Noise sensitivity quency sound sources have been found and quietened, this influences the response to community noise. Thus, it is not has not usually solved the problem completely [71]. surprising that noise sensitivity was associated with wind The ee ff cts of the Hum are reported as pressure or pain in turbine noise annoyance [8]. Crichton et al. [67] have con- the ear or head, body vibration or pain, loss of concentration, firmed this observation by showing that giving people posi- nausea and sleep disturbance. [47]. These general effects are tive expectations about exposure to wind turbine noise can reported internationally. statistically significantly reduce their health symptoms. This Unsympathetic handling of the complaint builds up stress is another example of the ‘demand characteristic’. and exacerbates the problems. Hum sufferers tend to be 1 3 188 Acoustics Australia (2020) 48:181–197 middle aged and elderly. They often have a low tolerance Some wind turbine noise policies in Australia and overseas level and are prone to negative reactions [47]. Personal ten- include penalties for sound from wind farms that has ‘special sions are reduced if the complaints are taken seriously by the audible characteristics’ (known as SACs) that are likely to authorities because this eases the additional stresses which make it significantly more noticeable and annoying to sensi- occur when they are not believed [47]. tive receivers. One of the key ‘special audible characteris- Leventhall et al. [47] summarised Vasudevan and Gor- tics’ of wind farm sound is the amplitude modulation (AM) don’s [73] experience from investigating the Hum as of the sound over time as the turbine blades are turning, follows:. which results in a rise and fall in wind farm loudness. This is usually characterised as a ‘whoosh–whoosh–whoosh’ sound The problems arose in quiet rural or suburban environ- modulated at the blade-passing frequency (usually around ments. 1–2 Hz). This sound is usually evident, to some extent, in The noise was often close to inaudibility and heard by a all wind turbine sound due to the nature of the noise genera- minority of people. tion mechanism at the turbine blade. However, the extent (or The noise was typically audible indoors and not outdoors. level) of modulation, known as the modulation depth, can The noise was more audible at night than during the day. vary significantly depending on the environmental condi - The noise had a throbbing and rumbly characteristic. tions, and some objective measure of the extent of amplitude The main complaints came from the 55–70 years age modulation, and its acceptability, is required. Some simple group. objective measures for AM were documented in the early The complainants had normal hearing. wind farm sound policies and standards, but there is gener- Medical examination excluded tinnitus. ally a concern that these were not rigorously developed, and their relationship to the extent of annoyance has never been These are now recognised as classic ‘hum’ descriptors. adequately demonstrated. It is often the case that only one person in a family is Lee et  al. [74] have studied the annoyance caused by sensitive to the Hum [47]. If the Hum is caused by sound, amplitude modulated wind turbine noise using 30 people. the fact that it is only ‘heard’ by a small minority of people They showed that the A-weighted equivalent sound level suggests that these people have more sensitive hearing than and the modulation depth both had a statistically significant the rest of the population. It has been suggested that the effect on the annoyance. However, the annoyance differences percentage of people in the effected age group who might between different modulation depths were only statistically be able to hear the Hum is 10% [56], 2.5% [71] or 0.5% [47]. significant when the difference in modulation depths was Leventhall et al. [47] assumed that the people most likely large. von Hünerbein et al. [75] showed that after remov- to suffer from the Hum were in the 50–59 age group who ing the effect of the A-weighted equivalent sound level, the comprise about 10% of the population. This meant that the annoyance increased monotonically with the modulation percentage of the total population likely to suffer from the depth, but this increase was not statistically significant due Hum is estimated to be 1%, 0.25% or 0.05%. While these to the small sample size of 20 people. Bockstael et al. [76] estimates are obviously very imprecise, they suggest that found a statistically significant link between annoyance and if ‘The Hum’ is responsible for any wind turbine health their measure of amplitude modulation. Ioannidou et al. [77] effects, population-wide epidemiology studies may not be found a statistically significant relationship between annoy - sufficiently sensitive to detect them. Rather, approaches that ance and the amplitude modulation depth of wind turbine identify outliers, clusters or more sophisticated forms of fre- noise. Yokoyama et al. [78] showed that amplitude modu- quentist statistics will need to be employed, as they are more lation of wind turbine noise became noticeable when the appropriate to identifying and describing low prevalence modulation depth exceeded 2 dB. events and low disease rates. Relevant to this, there are two The Institute of Acoustics (IoA) in the UK [79] has con- current NHMRC funded projects examining wind turbine ducted an extensive study into the best way to objectively noise effects on sleep which intend to increase the capacity measure amplitude modulation of wind turbine noise. The to identify possible underlying dysfunctions or sensitivities IoA looked at time-series methods, frequency-domain meth- by selecting noise-sensitive people. ods, and hybrid methods. They have recently recommended the use of a relatively complex hybrid method. This is quite a complicated procedure which could possibly result in imple- 8 Amplitude Modulation mentation differences between users. Therefore, the IoA has issued open-source Python software which carries out this Psychoacoustic studies have generally shown that sound with procedure in an accepted and consistent manner. varying temporal or frequency characteristics is more notice- Large [80] has compared the three initial amplitude able and more annoying than constant ‘steady-state’ noise. modulation rating methods proposed by the IoA with the 1 3 Acoustics Australia (2020) 48:181–197 189 annoyance ratings of 6 samples of wind turbine amplitude when rating sound signals because they are usually found modulation (AM) made by 336 people. She noted that the to be more subjectively disturbing than broadband sound AM rating methods ‘generally followed the shape of the at the same level. Usually, the approach is to add a positive annoyance ratings’ but that the range of the AM ratings penalty to the measured sound level, rather than reduce the was much greater than the range of the annoyance ratings. limit for sound containing tones. For wind farm noise, it is Hence some caution is needed, but the current IoA ampli- necessary to determine both the best scheme or approach tude modulation rating method is the best candidate for trial to measure tonality and where it should be measured. in Australia. It should be noted that none of the AM rating In terms of the measurement location, it is possible systems so far proposed include the possible effect of basilar to measure tonality near the turbines themselves, at the membrane biasing by the blade-passing tone and its harmon- receiver, or somewhere in between. Clearly, it is particu- ics [12]. Hansen et al. [81] have shown that the IoA method larly relevant at the receiver, and a measurement near to may need to be modie fi d in some circumstances, particularly the turbine is less critical because a sound source that is when the amplitude modulation is of a tone below 50 Hz. tonal near to the source, will not necessarily result in tonal The IoA have deliberately avoided specifying how their noise at the more distant receiver, where the sound is com- rating scheme should be used for rating the noise output bined with the ambient sound local to the receiver, which of wind turbines. Perkins et al. [82–84] have proposed that can significantly mask the tonal elements. Nevertheless, there be no penalty for an amplitude modulation rating the presence of tonality in the source signal is easier to which is less than 3 dB. For amplitude modulation ratings measure near the source because of the better signal to between 3–10 dB, the penalty increases linearly from a 3 dB noise ratio. One approach that has been suggested is to penalty at 3 dB AM depth, to 5 dB penalty at 10 dB AM make a measurement near the turbines as an ‘exclusion depth. Above 10 dB AM, the penalty is fixed at 5 dB. This test’, since, if the sound near the turbines is not tonal, penalty is added to the measured L values and is in addi- then it is unlikely to be tonal at the receiver. More intru- A90 tion to any tonal penalty. Perkins et al. [82] have observed sive tests at the receiver would therefore not be warranted. that ‘AM generates the greatest adverse impact during night- However, if the wind turbine sound did prove to be tonal time or early morning periods’. Because ETSU-R-97 [4] rec- near the turbines, this could be used to suggest what tonal ommends a higher night time wind turbine noise level limit frequency should be searched for near the receiver (and, if for England, Perkins et al. [82] recommend that the same tonal frequencies are measured at the receiver, what tonal limit for AM for England be applied all the times by adding frequencies could be excluded from being generated by the difference between the night time limit and the day time the wind turbines). limit to the AM penalty. This implies that they believe that If measurements of tonality are made only at the receiver, the ETSU-R-97 higher night-time wind turbine noise level and not in conjunction with a measurement made near the limit does not make sense. There has recently been further turbine, then it can be difficult to discriminate tonality from debate about appropriate penalties for amplitude modula- the wind turbines from ambient noise such as Aeolian noise tion [85]. emissions from wire fences, etc. One approach is to limit The draft New South Wales planning guidelines [86] measurements to the downwind condition. Another possibil- impose a penalty of 5 dB when the amplitude modulation ity is to make measurements only at night when the ambi- depth is greater than 4 dB. However, their maximum penalty ent noise is likely to be quieter. A problem with making is 5 dB, so that where more than one special audible charac- downwind measurements of tonality, is that the tonality can teristic penalty potentially applies, only one of the penalties sometimes only be audible to the side and upwind of the is added to the measured sound level. turbine [87]. The committee recommends that the United Kingdom In terms of the best approach to measuring and assessing Institute of Acoustics objective measurement method of tonality, it is usually helpful to conduct a less complicated measuring amplitude modulation and the WSP Parsons subjective screening test prior to making objective measure- Brinckerhoff method of penalising amplitude modulation ments. This is usually undertaken by an acoustic engineer be trialled in Australia. or other qualified person simply listening for the potential of tonality in wind farm sound or site recordings. A poten- tial problem with this approach is that tonality sometimes 9 Tonality only occurs for a narrow range of wind speeds and only for certain directions from the wind turbine and at certain times Tonality is the difference between the tone level and the [87]. Thus, having the expert listener make a judgement at level of the masking noise in the critical band around the the right time may be difficult. Having the affected person tone. Tonal elements are particularly salient, and poten- make a recording when they hear tonality may overcome tially annoying. It is common to penalise tonal sounds this problem. 1 3 190 Acoustics Australia (2020) 48:181–197 If the potential for tonality is detected, then further objec- At the Te Rere Hau review, it was argued that if 10% of tive measurements of tonality can be made in accordance measurements within a 1 m/s wide wind speed bin were with Annex C of ISO 1996-2:2007 [88]. This method is tonal, then the penalty should be applied to the wind- based on the Joint Nordic Method—Version 2 [89]. It is a speed bin. This approach requires bin analysis [95, 96], tonal audibility method, based on narrowband analysis. It rather than polynomial regression. This approach was sug- requires considerable signal processing and results in the gested because it would not overly penalise very infrequent calculation of tonal audibility and an adjustment penalty occurrence of Special Acoustic Characteristics (SACs) but between 0 and 6 dB. would apply an appropriate penalty to ‘encourage miti- However, because this reference method is complicated, gation’ where SACs occur with reasonable regularity. A ISO 1996-2:2007 [88] also contains a simplified method in similar 10% threshold approach to applying the SACs pen- Annex D. If the time-averaged sound pressure level in a one- alty has been adopted in New South Wales and Queensland third octave band exceeds the time-averaged sound pressure in Australia, and in the United Kingdom. However, this levels in both the adjacent two one-third octave bands by a approach needs some refinement because it could result level difference, a penalty, which is usually 5 dB, is applied. in a discontinuity in the compliance assessment (that is, The suggested level differences are: a hard switch from compliant to non-compliant) near the 10% limit. 15 dB in the low-frequency one-third-octave bands (25– Nevertheless, there is concern that if only a small per- 125 Hz), centage of the measured 10-min sound levels are penalized 8 dB in middle-frequency bands (160–400 Hz), for tonality, the effect of these penalized sound levels on 5 dB in high-frequency bands (500–10,000 Hz). the regression curve between the sound levels and the wind speeds, which is required by the NZ Standard NZS6808 to This simplified method can fail to identify low frequency determine the sound level which is regulated, may not be audible tones because of the tone’s side bands if the tone is significant. However, NZS6808-2010 [93] allows the sound substantially amplitude modulated [90]. levels measured over each 10 min period to be separated (Note: These methods have been updated in Annex J of into a group of sound level measurements with acceptable ISO/PAS 20065:2016 [91] and Annex K in ISO1996-2:2017 tonality and a group of sound level measurements with unac- [92]. Also, there is an alternative tonality method in ETSU- ceptable tonality. These two different groups of sound level R-97 [4].) measurements can be analysed separately. This allows the If a sound is identified as tonal, then it becomes neces- penalised periods to affect the regression between the meas- sary to assess how much ‘tonality’ is unacceptable and how ured sound levels and the wind speed when there is unac- the penalty should be applied to the 10-min L wind farm ceptable tonality. A90 sound level measurements. NZS 6806:2010 [93] implies that Several recent studies illustrate the complexities of inves- if tonality is detected, then the penalty should be applied tigation of the potential for tonality to influence perception to each 10 min L measurement, and that each penalised of wind turbine noise and the annoyance related to it. Søn- A90 measurement should then be included in the regression dergaard and Pedersen [97] noted the technical difficulties analysis. If these modified measurements are sufficient to in reconciling objective analysis of sound characteristics affect this regression, then the tonality effect is considered with subjective listening tests, pointing out for measure- to be ‘influential’. ments conducted over lengthy periods, short periods of high The NZ Standard does not provide guidance regarding tonality may not be detected. Yokoyama et al. [98] examined how much of the 10-min measurement can exhibit tonality methods to assess the effect of tonal components on subjec- in order to necessitate applying the penalty. For example, tive perception of noise, both physically (perception) and should the entire 10-min measurement exhibit tonality in psycho-acoustically (annoyance), demonstrating an influ- order to apply the penalty, or should the penalty apply if ence of tonality on both aspects, but with considerable vari- only part of the measurement is tonal? In practice, there ability in the response between individuals. Oliva et al. [99] is considerable variability, and it would be unusual for an argue against using fixed penalty values for tonal sound, entire 10-min noise measurement period to exhibit objec- suggesting, based on their assessment, that these penalties tively measured tonality. For the Te Rere Hau review [94] should vary with tonal frequency, tonal audibility and overall in New Zealand, it was accepted that if 2 min of the period level. exhibited measurable tonality, then the tonal penalty should Further work is required. The committee recommends apply to the whole period’s sample. If more than one tone that detailed attention now be given to the potential for tonal- in one period produces a penalty, it was decided that only ity to influence perception of wind turbine noise and annoy - one penalty (the greatest of them) should be applied to the ance related to it. This should include financial support for period. studies of the phenomenon and its behavioural implications. 1 3 Acoustics Australia (2020) 48:181–197 191 device itself, and only store or transmit the output of the 10 Wind Farm Sound Measurement analysis rather than raw audio signals. and Analysis The primary issue with any unattended sound monitoring and automated assessment is the potential for ‘false-positive’ The consideration of automated, unattended long-term sound level exceedances from unrelated local noise sources, measurement of wind farm sound is specifically raised in rather than the subject sound source (wind turbines in this the Terms of Reference for the Committee and was sug- case). One approach to limiting ‘false positive’ noise level gested at the original Australian Senate hearing into wind exceedance from automated unattended sound monitoring turbine noise. Sound measurement, and particularly auto- systems is to use directional microphone systems that limit mated unattended noise monitoring seems to be seen as a the noise received from areas other than in the direction of common solution to wind farm problems and the manage- the wind farm. The Australian developed ‘Barn Owl’ direc- ment of wind farm noise. However, there are many practi- tional microphone system has been used successfully for this cal issues with these types of sound measurement systems purpose around open cut mines. A similar cross-correlated particularly related to the use of precision microphones microphone array has also occasionally been used for spe- in inhospitable measurement environments, ongoing cali- cific wind farm noise measurements in the USA. Unfortu- bration, and the use of signal processing to automatically nately, such systems typically use additional microphones positively identify particular sound sources contributing and complex signal processing and further complicate any to the measured level at the sound level meter. automated unattended noise measurement system. Nevertheless, within the industry, there has been a move There are real practical issues with putting microphones towards conducting greater frequency analysis of wind tur- outside in the field: they are calibrated, sensitive devices. bine sound in addition to A-weighted sound level measure- There are ways to reduce these practical issues, but they are ments, and to adopt real time telemetry and real time audio expensive. Some of these issues are discussed in detail in the recordings. It is apparent that in future, as these technolo- committee’s paper [12] in the context of the measurement of gies mature, it should be possible to use real-time wind IS/LF energy from wind turbines. This is an area identified turbine sound measurements to actively control and man- as a potential target for the investment of research funding. age wind farms in order to satisfy sound level limits. In Since wind farms are necessarily located in windy areas, particular, all the relevant operating data of wind turbines there is a need to adequately protect microphones from wind are now routinely recorded using the Supervisory Control noise while not affecting their ability to accurately meas- And Data Acquisition (SCADA) system in order to opti- ure the wind farm noise. This typically requires the use of mise wind farm performance and manage and undertake special microphone wind shields incorporating a complex preventative maintenance. (SCADA is a system of soft- arrangement of inner and outer microphone wind screens. ware and hardware which allows the control and monitor- Protection against wind noise is easier if infrasound does ing of industrial processes at local or remote locations and not need to be measured and measurements only need to be the processing of data in real time. SCADA is widely used made in the audible frequency range. in the wind turbine industry.) It is therefore an extension of There are also practical and legal issues relating to the these existing systems to record sound measurement and placement of any microphone measurement system. For analysis data with the wind farm’s SCADA system and example, it is sometimes necessary to rent space in which to potentially to use this data to control the wind turbines. place the microphone. This typically requires a large volume It would be helpful if the wind farm industry were more of legal work to write agreements which ensure appropriate willing to share this SCADA data with researchers and access to data while restricting distribution of sensitive or other stakeholders. It is reported that sharing of such data commercial-in-confidence data. For instance, if a monitoring rarely occurs in Australia. While some of this data is com- system is placed on stakeholder land, then the stakeholder mercially sensitive, it should be possible to draft suitable may demand access to data which the wind farm operator is confidentiality agreements to allow this sharing to occur. unwilling to disclose. It is also important to note that there remain some The committee recommends that wind farm operators be potential legal issues in relation to the ongoing recording encouraged to continuously monitor wind turbine sound at of sound related to people’s privacy where sounds gener- some sensitive locations and be encouraged to incorporate ated by people may be recorded. Such recordings could these sound measurements as part of their SCADA sys- potentially breach various Australian States’ Listening tems. This sound data should be monitored by signal pro- Devices Acts when using long term audio recordings, and cessing systems to detect unusual sounds such as tonality further legal advice is required. One response may be to and excessive amplitude modulation. The Australian Gov- undertake the analysis of the sound at the measurement ernment should consider investing in the development of such technology so that the resulting Australian IP could be 1 3 192 Acoustics Australia (2020) 48:181–197 incorporated internationally as a ‘best in class’ mechanism It examines the ways that these effects can be assessed and of monitoring. mitigated. In so doing it provides an objective basis for harmonisation across Australia of provisions for siting and monitoring of wind turbines, which currently vary from state 11 Management Strategies to state, contributing to contention and potential inequities between Australians, depending on their place of residence. It is essential to ensure that wind turbine audible noise limits This paper shows that if rounding is removed, the outdoor are implemented and observed. These are needed to ensure wind turbine sound limits recommended by a recent World that: (a) the noise source is engineered and maintained to Health Organization report are the same as those recom- acceptable standards that limit noise generation and exclude mended for use in Australia by this paper. These limits are abnormal noises; and (b) that suitable setbacks are provided derived by determining the wind turbine level at which 10% to allow attenuation of sound emanating from the source of people are highly annoyed with wind turbines. Annoy- to acceptable, near imperceptible levels beyond this set- ance is used to set these wind turbine noise limits because back distance. For the small percentage of people affected the level of annoyance with wind turbines is the only effect by wind turbine noise [100], despite such provisions, other which consistently correlated with wind turbine noise sound strategies must also be considered. While one solution would level. It should be noted that this annoyance may not only be to assist these people to move away from wind turbine be due to wind turbine noise. Wind turbine noise level may locations, this may not always be possible. only be a proxy for distance from the wind turbines. On the Leventhall et  al. [101, 102] have used psychotherapy other hand, this paper also surveys possible perceptual and techniques such as cognitive behaviour therapy to help physiological effects of wind turbine noise. The paper also sufferers of low frequency noise cope with the noise. This looks at wind farm sound measurement and analysis includ- work was supported by the United Kingdom Department ing tonality and amplitude modulation, annoyance attributed for Environment, Food and Rural Affairs (DEFRA). These to low frequency noise, low frequency noise limits and man- psychotherapy techniques may be of assistance to people agement strategies to reduce annoyance with wind turbines. suffering from annoyance from wind turbine noise. Unfortu- In summary, the committee suggests that ‘annoyance’ is nately, these techniques appear to work best when the source the primary measure with which to set wind turbine noise of the noise is unknown, which is often the case with low limits and that the appropriate limit is one that ensures no frequency noise problems like “The Hum” as indicated in more than 10% of the population would be highly annoyed Sect. 6. With wind turbine noise, the source of the noise is when exposed to it. This threshold appears to be between well known. However, given that reported problems with 34–40 dB L outside the residence, with a mean Aeq (10 min) wind turbine noise can in some cases be accounted for by value of 37 dB L [3] and the committee urges har- Aeq (10 min) annoyance and other psychological effects, then psychother - monisation of state-by state guidelines around this standard. apy techniques may be appropriate form of management, The perceptual and physiological effects, both known and although they are unlikely to be effective for all sufferers. suspected, of wind turbine noise justify such an effort. Masking low pitched sound with low frequency brown and Open Access This article is licensed under a Creative Commons Attri- black noise is another therapeutic technique, which van den bution 4.0 International License, which permits use, sharing, adapta- Berg and de Boer [103] found to be helpful for about half tion, distribution and reproduction in any medium or format, as long the people they studied who are annoyed by it. as you give appropriate credit to the original author(s) and the source, The fact that some complaints about wind turbines occur provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are before wind farms start operating means that sensitive included in the article’s Creative Commons licence, unless indicated treatment of residents during the planning and construc- otherwise in a credit line to the material. If material is not included in tion phases is essential. Distribution of financial benefits to the article’s Creative Commons licence and your intended use is not effected residents will also help once the wind farm starts permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a operating. Rapid response to any problems reported by resi- copy of this licence, visit http://creativ ecommons .or g/licenses/b y/4.0/. dents is necessary. 12 Conclusions Appendix: The Statistical Power of Wind Turbine Noise Studies This paper provides a review of important aspects of the real and potential impacts of wind turbines on human well- Annoyance with wind turbines is the only of effect of wind being. It considers wind turbine noise and its relationship turbines on their neighbouring populations which has been to annoyance, sleep disturbance, quality of life and health. consistently discovered. This appendix investigates why 1 3 Acoustics Australia (2020) 48:181–197 193 other effects such as diseases caused by wind turbines have not been consistently found. An important point requiring discussion is the statistical sensitivity of any study and its capacity to detect the presence of an effect within a popula- tion. This is generally referred to as the statistical power of a population sampling study and quantifies the capacity to measure an experimental effect and/or to determine the proportion of the underlying population that show such an effect. If a population is assumed to be normally distributed with respect to a feature, then only a particular fraction of that population is likely to display such sensitivity above a cer- tain threshold. In the case of possible health effects of wind turbines, the relatively infrequent reports of ill health effects suggest that the sensitive proportion of the population is quite low [100]. The capacity to detect such sensitivity using Fig. 1 Percentage of experiments for which the occurrence of the dis- a population sampling approach will be dependent on the ease is zero. The disease probability is 0.1% and the sensitivity and underlying proportion in the population that display such a specificity are both 1.0 sensitivity and the number of samples taken from the popu- lation. For the Health Canada sleep disturbance study, the than 5% chance that the test will provide a type II error (i.e. smallest detectable percentage of people whose sleep quality incorrectly retain a false null hypothesis). In this simulation was worsened by increased wind turbine noise levels was there was a disease (0.1% rate) and the black bars represent estimated to be 7%. Since the Health Canada study did not the percentage of tests that would return P(disease) = 0, i.e. find any significant effects other than annoyance, the number a type II error of people suffering from disease due to exposure to wind This indicates that, of the many population studies of the turbine noise is likely to be substantially less than 7%. For effects wind turbines on the population where the focus has two relatively common clinical conditions of the inner ear, been on random sampling, the numbers of samples (gener- it is estimated that 0.2% of the population suffer Meniere’s ally of the order 10 ) are well below the numbers that would disease while recent estimates of superior semicircular canal be required to reliably detect the other relatively common dehiscence are around 0.1% of the population. In the absence inner ear conditions (order 10 samples). In the absence of of a known prevalence in the neighbouring population of any other data, the disease prevalence is estimated from the diseases caused by wind turbines, the authors have chosen to prevalence of superior semicircular canal dehiscence (SCD: use 0.1% of the neighbouring population based on the esti- 0.1%). A systematic analysis of health practitioner records mated prevalence of superior semicircular canal dehiscence as a percentage of the total exposed population in potentially to demonstrate the difficulty of detecting effects with low affected regions might provide a more grounded indication levels of prevalence in the population. The authors do not of the likely fraction of the population that may be suscepti- imply that 0.1% is the actual percentage of the population ble to wind turbine sound (presuming that is based on some suffering from diseases caused by wind turbines, since the similar inner ear dysfunction). actual figure is currently unknown. A second and critical issue in the analysis of such low The committee has used a simple model of statisti- prevalence occurrences is how they are identified and cur - cal power to examine the impact of sample size using the rently treated in the analysis of the population data. It is assumptions that (1) the prevalence of the disease is similar statistically impossible for a small number of low preva- to that of semicircular canal dehiscence (i.e. 0.1%) and (2) lence samples to have any meaningful impact on summary for simplicity we have chosen the best case scenario where statistics (the mean, median or mode) of a population. The the sensitivity of the test for the disease is perfect (100% meta-analyses of previous studies of potential health effects detection and no false alarms). of wind turbines have also used more traditional summary Figure 1 plots the percentage of studies that would fail to and linear regression models. More appropriate would be the detect the disease with an actual 0.1% prevalence with sam- identification of people who may potentially be more likely ple sizes ranging from 100 to 3200. The bottom dashed black to be affect by wind turbine noise for further examination, an line indicates 5%. The above model indicates that (1) for approach that is being pursued in the recent NHMRC funded sample sizes of 400 or less there is 70% to 90% chance that research projects. the test would fail to return a positive result; (2) a sample size of around 3200 samples is needed before there is a less 1 3 194 Acoustics Australia (2020) 48:181–197 noise annoyance. Appl. Acoust. 140, 288–295 (2018). https :// Because many of the symptoms claimed to be caused by doi.org/10.1016/j.apaco ust.2018.06.009 wind turbine noise are reasonably common in populations 4. ETSU-R-97.: The Assessment and Rating of Noise from Wind not exposed to wind turbine noise, it is even more difficult Farms, pp. 1–153. Department of Trade and Industry, London to detect statistically significant changes in the occurrence (1996) 5. World Health Organisation: Environmental Noise Guidelines of these symptoms in populations that are exposed to wind for the European Region. World Health Organisation Regional turbine noise. The Health Canada study [11] was designed Office for Europe, Copenhagen (2018) to be able to detect a relationship between a change in sleep 6. National Health and Medical Research Council.: NHMRC disturbance and wind turbine noise level. It was estimated Statement: Evidence on Wind Farms and Human Health, p. 1. National Health and Medical Research Council, Canberra that there would be 1120 survey responses and the stand- (2015) ard 95% confidence limits were to be used. This meant that 7. van den Berg, F.: Criteria for wind farm noise: Lmax and Lden. there was an 80% chance of being able to detect at least a Paper presented at the Euronoise 2008, Paris, June 29–July 4 7% difference in sleep disturbances in persons exposed to (2008) 8. Michaud, D.S., Keith, S.E., Feder, K., Voicescu, S.A., Marro, outdoor wind turbine noise of more than 40 dB(A) compared L., Than, J., Guay, M., Bower, T., Denning, A., Lavigne, E., to persons exposed to less than 40 dB(A) and only a 5% Whelan, C., Jannssen, S.A., Leroux, T., van den Berg, F.: Per- chance of detecting a difference where no difference actually sonal and situational variables associated with wind turbine existed [11, 104]. This statistical power calculation assumed noise annoyance. J. Acoust. Soc. Am. 139(3), 1455–1466 (2016). https ://doi.org/10.1121/1.49423 90 that the baseline prevalence for reported sleep disturbance 9. Michaud, D.S., Keith, S.E., Feder, K., Voicescu, S.A., Marro, in people exposed to outdoor wind turbine noise of less than L., Than, J., Guay, M., Bower, T., Denning, A., Lavigne, E., 40 dB(A) was between 7 and 10% and that 20% of the survey Whelan, C., Jannssen, S.A., Leroux, T., van den Berg, F.: population would be exposed to outdoor wind turbine noise Erratum: Personal and situational variables associated with wind turbine noise annoyance [J. Acoust. Soc. Am. 139(3), of more than 40 dB(A). It is probable that similar figures 1455–1466 (2016)]. J. Acoust. Soc. Am. 140(4), 2234 (2016). would apply to the detection of health effects. This means http://dx.doi.org/10.1121/1.49638 38 that if wind turbines cause health problems for less than 7% 10. Michaud, D.S., Feder, K., Keith, S.E., Voicescu, S.A., Marro, of the population, this effect is going to be very difficult, if L., Than, J., Guay, M., Denning, A., McGuire, D.A., Bower, T., Lavigne, E., Murray, B.J., Weiss, S.K., van den Berg, F.: Expo- not impossible, to rigorously detect using these sample sizes. sure to wind turbine noise: perceptual responses and reported Much larger sample sizes would need to be applied to detect health effects. J. Acoust. Soc. Am. 139(3), 1443–1454 (2016). low prevalence effects. https ://doi.org/10.1121/1.49423 91 A Danish study [105, 106] currently underway will 11. Michaud, D.S., Feder, K., Keith, S.E., Voicescu, S.A., Marro, L., Than, J., Guay, M., Denning, A., Murray, B.J., Weiss, S.K., address some of the problems raised in this section. It is Villeneuve, P.J., van den Berg, F., Bower, T.: Effects of wind a study of all Danes exposed to wind turbine noise since turbine noise on self-reported and objective measures of sleep. 1982. It is looking at the potential association of wind tur- Sleep 39(1), 97–109 (2016). https://doi.or g/10.5665/sleep.5326 bine noise with diabetes, cardiovascular diseases, perinatal 12. Carlile, S., Davy, J.L., Hillman, D., Burgemeister, K.: A review of the possible perceptual and physiological effects of birth factors and the use of medication for hypertension, wind turbine noise. Trends Hear. 22, 1–10 (2018). https ://doi. sleep problems and depression. It includes 553,066 dwell- org/10.1177/23312 16518 78955 1 ings and more than 1.3 million adult Danes. This study did 13. Council of Canadian Academies: Understanding the Evidence: not support an association between wind turbine noise and Wind Turbine Noise. The Expert Panel on Wind Turbine Noise and Human Health, Council of Canadian Academies, Ottawa redemption of antihypertension medication [107]. Poulsen (2015) et al. [108] did find an association between outdoor wind 14. Hansen, C.H., Hansen, K.L.: Recent advances in wind tur- turbine noise level and first redemption of sleep medication bine noise research. Acoustics 2, 172–207 (2020). https ://doi. or antidepressants by people aged 65 years or older. org/10.3390/acous tics2 01001 3 15. Knopper, L.D., Ollson, C.A., McCallum, L.C., Whitfield Aslund, M.L., Berger, R.G., Souweine, K., McDaniel, M.: Wind turbines and human health. Front. Public Health (2014). https ://doi.org/10.3389/fpubh .2014.00063 References 16. L’Agence nationale de sécurité sanitaire de l’alimentation, d.l.e.e.d.t.: Evaluation des effets sanitaires des basses fréquences sonores et infrasons dus aux parcs éoliens [Evalu- 1. Commonwealth of Australia.: Senate Select Committee on Wind ation of the health effects of low sound and infrasonic frequen- Turbines Final report, p. 350. Commonwealth of Australia, Can- cies due to wind farms]. In. L’Agence nationale de sécurité berra (2015) sanitaire de l’alimentation, de l’environnement et du travail, 2. Hübner, G., Pohl, J., Hoen, B., Firestone, J., Rand, J., Elliott, Maisons-Alfort, France (2017) D., Haac, R.: Monitoring annoyance and stress effects of wind 17. McCunney, R.J., Mundt, K.A., Colby, W.D., Dobie, R., Kaliski, turbines on nearby residents: a comparison of U.S. and Euro- K., Blais, M.: Wind turbines and health: a critical review of pean samples. Environ. Int. 132(105090), 1–9 (2019). https :// the scientific literature. J. Occup. Environ. Med. 56(11), e108– doi.org/10.1016/j.envin t.2019.10509 0 e130 (2014). https://doi.or g/10.1097/JOM.0000000000 00031 3 3. Davy, J.L., Burgemeister, K., Hillman, D.: Wind turbine sound limits: current status and recommendations based on mitigating 1 3 Acoustics Australia (2020) 48:181–197 195 18. National Health and Medical Research Council.: Information impacts of wind farm noise on sleep. Acoust. Aust. 46(1), Paper: Evidence on Wind Farms and Human Health, pp. 1–42. 87–97 (2018). https ://doi.org/10.1007/s4085 7-017-0120-9 National Health and Medical Research Council, Canberra (2015) 36. van den Berg, F.: Effects of sound on people. In: Bowdler, D., 19. Onakpoya, I.J., O’Sullivan, J., Thompson, M.J., Heneghan, C.J.: Leventhall, G. (eds.) Wind Turbine Noise, vol. 6, pp. 129–151. The effect of wind turbine noise on sleep and quality of life: a Multi-Science Publishing Co.Ltd, Brentwood (2011) systematic review and meta-analysis of observational studies. 37. Janssen, S., Vos, H., Eisses, A.R.: Hinder door geluid van Environ. Int. 82, 1–9 (2015). h t t p s : / / d o i . o r g / 1 0 . 1 0 1 6 / j . e nv i n windturbines-dosis-effectrelaties op basis van Nederlandse t.2015.04.014 en Zweedse gegevens (Annoyance from wind turbine sound- 20. Schmidt, J.H., Klokker, M.: Health effects related to wind turbine dose-effect relations based on Dutch and Swedish data-in noise exposure: a systematic review. PLoS ONE 9(12), e114183 Dutch) TNO-rapport 2008-D-R1051/B. In., vol. TNO-rapport (2014). https ://doi.org/10.1371/journ al.pone.01141 83 2008-D-R1051/B, pp. 1-29. TNO, Delft (2008) 21. van Kamp, I., van den Berg, F.: Health effects related to wind 38. Bakker, R.H., Pedersen, E., van den Berg, G.P., Stewart, turbine sound, including low-frequency sound and infrasound. R.E., Lok, W., Bouma, J.: Impact of wind turbine sound on Acoust. Aust. 46(1), 31–57 (2018). https: //doi.org/10.1007/s4085 annoyance, self-reported sleep disturbance and psychological 7-017-0115-6 distress. Sci. Total Environ. 425, 42–51 (2012). https ://doi. 22. Hansen, K.L., Hansen, C.H., Zajamšek, B.: Outdoor to indoor org/10.1016/j.scito tenv.2012.03.005 reduction of wind farm noise for rural residences. Build. Environ. 39. Pedersen, E.: Health aspects associated with wind turbine 94, 764–772 (2015) noise—results from three field studies. Noise Control Eng. J. 23. Marcillo, O., Arrowsmith, S., Blom, P., Jones, K.: On infrasound 59(1), 47–53 (2011). https ://doi.org/10.3397/1.35338 98 generated by wind farms and its propagation in low-altitude 40. Pedersen, E., Persson Waye, K.: Perception and annoyance due tropospheric waveguides. J. Geophys. Res. Atmos. 120(19), to wind turbine noise: a dose-response relationship. J. Acoust. 9855–9868 (2015). https ://doi.org/10.1002/2014J D0228 21 Soc. Am. 116(6), 3460–3470 (2004) 24. Pedersen, S., Møller, H., Waye, K.P.: Indoor measurements of 41. Pedersen, E., van den Berg, F., Bakker, R., Bouma, J.: noise at low frequencies-problems and solutions. J. Low Freq. Response to noise from modern wind farms in The Nether- Noise Vib. Act. Control 26(4), 249–270 (2007) lands. J. Acoust. Soc. Am. 126, 634–643 (2009). https ://doi. 25. Schomer, P.D., Erdreich, J., Pamidighantam, P.K., Boyle, J.H.: org/10.1121/1.31602 93 A theory to explain some physiological effects of the infrasonic 42. Pedersen, E., Persson Waye, K.: Wind turbine noise, annoy- emissions at some wind farm sites. J. Acoust. Soc. Am. 137(3), ance and self-reported health and well-being in different living 1356–1365 (2015). https ://doi.org/10.1121/1.49137 75 environments. Occup. Environ. Med. 64(7), 480–486 (2007) 26. Zajamšek, B., Hansen, K.L., Doolan, C.J., Hansen, C.H.: Char- 43. Feder, K., Michaud, D.S., Keith, S.E., Voicescu, S.A., Marro, acterisation of wind farm infrasound and low-frequency noise. L., Than, J., Guay, M., Denning, A., Bower, T., Lavigne, E., J. Sound Vib. 370, 176–190 (2016). https ://doi.org/10.1016/j. Whelan, C., van den Berg, F.: An assessment of quality of life jsv.2016.02.001 using the WHOQOL-BREF among participants living in the 27. Zorumski, W., Willshire Jr., W.: Downwind sound propagation in vicinity of wind turbines. Environ. Res. 142, 227–238 (2015). an atmospheric boundary layer. AIAA J. 27(5), 515–523 (1989). https ://doi.org/10.1016/j.envre s.2015.06.043 https ://doi.org/10.2514/3.10141 44. Mroczek, B., Banaś, J., Machowska-Szewczyk, M., Kurpas, D.: 28. Thorsson, P., Persson Waye, K., Smith, M., Ögren, M., Pedersen, Evaluation of quality of life of those living near a wind farm. E., Forssén, J.: Low-frequency outdoor indoor noise level differ - Int. J. Environ. Res. Public Health 12, 6066–6083 (2015). https ence for wind turbine assessment. J. Acoust. Soc. Am. 143(3), ://doi.org/10.3390/ijerp h1206 06066 206–211 (2018). https ://doi.org/10.1121/1.50270 18 45. Mroczek, B., Kurpas, D., Karakiewicz, B.: Influence of dis- 29. Hoffmeyer, D., Jakobsen, J.: Sound insulation of dwellings at low tances between places of residence and wind farms on the qual- frequencies. J. Low Freq. Noise Vib. Act. Control 29(1), 15–23 ity of life in near by areas. Ann. Agric. Environ. Med. 19(4), (2010) 692–696 (2012) 30. Salt, A.N., Hullar, T.E.: Responses of the ear to low frequency 46. Shepherd, D., McBride, D., Welch, D., Dirks, K.N., Hill, E.M., sounds, infrasound and wind turbines. Hear. Res. 268, 12–21 et al.: Evaluating the impact of wind turbine noise on health- (2010) related quality of life. Noise Health 13(54), 333 (2011) 31. Salt, A.N., Lichtenhan, J.T.: How does wind turbine noise affect 47. Leventhall, G., Pelmear, P., Benton, S.: A Review of Published people? Acoust. Today 10, 20–28 (2014) Research on Low Frequency Noise and Its Effects. Department 32. Dommes, E., Bauknecht, H., Scholz, G., Rothemund, Y., Hensel, for Environment, Food and Rural Affairs, London (2003) J., Klingebiel, R.: Auditory cortex stimulation by low-frequency 48. Moorhouse, A.T., Waddington, D.C., Adams, M.D.: Procedure tones—an fMRI study. Brain Res. 1304, 129–137 (2009). https for the assessment of low frequency noise complaints. Report ://doi.org/10.1016/j.brain res.2009.09.089 for Defra, NANR45 Revision 1. Acoustics Research Centre, 33. Weichenberger, M., Bauer, M., Kühler, R., Hensel, J., For- University of Salford (2011) lim, C.G., Ihlenfeld, A., Ittermann, B., Gallinat, J., Koch, S., 49. International Organization for Standardization: ISO 226:1987 Kühn, S.: Altered cortical and subcortical connectivity due to Normal Equal-Loudness Level Contours. International Organi- infrasound administered near the hearing threshold—evidence zation for Standardization, Geneva (1987) from fMRI. PLoS ONE 12(4), e0174420 (2017). https ://doi. 50. Dobie, R.: Robert Dobie’s letter regarding Salt and Lichten- org/10.1371/journ al.pone.01744 20 ham, Letter to the editor. Acoust. Today 10(2), 14 (2014) 34. Weichenberger, M., Kühler, R., Bauer, M., Hensel, J., Brühl, R., 51. Leventhall, G.: How the “mythology” of infrasound and low Ihlenfeld, A., Ittermann, B., Gallinat, J., Koch, S., Tilmmann, frequency noise related to wind turbines might have developed. S., Kühn, S.: Brief bursts of infrasound may improve cognitive Paper Presented at the First International Meeting on Wind function—an fMRI study. Hear. Res. 328, 87–93 (2015). https:// Turbine Noise: Perspectives for Control, Berlin, Germany, doi.org/10.1016/j.heare s.2015.08.001 17–18 October (2005) 35. Micic, G., Zajamsek, B., Lack, L., Hansen, K., Doolan, C., 52. Leventhall, G.: Infrasound from wind turbines—fact, fiction or Hansen, C., Vakulin, A., Lovato, N., Bruck, D., Chai-Coetzer, deception. Can. Acoust. 34(2), 29–36 (2006) C.L., Mercer, J., Catchside, P.: A review of the potential 1 3 196 Acoustics Australia (2020) 48:181–197 53. Leventhall, G.: Concerns about infrasound from wind turbines. 72. Mullins, J.H., Kelly, J.P.: The mystery of the Taos hum. Echoes Acoust. Today 9(3), 30–38 (2013) 5(3), 6 (1995) 54. Schomer, P.D.: Comments on recently published article, concerns 73. Vasudevan, R.N., Gordon, C.G.: Experimental study of annoy- about infrasound from wind turbines. Acoust. Today 9(4), 7–9 ance due to low frequency environmental noise. Appl. Acoust. (2013) 10, 57–69 (1977). https://doi.or g/10.1016/0003-682X(77)90007 55. Jakobsen, J.: Danish guidelines on environmental low frequency -X noise, infrasound and vibration. J. Low Freq. Noise Vib. Act. 74. Lee, S., Kim, K., Choi, W., Lee, S.: Annoyance caused by ampli- Control 20(3), 141–148 (2001). https ://doi.org/10.1260/2F026 tude modulation of wind turbine noise. Noise Control Eng. J. 30920 11493 091 59(1), 38–46 (2011). https ://doi.org/10.3397/1.35317 97 56. van den Berg, G.P., Passchier-Vermeer, W.: Assessment of low 75. von Hünerbein, S., King, A., Piper, B., Cand, M.: Wind Turbine frequency noise complaints. Paper Presented at the Internoise Amplitude Modulation: Research to Improve Understanding as 1999, Fort Lauderdale, 06–08 December 1999 to its Cause and Effect Work Package B(2): Development of an 57. Broner, N.: A simple outdoor criterion for assessment of low AM Dose-Response Relationship, pp. 140–265. University of frequency noise emission. Acoust. Aust. 39(1), 7–14 (2011) Salford, Acoustics Research Centre, Manchester (2013) 58. Hessler, G.F.: Proposed criteria in residential communities 76. Bockstael, A., Dekoninck, L., Can, A., Oldoni, D., De Coensel, for low-frequency noise emissions from industrial sources. B., Botteldooren, D.: Reduction of wind turbine noise annoy- Noise Control Eng. J. 52(4), 179–185 (2004). https ://doi. ance: an operational approach. Acta Acust. United Acust. 98, org/10.3397/1.28397 48 392–401 (2012). https ://doi.org/10.3813/AAA.91852 4 59. Broner, N., Leventhall, G.: Low frequency noise annoyance 77. Ioannidou, C., Santurette, S., Jeong, C.-H.: Effect of modulation assessment by low frequency noise rating (LFNR) curves. J. Low depth, frequency, and intermittence on wind turbine noise annoy- Freq. Noise Vib. 2, 20–28 (1983). https: //doi.org/10.1177/02630 ance. J. Acoust. Soc. Am. 139(3), 1241–1251 (2016). https://doi. 92383 00200 103org/10.1121/1.49445 70 60. Inukai, Y., Taya, H., Utsugi, A., Nagamur, N.: A new evaluation 78. Yokoyama, S., Sakamoto, S., Tachibana, H.: Study on the method for low frequency noise. Paper presented at the Internoise amplitude modulation of wind turbine noise: part 2- Auditory 90 experiments. Paper Presented at the Inter-noise 2013, Innsbruck, 61. Vercammen, M.L.S.: Setting limits for low frequency noise. Austria J. Low Freq. Noise Vib. 8, 105–109 (1989). https ://doi. 79. Institute of Acoustics United Kingdom.: A Method for Rat- org/10.1260/2F026 30920 11493 091 ing Amplitude Modulation in Wind Turbine Noise. Institute of 62. Vercammen, M.L.S.: Low frequency noise limits. J. Low Freq. Acoustics United Kingdom (2016) Noise Vib. 11, 7–13 (1992). https:// doi.org/10.1177/2F026309 23 80. Large, S.: A quantitative and qualitative review of amplitude 92011 00102 modulated noise from wind energy development. Paper Presented 63. Evans, T., Cooper, J., Lenchine, V.: Low frequency noise near at the Inter-noise, Hamburg (2016) wind farms and in other environments. Environment Protection 81. Hansen, K.L., Nguyen, P., Zajamsek, B., Catcheside, P., Hansen, Authority, South Australia and Resonate Acoustics, Adelaide C.H.: Prevalence of wind farm amplitude modulation at long- (2013) range residential locations. J. Sound Vib. 455, 136–149 (2019). 64. Hansen, K., Zajamsek, B., Hansen, C.: Identification of low https ://doi.org/10.1016/j.jsv.2019.05.008 frequency wind turbine noise using secondary windscreens of 82. Perkins, R.A., Lotinga, M.J., Berry, B., Grimwood, C.J., Stans- various geometries. Noise Control Eng. J. 62(2), 69–82 (2014) feld, S.A.: A review of research into the human response to 65. Hansen, K., Zajamsek, B., Hansen, C.: Comparison of the noise amplitude-modulated wind turbine noise and development of levels measured in the vicinity of a wind farm for shutdown and a planning control method. Paper Presented at the Inter-noise, operational conditions. In: INTER-NOISE and NOISE-CON Hamburg (2016) Congress and Conference Proceedings 2014, vol. 2, pp. 5192– 83. Wright, J., Perkins, R.A.: Wind Turbine AM Review Phase 1 5202. Institute of Noise Control Engineering Report. WSP Parsons Brinckerhoff, Bristol (2015) 66. ANSI/ASA.: ANSI/ASA S12.9-2016/Part 7 American National 84. Lotinga, M.J., Perkins, R.A.: Wind Turbine AM Review Phase 2 Standard Quantities and Procedures for Description and Meas- Report. WSP Parsons Brinckerhoff, Bristol (2016) urement of Environmental Sound, Part 7: Measurement of Low- 85. Bowdler, D., Cand, M., Hayes, M., Irvine, G.: Wind turbine noise frequency Noise and Infrasound Outdoors in the Presence of amplitude modulation penalty considerations. Proc. Inst. Acoust. Wind and Indoors in Occupied Spaces. ANSI/ASA (2016) 40(1), 253–261 (2018) 67. Crichton, F., Dodd, G., Schmid, G., Gamble, G., Cundy, T., 86. Department of Planning and Infrastructure.: Draft NSW Planning Petrie, K.J.: The power of positive and negative expectations to Guidelines: Wind Farms, pp. 1–55. Department of Planning and influence reported symptoms and mood during exposure to wind Infrastructure, State of New South Wales, Sydney (2011) farm sound. Health Psychol. 33(12), 1588–1592 (2014). https :// 87. Cooper, J., Evans, T., Petersen, D.: Method for assessing tonal- doi.org/10.1037/hea00 00037 ity at residences near wind farms. Int. J. Aeroacoust. 14(5–6), 68. Crichton, F., Dodd, G., Schmid, G., Gamble, G., Petrie, K.J.: Can 903–908 (2015) expectations produce symptoms from infrasound associated with 88. International Organization for Standardization: Acoustics- wind turbines? Health Psychol. 33(4), 360–364 (2014). https :// Description, Measurement and Assessment of Environmental doi.org/10.1037/a0031 760 Noise-Part 2: Determination of Environmental Noise Levels. 69. Tonin, R., Brett, J., Colagiuri, B.: The effect of infrasound and International Organization for Standardization, Geneva (2007) negative expectations to adverse pathological symptoms from 89. Pedersen, T.H., Søndergaard, M., B., A.: Objective Method for wind farms. J. Low Freq. Noise Vib. Act. Control 35(1), 77–90 Assessing the Audibility of Tones in Noise, Joint Nordic Method- (2016). https ://doi.org/10.1177/02630 92316 62825 7 Version 2, Report AV 1952/99. DELTA Acoustics & Vibration, 70. Cowan, J.P.: The Kokomo Hum Investigation. Acentech Incor- Hørsholm, Denmark (1999) porated, Moulton (2003) 90. Hansen, C.H., Doolan, C.J., Hansen, K.L.: Wind Farm Noise: 71. Leventhall, G.: Low frequency noise and annoyance. Noise Measurement, Assessment, and Control. Wiley, Chichester Health 6(23), 59–72 (2004) (2017) 1 3 Acoustics Australia (2020) 48:181–197 197 91. International Organization for Standardization: ISO/PAS 102. Leventhall, G., Robertson, D., Benton, S., Leventhall, L.: Help- 20065:2016 Acoustics—Objective Method for Assessing the ing sufferers to cope with noise using distance learning cognitive Audibility of Tones in Noise—Engineering Method. Interna- behaviour therapy. J. Low Freq. Noise Vib. Act. Control 31(3), tional Organization for Standardization, Geneva (2016) 193–203 (2012). https://doi.or g/10.1260/2F0263-0923.31.3.193 92. International Organization for Standardization: ISO 1996–2:2017 103. van den Berg, F., de Boer, K.: The effect of brown and black Acoustics—Description, Measurement and Assessment of Envi- noise on persons suffering from a low frequency sound. Paper ronmental Noise—Part 2: Determination of Sound Pressure Presented at the International Congress on Acoustics 2019, Levels. International Organization for Standardization, Geneva Aachen, Germany (2019) (2017) 104. Voicescu, S.A., Michaud, D.S., Feder, K., Marro, L., Than, J., 93. Standards New Zealand.: NZS 6808:2010 Acoustics-Wind Farm Guay, M., Denning, A., Bower, T., van den Berg, F., Broner, Noise, pp. 1–43. Standards New Zealand (2010) N., Lavigne, E.: Estimating annoyance to calculated wind tur- 94. Rogers, P., Sweetman, G., Burgemeister, K.: Decision of Hearing bine shadow flicker is improved when variables associated with Commissioners on a Review of Resource Consent Conditions wind turbine noise exposure are considered. J. Acoust. Soc. Am. Relating to the Te Rere Hau Wind Farm Operated by New Zea- 139(3), 1480–1492 (2016). https ://doi.org/10.1121/1.49424 03 land Windfarms Limited, vol. PGR-120496-5-208-V1, p. 151. 105. Poulsen, A.H., Sørensen, M.: Wind turbine noise and health, a Palmerston North City Council (2017) nationwide prospective study in Denmark. Paper Presented at the 95. Smith, M., Chiles, S.: Analysis techniques for wind farm sound Inter-noise 2016, Hamburg, Germany, 21–24 August (2016) level measurements. Acoust. Aust. 40(1), 51–56 (2012) 106. Backalacz, C., Søndergaard, L.S., Laursen, J.E.: “Big noise data” 96. South Australian Environment Protection Authority: Wind Farms for wind turbines. Paper Presented at the Inter-noise 2016, Ham- Environmental Noise Guidelines 2019—Draft for Consultation. burg, Germany, 21–24 August (2016) South Australian Environment Protection Authority, Adelaide 107. Poulsen, A.H., Raaschou-Nielsen, O., Peña, A., Hahmann, A.N., (2019) Nordsborg, R.B., Ketzel, M., Brandt, J., Mette Sørensen, M.: 97. Søndergaard, L.S., Pedersen, T.H.: Tonality in wind turbine Long-term exposure to wind turbine noise and redemption of noise. IEC 61400-11 ver. 2.1 and 3.0 and the Danish/joint nor- antihypertensive medication: a nationwide cohort study. Envi- dic method compared with listening tests. Paper Presented at the ron. Int. 121, 207–215 (2018). https ://doi.org/10.1016/j.envin Wind Turbine Noise (2013) t.2018.08.054 98. Yokoyama, S., Kobayashi, T., Tachibana, H.: Perception of tonal 108. Poulsen, A.H., Raaschou-Nielsen, O., Peña, A., Hahmann, A.N., components contained in wind turbine noise. Paper Presented at Nordsborg, R.B., Ketzel, M., Brandt, J., Sørensen, M.: Impact the Inter-noise 2016, Hamburg (2016) of long-term exposure to wind turbine noise on redemption of 99. Oliva, D., Hongisto, V., Haapakangas, A.: Annoyance of low- sleep medication and antidepressants: a nationwide cohort study. level tonal sounds—factors ae ff cting the penalty. Build. Environ. Environ. Health Perspect. 127(3), 037005 (2019). https ://doi. 123, 404–414 (2017)org/10.1289/EHP39 09 100. Office of the National Wind Farm Commissioner: 2018 Annual Report by the Office of the National Wind Farm Commissioner Publisher’s Note Springer Nature remains neutral with regard to to the Parliament of Australia. Office of the National Wind Farm jurisdictional claims in published maps and institutional affiliations. Commissioner, Melbourne (2019) 101. Leventhall, G., Benton, S., Robertson, D.: Coping strategies for low frequency noise. J. Low Freq. Noise Vib. Act. Control 27(1), 35–52 (2008). https://doi.or g/10.1260/2F02630920 87844 25460 1 3 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acoustics Australia Springer Journals

A Review of the Potential Impacts of Wind Turbine Noise in the Australian Context

Loading next page...
 
/lp/springer-journals/a-review-of-the-potential-impacts-of-wind-turbine-noise-in-the-mRXi2CvIVX
Publisher
Springer Journals
Copyright
Copyright © The Author(s) 2020. corrected publication 2020
ISSN
0814-6039
eISSN
1839-2571
DOI
10.1007/s40857-020-00192-4
Publisher site
See Article on Publisher Site

Abstract

This manuscript describes a range of technical deliberations undertaken by the authors during their work as members of the Australian Government’s Independent Scientific Committee on Wind Turbines. Central to these deliberations was the requirement upon the committee to improve understanding and monitoring of the potential impacts of sound from wind turbines (including low frequency and infrasound) on health and the environment. The paper examines existing wind tur- bine sound limits, possible perceptual and physiological effects of wind turbine noise, aspects of the effects of wind turbine sound on sleep health and quality of life, low-frequency noise limits, the concept of annoyance including alternative causes of it and the potential for it to be affected by low-frequency noise, the influence of amplitude modulation and tonality, sound measurement and analysis and management strategies. In so doing it provides an objective basis for harmonisation across Australia of provisions for siting and monitoring of wind turbines, which currently vary from state to state, contributing to contention and potential inequities between Australians, depending on their place of residence. Keywords Wind turbines · Wind farms · Noise · Annoyance · Health · Sleep 1 Introduction While renewable energy from wind turbines can have a posi- tive environmental impact, wind turbines can also be visu- ally imposing and are a source of audible sound and infra- sound. If turbines are placed near to where people live, the * John Laurence Davy johnldavy@gmail.com wind turbine sound can potentially be loud enough to be a source of disturbance, potentially adversely affecting wake- Kym Burgemeister kym.burg@arup.com ful activities and/or sleep with resulting irritability, nega- tivity and cognitive disturbance. It is held by some people David Hillman hillo@it.net.au that the audible sound and infrasound may also have more specific effects on health and well-being, including potential Simon Carlile carlile.simon@gmail.com effects on non-auditory function of the inner ear [1 ]. Further- more, the visual impact of wind turbines may cause individ- Royal Melbourne Institute of Technology (RMIT) ual concern, both in terms of their appearance and, in some University, GPO Box 2476, Melbourne, VIC 3001, Australia cases, shadow flicker. Added to these concerns, individuals Infrastructure Technologies, CSIRO, Private Bag 10, may develop negative perceptions regarding a perceived lack Clayton South, VIC 3169, Australia of fairness in planning decisions regarding siting of turbines Arup, Sky Park, One Melbourne Quarter, 699 Collins Street, in proximity to their dwellings. These negative reactions to Docklands, VIC 3008, Australia wind turbine presence have been encapsulated in concept of Centre for Sleep Science, University of Western Australia, ‘annoyance’ [2]. Thus, there is a logical basis for now deriv- Crawley, WA 6009, Australia ing a wind turbine sound limit based on limiting annoyance. Faculty of Medicine, University of Sydney, Camperdown, In order to manage potential impacts from wind turbine Australia sound, governments and regulators have established wind [X] The Moonshot Factory, Mountain View, CA 94043, USA Vol.:(0123456789) 1 3 182 Acoustics Australia (2020) 48:181–197 turbine sound limits that place an upper limit on the sound being a good practical value [4]. These values are similar to level that wind farms can generate and effectively place a the lower maximum design limits already adopted, or pro- limit on how close wind turbines can be placed to dwellings posed for use in Australia of 35, 37 and 40 dB L . Aeq (10 min) and population centres. There is some disparity in approach Thus, this study provides a method for harmonisation of to this issue and this manuscript describes deliberations by future wind farm sound limits in Australia based on direct the Australian Government’s Independent Scientific Com- assessments of human response to wind farm sound. It mittee on Wind Turbines (‘the committee’) aimed at opti- should be noted that all sound pressure levels in this paper mising the approach to determining their minimum distance are A-weighted and given as dB(A) unless otherwise stated. from noise-sensitive receivers and their management. It The World Health Organisation (WHO) [5] released examines aspects of the effects on sleep health and qual- Environmental Noise Guidelines for the European Region ity of life, low-frequency noise limits, alternative causes of in 2018. This publication conditionally recommends reduc- annoyance, annoyance attributed to low-frequency noise, ing outdoor noise levels produced by wind turbines to which management strategies, amplitude modulation, measure- people are exposed to below an L of 45 dB(A). This is den ment of wind farm tonality, wind farm sound measurement based on four studies which show that 10% of the population and analysis, and the statistical power of wind turbine noise were highly annoyed with wind turbines when exposed to studies. outdoor wind turbine noise levels of L equals 45 dB(A). den The purpose of publishing these deliberations is, by mak- Like the National Health and Medical Research Council ing them available to technical experts for their considera- (NHMRC) [6], WHO rated the evidence used to determine tion and feedback, to facilitate and promote harmonisation this wind turbine noise limit as being of low quality and across Australian states of the provisions for siting and that is the reason why the recommendation is conditional. monitoring of wind turbines. This manuscript sits along- An L of 45 dB(A) is equivalent to an L of 38.6 dB(A). den Aeq side reports from the committee of a less technical nature, This conversion assumes that the distribution of wind tur- including its reports to parliament and fact sheets it intends bine sound levels is the same during the day, evening and to make available on its website. night [7]. This is close to the wind turbine noise limit of L Aeq of 37 dB(A) determined by the committee [3] using the same requirement of keeping the percentage of the exposed popu- 2 Wind Turbine Sound Limits lation who are highly annoyed with wind turbines to less than 10%. In fact, reading the L to the nearest 0.1 dB from den Committee members recently undertook a detailed review both the mean average European curve and the Japanese of the existing wind turbine sound limits in Australian states curve in the Fig. 16 of the WHO report [5] at which 10% of and several other countries with similar constraints, how people are highly annoyed with wind turbines gives 43.7 dB these were established and a method that could facilitate L which is equal to 37.3 dB L . It appears that the WHO den Aeq their harmonisation [3]. It was found that most existing wind sound level limit was rounded to the nearest 5 dB. The WHO farm sound limits appear to have been adopted to avoid sleep analysis did not include the 2016 results of Michaud et al. disturbance but were developed using data derived from [8–11]. If the committee’s sound level limit [3] is deter- sound sources other than wind turbines. This seems to have mined to the nearest 0.1 dB, rather than the nearest 1 dB, been a reasonable approach at the time of their adoption the limit is 35.3 dB L , which is equal to 37.3 dB A90(10min) because of the paucity of other suitable data. More recently, L , and is equal to the WHO value to the nearest 0.1 dB. Aeq the concept of ‘annoyance’ has been used to encapsulate Note however that the uncertainty limits are large. The WHO negative reactions to wind turbine sound. Given that many report found six studies which it rated as low quality, and studies have now demonstrated a significant relationship which did not reveal consistent results about effects of wind between annoyance and wind turbine sound level, regardless turbine noise on sleep disturbance. The WHO report found of whether sound was the major source of the annoyance, no studies on the effects of wind turbine noise on the preva- there is a logical basis for now deriving a wind turbine sound lence of ischaemic heart disease, hypertension, permanent limit based on annoyance. hearing impairment, and reading skills and oral comprehen- The committee’s analysis suggests that an appropriate sion in children. noise limit to ensure that no more than 10% of the popula- The committee recommends that state and territory gov- tion are ‘highly annoyed’ when exposed to wind farm noise ernments consider harmonising their wind turbine sound is between 34 and 40 dB L outside the residence, limits by adopting the limits proposed in their paper [3]. It Aeq (10 min) with a mean value of 37 dB L [3]. The cut-off of would also like to see more uniformity in sound measure- Aeq (10 min) 10% is somewhat arbitrary and itself could be a subject of ment and compliance requirements. Although the committee informed debate. The corresponding measurement limits in believes that wind turbine sound level should be the primary L are between 1.5 and 2.5 dB lower with 2 dB lower determinant of how close residences can be to wind turbines, A90(10 min) 1 3 Acoustics Australia (2020) 48:181–197 183 there should also be a minimum setback distance. This mini- or not of wind turbine noise (WTN), they do demonstrate mum distance may be varied under particular circumstances, that such sounds are encoded by the human nervous system. such as when the residences are exposed to the same high The committee concluded, consistent with other stud- winds as the wind turbines themselves. This produces high ies by the NHMRC, that the quality of data relating to the background noise levels at the residences and allows the potential health effects of WTN was not good. The review residences to be exposed to a higher level of wind turbine identifies a range of research questions that would be appro- noise and hence to be effectively closer to the wind turbines priate for further detailed study in order to address the many than would normally be the case. With current wind turbine outstanding scientific questions. In brief, these included: technology, this minimum distance should be in the range between the 1 km adopted by the Victorian Government and 1. Characterization and modelling of the sound generated the 1.5 km recommended by the National Health and Medi- by modern windfarms focusing on the blade-passing cal Research Council and adopted by the Queensland Gov- frequency (BPF) and higher harmonics along with the ernment. These minimum distances may need to be revised effects of terrain and atmospheric conditions, etc.; in the future due to technology changes. 2. The development of a more complete understanding of the interactions between WTN and the built structures in which people live and sleep; 3 Possible Perceptual and Physiological 3. New methods need to be developed for measuring acute Eec ff ts of Wind Turbine Infrasound and chronic exposure (dosimetry); and Low‑Frequency Noise 4. Structural and aeronautic engineering research to mini- mize the sound pressure level at the BPF; In a further publication, the committee [12] recognised 5. Effects of IS/LF on the cochlea and vestibular apparatus; and responded to the need to review the scientific litera - 6. A better understanding of the neural connectivity of the ture relating to possible perceptual and physiological effects inner ear and an understanding of the neural and behav- of infrasound and low-frequency sound (IS/LF). Previous ioural consequences of their possible activation by IS/ reviews [13–21] have mostly relied on an epidemiological LF; approach providing meta-analysis of the existing population- 7. Studies of individuals who report susceptibility to WTN based research. As outlined in Appendix, the sensitivity of for dysfunction or pathology that mediates susceptibil- this approach appears quite low. By contrast, the committee ity (e.g. superior semicircular canal dehiscence or lym- focussed on physiological mechanisms at the level of the phatic hydrops). individual to determine if there was evidence of an effect of IS/LF sound energy on the organism. The committee believes that further scientific research is Studies of the generation and propagation of IS/LF sound needed to discover why some people complain about being by wind turbines demonstrate that the acoustical energy per badly ae ff cted by wind turbine noise. It recommends that the unit frequency at the blade-passing frequency (BPF) and at NHMRC and ARC consider the research agenda outlined its harmonic frequencies below 10–15 Hz is greater than above for increased priority funding as one means to address at higher frequencies. Propagation models and field studies this potentially important public health and policy, energy have indicated that sound at these IS/LF frequencies can security and scientific issue. propagate with less attenuation with distance than higher frequencies because of their lower sound absorption during passage through the air and on reflection from the ground 4 Eec ff ts on Sleep Health and Quality of Life [12, 22–28]. Added to this is uncertainty regarding the effec- tiveness of sound insulation of houses at infrasound and low Most of the wind turbine noise limits that were described frequencies [29]. Given these uncertainties, there was a pau- in the committee’s earlier manuscript [3] were set to city of data relating to the potential exposure of individuals avoid sleep disturbance using generic noise studies and in the vicinity of wind turbines, particularly within dwellings the sound insulation provided by partially open windows. where they work and sleep. Thus, it makes sense to look at what evidence there is for Reviews of physiological transduction and neural excita- a relationship between wind turbine noise levels and sleep tion provided a strong prima facia case for the transduction disturbance. of IS/LF [12, 30, 31] and stimulation of the human nervous The NHMRC [6] stated that there is inconsistent, poor system consistent with studies demonstrating perceptual sen- quality direct evidence of an association between sleep dis- sitivity to high levels of IS/LF sounds and to neural (cortical) turbance and wind farm noise. They observed that sleep dis- activation at more moderate sound levels [12, 32–34]. While turbance was not objectively measured in the studies and that these data do not by themselves, speak to the health effects a range of other factors could explain the associations that 1 3 184 Acoustics Australia (2020) 48:181–197 were observed. Michaud et al. [11] used both self-reported This statement was re-enforced by the Health Canada study and objective measures of sleep quality. They concluded that [10]. However, it should be noted that the NHMRC [6] also there was no association between the exposure to outdoor stated that the evidence is of poor quality. Because of the con- wind turbine noise of up to 46 dB(A) and sleep disturbance. cern expressed by some people, they recommended further Micic et al. [35] have pointed out the limitations of this high-quality research into the possible health effects of wind study and the other studies discussed in this section. It the farms. To be clear, in a situation where data quality is poor, it case of the Michaud et al. study, these limitations included is not possible to draw a secure positive or negative conclusion the use of actigraphy for the objective measure of sleep and with respect to the question of the association between wind the use of calculated sound levels which ignored special turbine noise and health effects. audible characteristics. For instance, according to Feder et al. [43], there have van den Berg [36] stated that Janssen et al. [37] had ana- been a few studies on the relationship between quality of lysed the sleep disturbance data from two Swedish and one life and wind turbine noise level and the findings are incon- Dutch study whose annoyance data were used in the com- sistent. One group [44, 45] showed that quality of life mittee’s paper [3]. Janssen et al. only found a statistically improved with closer proximity to a wind farm, suggesting significant relationship between sleep disturbance and wind other factors apart from sound levels, influence this. On the turbine noise level when they excluded persons who received other hand, Shepherd et al. [46] found that the quality of economic benefit from the wind turbines [36, 37]. When all life decreased when the wind farm noise level increased. residents were included, there was no statistically significant Onakpoya et al. [19] cites this and several other studies to relationship. However, there may be a small percentage of support the relationship, but they noted some that did not the population with individual sensitivities which would not and they were unable to conduct a meta-analysis because be discovered by a study of this size. It should be noted that of inconsistency in the quality of life measures used across the sleep disturbance was not necessarily from wind turbine these studies. Given the absence of consistent data regarding noise. the effects of wind turbine noise on quality of life data, it Bakker et al. [38] further analysed the data on residents appears that quality of life measures alone cannot currently from the Dutch study who received no economic benefit. be recommended to set wind turbine noise limits. They found no statistically significant relationship between Most of these studies used very small numbers of partici- sleep disturbance and wind turbine noise level. There was a pants, which deprives the analyses of an appropriate level statistically significant relationship between annoyance and of statistical power to detect small influences in the larger sleep disturbance. In the quieter rural areas, there was also a population (see “Appendix”). These studies do not provide statistically significant relationship between annoyance and consistent evidence regarding the influence of wind turbine wind turbine noise level. noise on sleep health and quality of life or distinguish these Pedersen [39] re-analysed the data from the two Swedish influences from others in helping determine reasonable wind and one Dutch study. Pedersen found that there was a statis- turbine noise limits. This lack of consistency suggests that tically significant relationship between wind turbine noise some effects may only be experienced by a small propor - levels and sleep disturbance for the first Swedish study [40] tion of the population making their detection problematic and the Dutch study [41]. The second Swedish study [42] where studies with low participant numbers are used to highlights other factors, in addition to sound levels that influ- detect them. ence perception of and annoyance with wind turbine noise The committee supports the conclusions of the National including individual characteristics, such as noise sensitivity Health and Medical Research Council that there is currently and attitude to the source, and the influence of dissimilar no consistent evidence regarding the effects of wind farms environments, including the influence of terrain. Hence it on human health and their call for high quality research appears too simplistic to use analysis of sleep disturbance into the matter, particularly where close proximity (within in terms of wind turbine noise levels alone to set limits for 1500 m) is involved [6]. The committee notes that the wind wind turbine noise, as other factors are also involved. turbine industry is a very large and growing industry world- van den Berg [36] has concluded that audible noise from wide and such an investment could provide significant wind turbines may cause annoyance which aggravates sleep advantage to Australian industry. problems. Hence wind turbine noise limits which prevent annoyance may also prevent sleep disturbance. Thus, an alternative approach may be to set wind turbine noise lim- 5 Low‑Frequency Noise Limits its using the percentage of people who are highly annoyed given the current state of knowledge. Because of the concern that has been expressed about The NHMRC [6] concluded that there is no consistent evi- the possible effects of low-frequency noise from wind dence that wind farms cause adverse health effects in humans. turbines, it is appropriate to review existing or proposed 1 3 Acoustics Australia (2020) 48:181–197 185 low-frequency noise limits from around the world. Table 1 criteria [55]. L is the A-weight noise in the 10 to 160 Hz A, LF shows reference curves which have been used or suggested third octave bands. The Danish evening and night time third to be used for the control of generic low-frequency noise. octave band sound levels must be sufficiently below the Table 1 is taken from Leventhall et al. [47] and the reference 20 dB(A) contour values shown in Table 1, so that the com- curve recommended to DEFRA in the UK by Moorhouse bination of these third octave band values does not exceed et al. [48] has been added to the table. The ISO 226 values 20 dB(A). The value of the 20 dB(A) contour for each third are the threshold of human hearing sound levels taken from octave band is the sound pressure level in that third octave a version of ISO 226 [49] which is no longer current. Except band which on its own has a sound level of 20 dB(A). The for the Polish and Danish night values which are based on infrasound criterion is not greater than 85 or 90 dB(G) [55], A-weighted values, the values are similar to the human which wind turbine noise is well known to easily satisfy. threshold values at 50 Hz and below. This means that the A 5 dB penalty is added to the measured values for impul- creators of these limits considered that low-frequency noise sive noise such as single blows from a press or drop forge close to the hearing threshold could be annoying. Zajamšek hammer. et al. [26] have shown that indoor third octave band sound The Polish requirement is that noise is considered to be pressure levels of wind turbine noise below 50 Hz are signif- annoying if any third octave band level is greater than the icantly below the human hearing threshold. This leads some 10 dB(A) contour shown in Table 1 and greater than 10 dB researchers to believe that wind turbine noise below 50 Hz is for tonal noise or 6 dB for broadband noise above the third not a problem [50–53]. However, as noted in the committee’s octave band background noise level. This is the reason why previously published analysis [12], not all researchers agree the Polish curve is 10 dB lower than the Danish curve. The that this is the case [25, 30, 31, 54]. value of the 10 dB(A) contour for each third octave band is It should be noted that these criterion curves are applied the sound pressure level in that third octave band which on in different ways. Table  2 shows the Danish indoor noise its own has a sound level of 10 dB(A). Table 1 Low-frequency noise criterion curves Frequency Hz Poland Germany Netherlands Denmark Night Sweden UK ISO 226 10 dB(A) contour DIN 45680 dB NSG dB 20 dB(A) contour dB DEFRA dB dB 8 103 10 80.4 95 90.4 92 12.5 83.4 87 93.4 87 16 66.7 79 76.7 87 20 60.5 71 74 70.5 74 74.3 25 54.7 63 64 64.7 64 65 31.5 49.3 55.5 55 59.4 56 56 56.3 40 44.6 48 46 54.6 49 49 48.4 50 40.2 40.5 39 50.2 43 43 41.7 63 36.2 33.5 33 46.2 41.5 42 35.5 80 32.5 28 27 42.5 40 40 29.8 100 29.1 23.5 22 39.1 38 38 25.1 125 26.1 36.1 36 36 20.7 160 23.4 33.4 34 34 16.8 200 20.9 32 13.8 250 18.6 11.2 Table 2 Danish generic noise Infrasound L Low-frequency Normal noise limit L (dB) G A criteria (dB) noise (dB) Dwelling, evening and night 85 20 30 dB/25 dB Dwelling, day 85 25 30 dB-day and evening Classroom, office etc. 85 30 40 dB Other rooms in enterprises 90 35 50 dB 1 3 186 Acoustics Australia (2020) 48:181–197 According to Leventhall [47], in the application of the presence of people within a space. The levels of low fre- Swedish method, the noise may be considered a nuisance quency noise at the two wind farm locations, which were if its level exceeds the criterion curve in any third octave approximately 1.5 kilometres away from the nearest wind band. In the Dutch method, the LF sound is considered audi- turbine, were low in comparison with the urban areas and ble and potentially annoying if the equivalent third octave were not noticeably higher than at the other two rural sound pressure level is above the reference curve at one or locations. It should be noted that although this study did more frequencies [56]. The DEFRA method [48] requires give the time of day and the wind speed when the meas- any third octave band L which exceeds the criterion curve urements were made, it did not give the power output or eq to be investigated. The criterion curve is relaxed by 5 dB if other meteorological data. The low frequency levels at one the noise occurs only during the day or if the noise is not location remained below the Danish and DEFRA criteria fluctuating. at all times. The outdoor levels remained below 60 dB(C) Leventhall [47] has described the German DIN 45680 during the night-time periods. The Danish 20 dB(A) night- method. The difference (dB(C) − dB(A)) > 20 dB is used time criterion was exceeded for 10% of the measurement as an initial indication of the presence of low-frequency time at another location. This was believed to be due to noise. The noise is then measured in third octaves over the construction of the house rather than the contribution specified time periods and compared with the threshold of noise from Clements Gap Wind Farm. There were very curve in Table 1. The main frequency range is from 10 Hz occasional exceedances of the night-time DEFRA crite- to 80 Hz. Frequencies of 8 Hz and 100 Hz are used only if ria at this site, but the percentage of exceedances was no the noise has many components within the range 10 Hz to greater than at two other locations with no wind turbines 80 Hz. DIN 45680 assumes that the great majority of low- within 10 kilometres. Hansen et al. [64] measured wind frequency noise problems from industrial sources are tonal farm noise in the 50 Hz third octave which was well above and that thus the 8 Hz and 100 Hz third octave bands will the DEFRA limit. only rarely be used. If the level in a third octave band is 5 dB Organised shutdowns showed that the contribution of the or more above the level in the two neighbouring bands, the Bluff Wind Farm to low frequency noise levels at one loca- noise is described as tonal. For tonal noises, the level of the tion was negligible. There may have been a relatively small tone above the hearing threshold is found. All the limits are contribution of low frequency noise levels at this location reduced by 5 dB during night-time. from the Clements Gap Wind Farm at frequencies of 100 Hz Other possible low-frequency noise requirements are and above. However, Hansen et al. [65] did find a substantial upper outdoor limits of L equals 65 dB(C) during the day reduction in the low frequency noise levels during a shut- Ceq and 60 dB(C) during the night [57, 58]. As stated above, down of the Waterloo Wind Farm relative to levels during the difference (dB(C) − dB(A)) > 20 dB is also sometimes operation. used as an initial indication of the presence of low-frequency It is worth noting that the frequency ranges considered noise. Broner and Leventhall [59] have proposed the use of by all the standards discussed above do not extend to the Low-Frequency Noise Rating (LFNR) curves. Inukai et al. blade-passing frequencies and the early harmonics (approxi- [60] developed a new weighting curve for low-frequency mately 0.5–8.0 Hz) which represent the largest components noise. Vercammen [61, 62] developed low-frequency noise of IS and LF energy emitted by wind turbines. As discussed limits which appear to be the forerunner of the Danish limits. under ‘Possible perceptual and physiological effects of In urban environments, Evans et  al. [63] found that wind turbine noise’ above, there is a prima facia case for A-weighted low-frequency noise levels at all locations regu- the somatic and/or neural transduction of these frequencies, larly exceed the night time residential criteria of 20 dB(A) and Zajamšek et al. [26] found that wind turbine noise did used in Denmark (between 16 and 86% of the time). These increase the infrasonic and low frequency noise during quiet excluded periods affected by people’s daily activities. The night time periods. DEFRA night-time low frequency noise criteria were also The committee is unable to recommend low frequency regularly exceeded at the urban locations. sound or infrasound limits for wind farms in the absence In rural environments Evans et al. [63] found a lower of definite evidence of the health effects of low frequency level of low frequency noise in the environment at the four sound or infrasound from wind turbines. There would also rural locations relative to the seven urban locations. The need to be a reliable method of measuring low frequency measured night-time L levels at four rural locations noise and infrasound before a limit could be imposed. One A,LF exceeded the 20 dB(A) Danish criterion for only 10% of possible method is described in ANSI/ASA S12.9-2016/ the time or less. This 20 dB(A) criterion was not exceeded Part 7 [66]. The committee recommends that research on at one of the rural locations. The levels of low frequency the possible impact of low frequency sound and infrasound noise were correlated to wind speed at the measurement on humans from industrial sources including wind turbines site. At some locations, they were also affected by the is continued. 1 3 Acoustics Australia (2020) 48:181–197 187 Michaud et al. [8] further observed that personal ben- 6 Alternative Causes of Annoyance efit was not retained in their unrestricted modelling of the relationship between wind turbine noise and annoyance, It has been demonstrated experimentally that people suffer although this was probably due to the small number of par- more health problems if they are led to believe that wind ticipants in this category. Personal benefit was found to be turbines are harmful (nocebo effect) [67– 69]. This is an statistically significant in their restricted model, although example of the well-known psychological bias referred the associated increase in R with addition of this variable to as the ‘demand characteristic’ in perceptual and social was only 3%. Together with Pedersen et al. [41], these find- psychological research. ings support the distribution of direct or indirect personal Michaud et al. [8] examined the statistically significant benefits to participants living in close proximity to wind variables related to annoyance with wind turbines using a power projects. multiple logistic regression model. The importance of each The finding that wind turbine noise level alone is not a variable was ranked using the Nagelkerke pseudo R . The particularly strong predictor of annoyance with wind tur- closer the Nagelkerke pseudo R is to 100%, the better the bines suggests that other actions should be undertaken in multiple logistic regression model equation predicts the conjunction with the setting of wind turbine noise limits in observed probability of occurrence. Wind turbine noise order to reduce annoyance. Furthermore, it needs to be rec- level had an R equal to 9%. This increased to 11% when ognized that even small effects can be important as they may the location in Canada was added to form the base model. reflect the influence of a limited number of individuals with Addition of further variables including those related to particular sensitivities that need to be accounted for [47]. other wind turbine annoyance, personal benefit, noise The committee recommends that wind farm develop- sensitivity, physical safety concerns, property ownership ers educate, consult with and provide some resources to and the location within Canada of the operation lifted the the local community in order to identify and minimise the R value to 58% (meaning that 58% of the variance in diverse potential sources of annoyance with wind farms. the relationship of annoyance to wind turbines could be explained by them). This suggests that wind turbine noise alone is not a powerful predictor of annoyance, and that 7 Annoyance Attributed to Low Frequency many other factors contribute to the problem. Noise In further analysis Michaud et al. [8] noted that while they failed to find a relationship between wind turbine In various settings around the world, a small percentage of noise levels and sleep disturbance, the strongest associa- people report being annoyed by what they perceive as per- tion with annoyance was identifying wind turbines as the sistent low frequency noise, usually from an unknown or source of noise that led to window closing because it was undiscovered source as obvious sources have been elimi- disturbing sleep. They suggested that closing the window nated. This phenomenon is often referred to as ‘The Hum’. may be an expression of the annoyance towards WTN and/ It is helpful to examine reports of ‘The Hum’ because its or a coping strategy that protects against sleep disturbance. reported symptoms are similar to some of the symptoms Given that closing the window reduces the indoor WTN reported by some people living near wind turbines [47, level and hence improves sleep, this action may conceiv- 70–73]. The Hum is perceived as a low frequency noise ably explain the absent association between WTN levels which is often described as a throbbing noise. It is proba- and sleep disturbance. bly, but not necessarily, caused by low frequency noise from Michaud et al. [8] also noted that concern for physical industrial or other anthropogenic noise sources. There have safety due to the presence of wind turbines was a significant been several attempts to find the cause of the Hum recorded predictor of annoyance in both the unrestricted and restricted in the literature [70, 72, 73]. However, Leventhall (2004) models suggesting that actions (such as education and com- notes that ‘No widespread Hum has been unequivocally munity consultation) which address this concern during the traced to specific sources, although suspicion has pointed at planning stages of a wind project may reduce community industrial complexes, especially fans’. Even when low fre- annoyance toward wind turbine noise. Noise sensitivity quency sound sources have been found and quietened, this influences the response to community noise. Thus, it is not has not usually solved the problem completely [71]. surprising that noise sensitivity was associated with wind The ee ff cts of the Hum are reported as pressure or pain in turbine noise annoyance [8]. Crichton et al. [67] have con- the ear or head, body vibration or pain, loss of concentration, firmed this observation by showing that giving people posi- nausea and sleep disturbance. [47]. These general effects are tive expectations about exposure to wind turbine noise can reported internationally. statistically significantly reduce their health symptoms. This Unsympathetic handling of the complaint builds up stress is another example of the ‘demand characteristic’. and exacerbates the problems. Hum sufferers tend to be 1 3 188 Acoustics Australia (2020) 48:181–197 middle aged and elderly. They often have a low tolerance Some wind turbine noise policies in Australia and overseas level and are prone to negative reactions [47]. Personal ten- include penalties for sound from wind farms that has ‘special sions are reduced if the complaints are taken seriously by the audible characteristics’ (known as SACs) that are likely to authorities because this eases the additional stresses which make it significantly more noticeable and annoying to sensi- occur when they are not believed [47]. tive receivers. One of the key ‘special audible characteris- Leventhall et al. [47] summarised Vasudevan and Gor- tics’ of wind farm sound is the amplitude modulation (AM) don’s [73] experience from investigating the Hum as of the sound over time as the turbine blades are turning, follows:. which results in a rise and fall in wind farm loudness. This is usually characterised as a ‘whoosh–whoosh–whoosh’ sound The problems arose in quiet rural or suburban environ- modulated at the blade-passing frequency (usually around ments. 1–2 Hz). This sound is usually evident, to some extent, in The noise was often close to inaudibility and heard by a all wind turbine sound due to the nature of the noise genera- minority of people. tion mechanism at the turbine blade. However, the extent (or The noise was typically audible indoors and not outdoors. level) of modulation, known as the modulation depth, can The noise was more audible at night than during the day. vary significantly depending on the environmental condi - The noise had a throbbing and rumbly characteristic. tions, and some objective measure of the extent of amplitude The main complaints came from the 55–70 years age modulation, and its acceptability, is required. Some simple group. objective measures for AM were documented in the early The complainants had normal hearing. wind farm sound policies and standards, but there is gener- Medical examination excluded tinnitus. ally a concern that these were not rigorously developed, and their relationship to the extent of annoyance has never been These are now recognised as classic ‘hum’ descriptors. adequately demonstrated. It is often the case that only one person in a family is Lee et  al. [74] have studied the annoyance caused by sensitive to the Hum [47]. If the Hum is caused by sound, amplitude modulated wind turbine noise using 30 people. the fact that it is only ‘heard’ by a small minority of people They showed that the A-weighted equivalent sound level suggests that these people have more sensitive hearing than and the modulation depth both had a statistically significant the rest of the population. It has been suggested that the effect on the annoyance. However, the annoyance differences percentage of people in the effected age group who might between different modulation depths were only statistically be able to hear the Hum is 10% [56], 2.5% [71] or 0.5% [47]. significant when the difference in modulation depths was Leventhall et al. [47] assumed that the people most likely large. von Hünerbein et al. [75] showed that after remov- to suffer from the Hum were in the 50–59 age group who ing the effect of the A-weighted equivalent sound level, the comprise about 10% of the population. This meant that the annoyance increased monotonically with the modulation percentage of the total population likely to suffer from the depth, but this increase was not statistically significant due Hum is estimated to be 1%, 0.25% or 0.05%. While these to the small sample size of 20 people. Bockstael et al. [76] estimates are obviously very imprecise, they suggest that found a statistically significant link between annoyance and if ‘The Hum’ is responsible for any wind turbine health their measure of amplitude modulation. Ioannidou et al. [77] effects, population-wide epidemiology studies may not be found a statistically significant relationship between annoy - sufficiently sensitive to detect them. Rather, approaches that ance and the amplitude modulation depth of wind turbine identify outliers, clusters or more sophisticated forms of fre- noise. Yokoyama et al. [78] showed that amplitude modu- quentist statistics will need to be employed, as they are more lation of wind turbine noise became noticeable when the appropriate to identifying and describing low prevalence modulation depth exceeded 2 dB. events and low disease rates. Relevant to this, there are two The Institute of Acoustics (IoA) in the UK [79] has con- current NHMRC funded projects examining wind turbine ducted an extensive study into the best way to objectively noise effects on sleep which intend to increase the capacity measure amplitude modulation of wind turbine noise. The to identify possible underlying dysfunctions or sensitivities IoA looked at time-series methods, frequency-domain meth- by selecting noise-sensitive people. ods, and hybrid methods. They have recently recommended the use of a relatively complex hybrid method. This is quite a complicated procedure which could possibly result in imple- 8 Amplitude Modulation mentation differences between users. Therefore, the IoA has issued open-source Python software which carries out this Psychoacoustic studies have generally shown that sound with procedure in an accepted and consistent manner. varying temporal or frequency characteristics is more notice- Large [80] has compared the three initial amplitude able and more annoying than constant ‘steady-state’ noise. modulation rating methods proposed by the IoA with the 1 3 Acoustics Australia (2020) 48:181–197 189 annoyance ratings of 6 samples of wind turbine amplitude when rating sound signals because they are usually found modulation (AM) made by 336 people. She noted that the to be more subjectively disturbing than broadband sound AM rating methods ‘generally followed the shape of the at the same level. Usually, the approach is to add a positive annoyance ratings’ but that the range of the AM ratings penalty to the measured sound level, rather than reduce the was much greater than the range of the annoyance ratings. limit for sound containing tones. For wind farm noise, it is Hence some caution is needed, but the current IoA ampli- necessary to determine both the best scheme or approach tude modulation rating method is the best candidate for trial to measure tonality and where it should be measured. in Australia. It should be noted that none of the AM rating In terms of the measurement location, it is possible systems so far proposed include the possible effect of basilar to measure tonality near the turbines themselves, at the membrane biasing by the blade-passing tone and its harmon- receiver, or somewhere in between. Clearly, it is particu- ics [12]. Hansen et al. [81] have shown that the IoA method larly relevant at the receiver, and a measurement near to may need to be modie fi d in some circumstances, particularly the turbine is less critical because a sound source that is when the amplitude modulation is of a tone below 50 Hz. tonal near to the source, will not necessarily result in tonal The IoA have deliberately avoided specifying how their noise at the more distant receiver, where the sound is com- rating scheme should be used for rating the noise output bined with the ambient sound local to the receiver, which of wind turbines. Perkins et al. [82–84] have proposed that can significantly mask the tonal elements. Nevertheless, there be no penalty for an amplitude modulation rating the presence of tonality in the source signal is easier to which is less than 3 dB. For amplitude modulation ratings measure near the source because of the better signal to between 3–10 dB, the penalty increases linearly from a 3 dB noise ratio. One approach that has been suggested is to penalty at 3 dB AM depth, to 5 dB penalty at 10 dB AM make a measurement near the turbines as an ‘exclusion depth. Above 10 dB AM, the penalty is fixed at 5 dB. This test’, since, if the sound near the turbines is not tonal, penalty is added to the measured L values and is in addi- then it is unlikely to be tonal at the receiver. More intru- A90 tion to any tonal penalty. Perkins et al. [82] have observed sive tests at the receiver would therefore not be warranted. that ‘AM generates the greatest adverse impact during night- However, if the wind turbine sound did prove to be tonal time or early morning periods’. Because ETSU-R-97 [4] rec- near the turbines, this could be used to suggest what tonal ommends a higher night time wind turbine noise level limit frequency should be searched for near the receiver (and, if for England, Perkins et al. [82] recommend that the same tonal frequencies are measured at the receiver, what tonal limit for AM for England be applied all the times by adding frequencies could be excluded from being generated by the difference between the night time limit and the day time the wind turbines). limit to the AM penalty. This implies that they believe that If measurements of tonality are made only at the receiver, the ETSU-R-97 higher night-time wind turbine noise level and not in conjunction with a measurement made near the limit does not make sense. There has recently been further turbine, then it can be difficult to discriminate tonality from debate about appropriate penalties for amplitude modula- the wind turbines from ambient noise such as Aeolian noise tion [85]. emissions from wire fences, etc. One approach is to limit The draft New South Wales planning guidelines [86] measurements to the downwind condition. Another possibil- impose a penalty of 5 dB when the amplitude modulation ity is to make measurements only at night when the ambi- depth is greater than 4 dB. However, their maximum penalty ent noise is likely to be quieter. A problem with making is 5 dB, so that where more than one special audible charac- downwind measurements of tonality, is that the tonality can teristic penalty potentially applies, only one of the penalties sometimes only be audible to the side and upwind of the is added to the measured sound level. turbine [87]. The committee recommends that the United Kingdom In terms of the best approach to measuring and assessing Institute of Acoustics objective measurement method of tonality, it is usually helpful to conduct a less complicated measuring amplitude modulation and the WSP Parsons subjective screening test prior to making objective measure- Brinckerhoff method of penalising amplitude modulation ments. This is usually undertaken by an acoustic engineer be trialled in Australia. or other qualified person simply listening for the potential of tonality in wind farm sound or site recordings. A poten- tial problem with this approach is that tonality sometimes 9 Tonality only occurs for a narrow range of wind speeds and only for certain directions from the wind turbine and at certain times Tonality is the difference between the tone level and the [87]. Thus, having the expert listener make a judgement at level of the masking noise in the critical band around the the right time may be difficult. Having the affected person tone. Tonal elements are particularly salient, and poten- make a recording when they hear tonality may overcome tially annoying. It is common to penalise tonal sounds this problem. 1 3 190 Acoustics Australia (2020) 48:181–197 If the potential for tonality is detected, then further objec- At the Te Rere Hau review, it was argued that if 10% of tive measurements of tonality can be made in accordance measurements within a 1 m/s wide wind speed bin were with Annex C of ISO 1996-2:2007 [88]. This method is tonal, then the penalty should be applied to the wind- based on the Joint Nordic Method—Version 2 [89]. It is a speed bin. This approach requires bin analysis [95, 96], tonal audibility method, based on narrowband analysis. It rather than polynomial regression. This approach was sug- requires considerable signal processing and results in the gested because it would not overly penalise very infrequent calculation of tonal audibility and an adjustment penalty occurrence of Special Acoustic Characteristics (SACs) but between 0 and 6 dB. would apply an appropriate penalty to ‘encourage miti- However, because this reference method is complicated, gation’ where SACs occur with reasonable regularity. A ISO 1996-2:2007 [88] also contains a simplified method in similar 10% threshold approach to applying the SACs pen- Annex D. If the time-averaged sound pressure level in a one- alty has been adopted in New South Wales and Queensland third octave band exceeds the time-averaged sound pressure in Australia, and in the United Kingdom. However, this levels in both the adjacent two one-third octave bands by a approach needs some refinement because it could result level difference, a penalty, which is usually 5 dB, is applied. in a discontinuity in the compliance assessment (that is, The suggested level differences are: a hard switch from compliant to non-compliant) near the 10% limit. 15 dB in the low-frequency one-third-octave bands (25– Nevertheless, there is concern that if only a small per- 125 Hz), centage of the measured 10-min sound levels are penalized 8 dB in middle-frequency bands (160–400 Hz), for tonality, the effect of these penalized sound levels on 5 dB in high-frequency bands (500–10,000 Hz). the regression curve between the sound levels and the wind speeds, which is required by the NZ Standard NZS6808 to This simplified method can fail to identify low frequency determine the sound level which is regulated, may not be audible tones because of the tone’s side bands if the tone is significant. However, NZS6808-2010 [93] allows the sound substantially amplitude modulated [90]. levels measured over each 10 min period to be separated (Note: These methods have been updated in Annex J of into a group of sound level measurements with acceptable ISO/PAS 20065:2016 [91] and Annex K in ISO1996-2:2017 tonality and a group of sound level measurements with unac- [92]. Also, there is an alternative tonality method in ETSU- ceptable tonality. These two different groups of sound level R-97 [4].) measurements can be analysed separately. This allows the If a sound is identified as tonal, then it becomes neces- penalised periods to affect the regression between the meas- sary to assess how much ‘tonality’ is unacceptable and how ured sound levels and the wind speed when there is unac- the penalty should be applied to the 10-min L wind farm ceptable tonality. A90 sound level measurements. NZS 6806:2010 [93] implies that Several recent studies illustrate the complexities of inves- if tonality is detected, then the penalty should be applied tigation of the potential for tonality to influence perception to each 10 min L measurement, and that each penalised of wind turbine noise and the annoyance related to it. Søn- A90 measurement should then be included in the regression dergaard and Pedersen [97] noted the technical difficulties analysis. If these modified measurements are sufficient to in reconciling objective analysis of sound characteristics affect this regression, then the tonality effect is considered with subjective listening tests, pointing out for measure- to be ‘influential’. ments conducted over lengthy periods, short periods of high The NZ Standard does not provide guidance regarding tonality may not be detected. Yokoyama et al. [98] examined how much of the 10-min measurement can exhibit tonality methods to assess the effect of tonal components on subjec- in order to necessitate applying the penalty. For example, tive perception of noise, both physically (perception) and should the entire 10-min measurement exhibit tonality in psycho-acoustically (annoyance), demonstrating an influ- order to apply the penalty, or should the penalty apply if ence of tonality on both aspects, but with considerable vari- only part of the measurement is tonal? In practice, there ability in the response between individuals. Oliva et al. [99] is considerable variability, and it would be unusual for an argue against using fixed penalty values for tonal sound, entire 10-min noise measurement period to exhibit objec- suggesting, based on their assessment, that these penalties tively measured tonality. For the Te Rere Hau review [94] should vary with tonal frequency, tonal audibility and overall in New Zealand, it was accepted that if 2 min of the period level. exhibited measurable tonality, then the tonal penalty should Further work is required. The committee recommends apply to the whole period’s sample. If more than one tone that detailed attention now be given to the potential for tonal- in one period produces a penalty, it was decided that only ity to influence perception of wind turbine noise and annoy - one penalty (the greatest of them) should be applied to the ance related to it. This should include financial support for period. studies of the phenomenon and its behavioural implications. 1 3 Acoustics Australia (2020) 48:181–197 191 device itself, and only store or transmit the output of the 10 Wind Farm Sound Measurement analysis rather than raw audio signals. and Analysis The primary issue with any unattended sound monitoring and automated assessment is the potential for ‘false-positive’ The consideration of automated, unattended long-term sound level exceedances from unrelated local noise sources, measurement of wind farm sound is specifically raised in rather than the subject sound source (wind turbines in this the Terms of Reference for the Committee and was sug- case). One approach to limiting ‘false positive’ noise level gested at the original Australian Senate hearing into wind exceedance from automated unattended sound monitoring turbine noise. Sound measurement, and particularly auto- systems is to use directional microphone systems that limit mated unattended noise monitoring seems to be seen as a the noise received from areas other than in the direction of common solution to wind farm problems and the manage- the wind farm. The Australian developed ‘Barn Owl’ direc- ment of wind farm noise. However, there are many practi- tional microphone system has been used successfully for this cal issues with these types of sound measurement systems purpose around open cut mines. A similar cross-correlated particularly related to the use of precision microphones microphone array has also occasionally been used for spe- in inhospitable measurement environments, ongoing cali- cific wind farm noise measurements in the USA. Unfortu- bration, and the use of signal processing to automatically nately, such systems typically use additional microphones positively identify particular sound sources contributing and complex signal processing and further complicate any to the measured level at the sound level meter. automated unattended noise measurement system. Nevertheless, within the industry, there has been a move There are real practical issues with putting microphones towards conducting greater frequency analysis of wind tur- outside in the field: they are calibrated, sensitive devices. bine sound in addition to A-weighted sound level measure- There are ways to reduce these practical issues, but they are ments, and to adopt real time telemetry and real time audio expensive. Some of these issues are discussed in detail in the recordings. It is apparent that in future, as these technolo- committee’s paper [12] in the context of the measurement of gies mature, it should be possible to use real-time wind IS/LF energy from wind turbines. This is an area identified turbine sound measurements to actively control and man- as a potential target for the investment of research funding. age wind farms in order to satisfy sound level limits. In Since wind farms are necessarily located in windy areas, particular, all the relevant operating data of wind turbines there is a need to adequately protect microphones from wind are now routinely recorded using the Supervisory Control noise while not affecting their ability to accurately meas- And Data Acquisition (SCADA) system in order to opti- ure the wind farm noise. This typically requires the use of mise wind farm performance and manage and undertake special microphone wind shields incorporating a complex preventative maintenance. (SCADA is a system of soft- arrangement of inner and outer microphone wind screens. ware and hardware which allows the control and monitor- Protection against wind noise is easier if infrasound does ing of industrial processes at local or remote locations and not need to be measured and measurements only need to be the processing of data in real time. SCADA is widely used made in the audible frequency range. in the wind turbine industry.) It is therefore an extension of There are also practical and legal issues relating to the these existing systems to record sound measurement and placement of any microphone measurement system. For analysis data with the wind farm’s SCADA system and example, it is sometimes necessary to rent space in which to potentially to use this data to control the wind turbines. place the microphone. This typically requires a large volume It would be helpful if the wind farm industry were more of legal work to write agreements which ensure appropriate willing to share this SCADA data with researchers and access to data while restricting distribution of sensitive or other stakeholders. It is reported that sharing of such data commercial-in-confidence data. For instance, if a monitoring rarely occurs in Australia. While some of this data is com- system is placed on stakeholder land, then the stakeholder mercially sensitive, it should be possible to draft suitable may demand access to data which the wind farm operator is confidentiality agreements to allow this sharing to occur. unwilling to disclose. It is also important to note that there remain some The committee recommends that wind farm operators be potential legal issues in relation to the ongoing recording encouraged to continuously monitor wind turbine sound at of sound related to people’s privacy where sounds gener- some sensitive locations and be encouraged to incorporate ated by people may be recorded. Such recordings could these sound measurements as part of their SCADA sys- potentially breach various Australian States’ Listening tems. This sound data should be monitored by signal pro- Devices Acts when using long term audio recordings, and cessing systems to detect unusual sounds such as tonality further legal advice is required. One response may be to and excessive amplitude modulation. The Australian Gov- undertake the analysis of the sound at the measurement ernment should consider investing in the development of such technology so that the resulting Australian IP could be 1 3 192 Acoustics Australia (2020) 48:181–197 incorporated internationally as a ‘best in class’ mechanism It examines the ways that these effects can be assessed and of monitoring. mitigated. In so doing it provides an objective basis for harmonisation across Australia of provisions for siting and monitoring of wind turbines, which currently vary from state 11 Management Strategies to state, contributing to contention and potential inequities between Australians, depending on their place of residence. It is essential to ensure that wind turbine audible noise limits This paper shows that if rounding is removed, the outdoor are implemented and observed. These are needed to ensure wind turbine sound limits recommended by a recent World that: (a) the noise source is engineered and maintained to Health Organization report are the same as those recom- acceptable standards that limit noise generation and exclude mended for use in Australia by this paper. These limits are abnormal noises; and (b) that suitable setbacks are provided derived by determining the wind turbine level at which 10% to allow attenuation of sound emanating from the source of people are highly annoyed with wind turbines. Annoy- to acceptable, near imperceptible levels beyond this set- ance is used to set these wind turbine noise limits because back distance. For the small percentage of people affected the level of annoyance with wind turbines is the only effect by wind turbine noise [100], despite such provisions, other which consistently correlated with wind turbine noise sound strategies must also be considered. While one solution would level. It should be noted that this annoyance may not only be to assist these people to move away from wind turbine be due to wind turbine noise. Wind turbine noise level may locations, this may not always be possible. only be a proxy for distance from the wind turbines. On the Leventhall et  al. [101, 102] have used psychotherapy other hand, this paper also surveys possible perceptual and techniques such as cognitive behaviour therapy to help physiological effects of wind turbine noise. The paper also sufferers of low frequency noise cope with the noise. This looks at wind farm sound measurement and analysis includ- work was supported by the United Kingdom Department ing tonality and amplitude modulation, annoyance attributed for Environment, Food and Rural Affairs (DEFRA). These to low frequency noise, low frequency noise limits and man- psychotherapy techniques may be of assistance to people agement strategies to reduce annoyance with wind turbines. suffering from annoyance from wind turbine noise. Unfortu- In summary, the committee suggests that ‘annoyance’ is nately, these techniques appear to work best when the source the primary measure with which to set wind turbine noise of the noise is unknown, which is often the case with low limits and that the appropriate limit is one that ensures no frequency noise problems like “The Hum” as indicated in more than 10% of the population would be highly annoyed Sect. 6. With wind turbine noise, the source of the noise is when exposed to it. This threshold appears to be between well known. However, given that reported problems with 34–40 dB L outside the residence, with a mean Aeq (10 min) wind turbine noise can in some cases be accounted for by value of 37 dB L [3] and the committee urges har- Aeq (10 min) annoyance and other psychological effects, then psychother - monisation of state-by state guidelines around this standard. apy techniques may be appropriate form of management, The perceptual and physiological effects, both known and although they are unlikely to be effective for all sufferers. suspected, of wind turbine noise justify such an effort. Masking low pitched sound with low frequency brown and Open Access This article is licensed under a Creative Commons Attri- black noise is another therapeutic technique, which van den bution 4.0 International License, which permits use, sharing, adapta- Berg and de Boer [103] found to be helpful for about half tion, distribution and reproduction in any medium or format, as long the people they studied who are annoyed by it. as you give appropriate credit to the original author(s) and the source, The fact that some complaints about wind turbines occur provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are before wind farms start operating means that sensitive included in the article’s Creative Commons licence, unless indicated treatment of residents during the planning and construc- otherwise in a credit line to the material. If material is not included in tion phases is essential. Distribution of financial benefits to the article’s Creative Commons licence and your intended use is not effected residents will also help once the wind farm starts permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a operating. Rapid response to any problems reported by resi- copy of this licence, visit http://creativ ecommons .or g/licenses/b y/4.0/. dents is necessary. 12 Conclusions Appendix: The Statistical Power of Wind Turbine Noise Studies This paper provides a review of important aspects of the real and potential impacts of wind turbines on human well- Annoyance with wind turbines is the only of effect of wind being. It considers wind turbine noise and its relationship turbines on their neighbouring populations which has been to annoyance, sleep disturbance, quality of life and health. consistently discovered. This appendix investigates why 1 3 Acoustics Australia (2020) 48:181–197 193 other effects such as diseases caused by wind turbines have not been consistently found. An important point requiring discussion is the statistical sensitivity of any study and its capacity to detect the presence of an effect within a popula- tion. This is generally referred to as the statistical power of a population sampling study and quantifies the capacity to measure an experimental effect and/or to determine the proportion of the underlying population that show such an effect. If a population is assumed to be normally distributed with respect to a feature, then only a particular fraction of that population is likely to display such sensitivity above a cer- tain threshold. In the case of possible health effects of wind turbines, the relatively infrequent reports of ill health effects suggest that the sensitive proportion of the population is quite low [100]. The capacity to detect such sensitivity using Fig. 1 Percentage of experiments for which the occurrence of the dis- a population sampling approach will be dependent on the ease is zero. The disease probability is 0.1% and the sensitivity and underlying proportion in the population that display such a specificity are both 1.0 sensitivity and the number of samples taken from the popu- lation. For the Health Canada sleep disturbance study, the than 5% chance that the test will provide a type II error (i.e. smallest detectable percentage of people whose sleep quality incorrectly retain a false null hypothesis). In this simulation was worsened by increased wind turbine noise levels was there was a disease (0.1% rate) and the black bars represent estimated to be 7%. Since the Health Canada study did not the percentage of tests that would return P(disease) = 0, i.e. find any significant effects other than annoyance, the number a type II error of people suffering from disease due to exposure to wind This indicates that, of the many population studies of the turbine noise is likely to be substantially less than 7%. For effects wind turbines on the population where the focus has two relatively common clinical conditions of the inner ear, been on random sampling, the numbers of samples (gener- it is estimated that 0.2% of the population suffer Meniere’s ally of the order 10 ) are well below the numbers that would disease while recent estimates of superior semicircular canal be required to reliably detect the other relatively common dehiscence are around 0.1% of the population. In the absence inner ear conditions (order 10 samples). In the absence of of a known prevalence in the neighbouring population of any other data, the disease prevalence is estimated from the diseases caused by wind turbines, the authors have chosen to prevalence of superior semicircular canal dehiscence (SCD: use 0.1% of the neighbouring population based on the esti- 0.1%). A systematic analysis of health practitioner records mated prevalence of superior semicircular canal dehiscence as a percentage of the total exposed population in potentially to demonstrate the difficulty of detecting effects with low affected regions might provide a more grounded indication levels of prevalence in the population. The authors do not of the likely fraction of the population that may be suscepti- imply that 0.1% is the actual percentage of the population ble to wind turbine sound (presuming that is based on some suffering from diseases caused by wind turbines, since the similar inner ear dysfunction). actual figure is currently unknown. A second and critical issue in the analysis of such low The committee has used a simple model of statisti- prevalence occurrences is how they are identified and cur - cal power to examine the impact of sample size using the rently treated in the analysis of the population data. It is assumptions that (1) the prevalence of the disease is similar statistically impossible for a small number of low preva- to that of semicircular canal dehiscence (i.e. 0.1%) and (2) lence samples to have any meaningful impact on summary for simplicity we have chosen the best case scenario where statistics (the mean, median or mode) of a population. The the sensitivity of the test for the disease is perfect (100% meta-analyses of previous studies of potential health effects detection and no false alarms). of wind turbines have also used more traditional summary Figure 1 plots the percentage of studies that would fail to and linear regression models. More appropriate would be the detect the disease with an actual 0.1% prevalence with sam- identification of people who may potentially be more likely ple sizes ranging from 100 to 3200. The bottom dashed black to be affect by wind turbine noise for further examination, an line indicates 5%. The above model indicates that (1) for approach that is being pursued in the recent NHMRC funded sample sizes of 400 or less there is 70% to 90% chance that research projects. the test would fail to return a positive result; (2) a sample size of around 3200 samples is needed before there is a less 1 3 194 Acoustics Australia (2020) 48:181–197 noise annoyance. Appl. Acoust. 140, 288–295 (2018). https :// Because many of the symptoms claimed to be caused by doi.org/10.1016/j.apaco ust.2018.06.009 wind turbine noise are reasonably common in populations 4. ETSU-R-97.: The Assessment and Rating of Noise from Wind not exposed to wind turbine noise, it is even more difficult Farms, pp. 1–153. Department of Trade and Industry, London to detect statistically significant changes in the occurrence (1996) 5. World Health Organisation: Environmental Noise Guidelines of these symptoms in populations that are exposed to wind for the European Region. World Health Organisation Regional turbine noise. The Health Canada study [11] was designed Office for Europe, Copenhagen (2018) to be able to detect a relationship between a change in sleep 6. National Health and Medical Research Council.: NHMRC disturbance and wind turbine noise level. It was estimated Statement: Evidence on Wind Farms and Human Health, p. 1. National Health and Medical Research Council, Canberra that there would be 1120 survey responses and the stand- (2015) ard 95% confidence limits were to be used. This meant that 7. van den Berg, F.: Criteria for wind farm noise: Lmax and Lden. there was an 80% chance of being able to detect at least a Paper presented at the Euronoise 2008, Paris, June 29–July 4 7% difference in sleep disturbances in persons exposed to (2008) 8. Michaud, D.S., Keith, S.E., Feder, K., Voicescu, S.A., Marro, outdoor wind turbine noise of more than 40 dB(A) compared L., Than, J., Guay, M., Bower, T., Denning, A., Lavigne, E., to persons exposed to less than 40 dB(A) and only a 5% Whelan, C., Jannssen, S.A., Leroux, T., van den Berg, F.: Per- chance of detecting a difference where no difference actually sonal and situational variables associated with wind turbine existed [11, 104]. This statistical power calculation assumed noise annoyance. J. Acoust. Soc. Am. 139(3), 1455–1466 (2016). https ://doi.org/10.1121/1.49423 90 that the baseline prevalence for reported sleep disturbance 9. Michaud, D.S., Keith, S.E., Feder, K., Voicescu, S.A., Marro, in people exposed to outdoor wind turbine noise of less than L., Than, J., Guay, M., Bower, T., Denning, A., Lavigne, E., 40 dB(A) was between 7 and 10% and that 20% of the survey Whelan, C., Jannssen, S.A., Leroux, T., van den Berg, F.: population would be exposed to outdoor wind turbine noise Erratum: Personal and situational variables associated with wind turbine noise annoyance [J. Acoust. Soc. Am. 139(3), of more than 40 dB(A). It is probable that similar figures 1455–1466 (2016)]. J. Acoust. Soc. Am. 140(4), 2234 (2016). would apply to the detection of health effects. This means http://dx.doi.org/10.1121/1.49638 38 that if wind turbines cause health problems for less than 7% 10. Michaud, D.S., Feder, K., Keith, S.E., Voicescu, S.A., Marro, of the population, this effect is going to be very difficult, if L., Than, J., Guay, M., Denning, A., McGuire, D.A., Bower, T., Lavigne, E., Murray, B.J., Weiss, S.K., van den Berg, F.: Expo- not impossible, to rigorously detect using these sample sizes. sure to wind turbine noise: perceptual responses and reported Much larger sample sizes would need to be applied to detect health effects. J. Acoust. Soc. Am. 139(3), 1443–1454 (2016). low prevalence effects. https ://doi.org/10.1121/1.49423 91 A Danish study [105, 106] currently underway will 11. Michaud, D.S., Feder, K., Keith, S.E., Voicescu, S.A., Marro, L., Than, J., Guay, M., Denning, A., Murray, B.J., Weiss, S.K., address some of the problems raised in this section. It is Villeneuve, P.J., van den Berg, F., Bower, T.: Effects of wind a study of all Danes exposed to wind turbine noise since turbine noise on self-reported and objective measures of sleep. 1982. It is looking at the potential association of wind tur- Sleep 39(1), 97–109 (2016). https://doi.or g/10.5665/sleep.5326 bine noise with diabetes, cardiovascular diseases, perinatal 12. Carlile, S., Davy, J.L., Hillman, D., Burgemeister, K.: A review of the possible perceptual and physiological effects of birth factors and the use of medication for hypertension, wind turbine noise. Trends Hear. 22, 1–10 (2018). https ://doi. sleep problems and depression. It includes 553,066 dwell- org/10.1177/23312 16518 78955 1 ings and more than 1.3 million adult Danes. This study did 13. Council of Canadian Academies: Understanding the Evidence: not support an association between wind turbine noise and Wind Turbine Noise. The Expert Panel on Wind Turbine Noise and Human Health, Council of Canadian Academies, Ottawa redemption of antihypertension medication [107]. Poulsen (2015) et al. [108] did find an association between outdoor wind 14. Hansen, C.H., Hansen, K.L.: Recent advances in wind tur- turbine noise level and first redemption of sleep medication bine noise research. Acoustics 2, 172–207 (2020). https ://doi. or antidepressants by people aged 65 years or older. org/10.3390/acous tics2 01001 3 15. Knopper, L.D., Ollson, C.A., McCallum, L.C., Whitfield Aslund, M.L., Berger, R.G., Souweine, K., McDaniel, M.: Wind turbines and human health. Front. Public Health (2014). https ://doi.org/10.3389/fpubh .2014.00063 References 16. L’Agence nationale de sécurité sanitaire de l’alimentation, d.l.e.e.d.t.: Evaluation des effets sanitaires des basses fréquences sonores et infrasons dus aux parcs éoliens [Evalu- 1. Commonwealth of Australia.: Senate Select Committee on Wind ation of the health effects of low sound and infrasonic frequen- Turbines Final report, p. 350. Commonwealth of Australia, Can- cies due to wind farms]. In. L’Agence nationale de sécurité berra (2015) sanitaire de l’alimentation, de l’environnement et du travail, 2. Hübner, G., Pohl, J., Hoen, B., Firestone, J., Rand, J., Elliott, Maisons-Alfort, France (2017) D., Haac, R.: Monitoring annoyance and stress effects of wind 17. McCunney, R.J., Mundt, K.A., Colby, W.D., Dobie, R., Kaliski, turbines on nearby residents: a comparison of U.S. and Euro- K., Blais, M.: Wind turbines and health: a critical review of pean samples. Environ. Int. 132(105090), 1–9 (2019). https :// the scientific literature. J. Occup. Environ. Med. 56(11), e108– doi.org/10.1016/j.envin t.2019.10509 0 e130 (2014). https://doi.or g/10.1097/JOM.0000000000 00031 3 3. Davy, J.L., Burgemeister, K., Hillman, D.: Wind turbine sound limits: current status and recommendations based on mitigating 1 3 Acoustics Australia (2020) 48:181–197 195 18. National Health and Medical Research Council.: Information impacts of wind farm noise on sleep. Acoust. Aust. 46(1), Paper: Evidence on Wind Farms and Human Health, pp. 1–42. 87–97 (2018). https ://doi.org/10.1007/s4085 7-017-0120-9 National Health and Medical Research Council, Canberra (2015) 36. van den Berg, F.: Effects of sound on people. In: Bowdler, D., 19. Onakpoya, I.J., O’Sullivan, J., Thompson, M.J., Heneghan, C.J.: Leventhall, G. (eds.) Wind Turbine Noise, vol. 6, pp. 129–151. The effect of wind turbine noise on sleep and quality of life: a Multi-Science Publishing Co.Ltd, Brentwood (2011) systematic review and meta-analysis of observational studies. 37. Janssen, S., Vos, H., Eisses, A.R.: Hinder door geluid van Environ. Int. 82, 1–9 (2015). h t t p s : / / d o i . o r g / 1 0 . 1 0 1 6 / j . e nv i n windturbines-dosis-effectrelaties op basis van Nederlandse t.2015.04.014 en Zweedse gegevens (Annoyance from wind turbine sound- 20. Schmidt, J.H., Klokker, M.: Health effects related to wind turbine dose-effect relations based on Dutch and Swedish data-in noise exposure: a systematic review. PLoS ONE 9(12), e114183 Dutch) TNO-rapport 2008-D-R1051/B. In., vol. TNO-rapport (2014). https ://doi.org/10.1371/journ al.pone.01141 83 2008-D-R1051/B, pp. 1-29. TNO, Delft (2008) 21. van Kamp, I., van den Berg, F.: Health effects related to wind 38. Bakker, R.H., Pedersen, E., van den Berg, G.P., Stewart, turbine sound, including low-frequency sound and infrasound. R.E., Lok, W., Bouma, J.: Impact of wind turbine sound on Acoust. Aust. 46(1), 31–57 (2018). https: //doi.org/10.1007/s4085 annoyance, self-reported sleep disturbance and psychological 7-017-0115-6 distress. Sci. Total Environ. 425, 42–51 (2012). https ://doi. 22. Hansen, K.L., Hansen, C.H., Zajamšek, B.: Outdoor to indoor org/10.1016/j.scito tenv.2012.03.005 reduction of wind farm noise for rural residences. Build. Environ. 39. Pedersen, E.: Health aspects associated with wind turbine 94, 764–772 (2015) noise—results from three field studies. Noise Control Eng. J. 23. Marcillo, O., Arrowsmith, S., Blom, P., Jones, K.: On infrasound 59(1), 47–53 (2011). https ://doi.org/10.3397/1.35338 98 generated by wind farms and its propagation in low-altitude 40. Pedersen, E., Persson Waye, K.: Perception and annoyance due tropospheric waveguides. J. Geophys. Res. Atmos. 120(19), to wind turbine noise: a dose-response relationship. J. Acoust. 9855–9868 (2015). https ://doi.org/10.1002/2014J D0228 21 Soc. Am. 116(6), 3460–3470 (2004) 24. Pedersen, S., Møller, H., Waye, K.P.: Indoor measurements of 41. Pedersen, E., van den Berg, F., Bakker, R., Bouma, J.: noise at low frequencies-problems and solutions. J. Low Freq. Response to noise from modern wind farms in The Nether- Noise Vib. Act. Control 26(4), 249–270 (2007) lands. J. Acoust. Soc. Am. 126, 634–643 (2009). https ://doi. 25. Schomer, P.D., Erdreich, J., Pamidighantam, P.K., Boyle, J.H.: org/10.1121/1.31602 93 A theory to explain some physiological effects of the infrasonic 42. Pedersen, E., Persson Waye, K.: Wind turbine noise, annoy- emissions at some wind farm sites. J. Acoust. Soc. Am. 137(3), ance and self-reported health and well-being in different living 1356–1365 (2015). https ://doi.org/10.1121/1.49137 75 environments. Occup. Environ. Med. 64(7), 480–486 (2007) 26. Zajamšek, B., Hansen, K.L., Doolan, C.J., Hansen, C.H.: Char- 43. Feder, K., Michaud, D.S., Keith, S.E., Voicescu, S.A., Marro, acterisation of wind farm infrasound and low-frequency noise. L., Than, J., Guay, M., Denning, A., Bower, T., Lavigne, E., J. Sound Vib. 370, 176–190 (2016). https ://doi.org/10.1016/j. Whelan, C., van den Berg, F.: An assessment of quality of life jsv.2016.02.001 using the WHOQOL-BREF among participants living in the 27. Zorumski, W., Willshire Jr., W.: Downwind sound propagation in vicinity of wind turbines. Environ. Res. 142, 227–238 (2015). an atmospheric boundary layer. AIAA J. 27(5), 515–523 (1989). https ://doi.org/10.1016/j.envre s.2015.06.043 https ://doi.org/10.2514/3.10141 44. Mroczek, B., Banaś, J., Machowska-Szewczyk, M., Kurpas, D.: 28. Thorsson, P., Persson Waye, K., Smith, M., Ögren, M., Pedersen, Evaluation of quality of life of those living near a wind farm. E., Forssén, J.: Low-frequency outdoor indoor noise level differ - Int. J. Environ. Res. Public Health 12, 6066–6083 (2015). https ence for wind turbine assessment. J. Acoust. Soc. Am. 143(3), ://doi.org/10.3390/ijerp h1206 06066 206–211 (2018). https ://doi.org/10.1121/1.50270 18 45. Mroczek, B., Kurpas, D., Karakiewicz, B.: Influence of dis- 29. Hoffmeyer, D., Jakobsen, J.: Sound insulation of dwellings at low tances between places of residence and wind farms on the qual- frequencies. J. Low Freq. Noise Vib. Act. Control 29(1), 15–23 ity of life in near by areas. Ann. Agric. Environ. Med. 19(4), (2010) 692–696 (2012) 30. Salt, A.N., Hullar, T.E.: Responses of the ear to low frequency 46. Shepherd, D., McBride, D., Welch, D., Dirks, K.N., Hill, E.M., sounds, infrasound and wind turbines. Hear. Res. 268, 12–21 et al.: Evaluating the impact of wind turbine noise on health- (2010) related quality of life. Noise Health 13(54), 333 (2011) 31. Salt, A.N., Lichtenhan, J.T.: How does wind turbine noise affect 47. Leventhall, G., Pelmear, P., Benton, S.: A Review of Published people? Acoust. Today 10, 20–28 (2014) Research on Low Frequency Noise and Its Effects. Department 32. Dommes, E., Bauknecht, H., Scholz, G., Rothemund, Y., Hensel, for Environment, Food and Rural Affairs, London (2003) J., Klingebiel, R.: Auditory cortex stimulation by low-frequency 48. Moorhouse, A.T., Waddington, D.C., Adams, M.D.: Procedure tones—an fMRI study. Brain Res. 1304, 129–137 (2009). https for the assessment of low frequency noise complaints. Report ://doi.org/10.1016/j.brain res.2009.09.089 for Defra, NANR45 Revision 1. Acoustics Research Centre, 33. Weichenberger, M., Bauer, M., Kühler, R., Hensel, J., For- University of Salford (2011) lim, C.G., Ihlenfeld, A., Ittermann, B., Gallinat, J., Koch, S., 49. International Organization for Standardization: ISO 226:1987 Kühn, S.: Altered cortical and subcortical connectivity due to Normal Equal-Loudness Level Contours. International Organi- infrasound administered near the hearing threshold—evidence zation for Standardization, Geneva (1987) from fMRI. PLoS ONE 12(4), e0174420 (2017). https ://doi. 50. Dobie, R.: Robert Dobie’s letter regarding Salt and Lichten- org/10.1371/journ al.pone.01744 20 ham, Letter to the editor. Acoust. Today 10(2), 14 (2014) 34. Weichenberger, M., Kühler, R., Bauer, M., Hensel, J., Brühl, R., 51. Leventhall, G.: How the “mythology” of infrasound and low Ihlenfeld, A., Ittermann, B., Gallinat, J., Koch, S., Tilmmann, frequency noise related to wind turbines might have developed. S., Kühn, S.: Brief bursts of infrasound may improve cognitive Paper Presented at the First International Meeting on Wind function—an fMRI study. Hear. Res. 328, 87–93 (2015). https:// Turbine Noise: Perspectives for Control, Berlin, Germany, doi.org/10.1016/j.heare s.2015.08.001 17–18 October (2005) 35. Micic, G., Zajamsek, B., Lack, L., Hansen, K., Doolan, C., 52. Leventhall, G.: Infrasound from wind turbines—fact, fiction or Hansen, C., Vakulin, A., Lovato, N., Bruck, D., Chai-Coetzer, deception. Can. Acoust. 34(2), 29–36 (2006) C.L., Mercer, J., Catchside, P.: A review of the potential 1 3 196 Acoustics Australia (2020) 48:181–197 53. Leventhall, G.: Concerns about infrasound from wind turbines. 72. Mullins, J.H., Kelly, J.P.: The mystery of the Taos hum. Echoes Acoust. Today 9(3), 30–38 (2013) 5(3), 6 (1995) 54. Schomer, P.D.: Comments on recently published article, concerns 73. Vasudevan, R.N., Gordon, C.G.: Experimental study of annoy- about infrasound from wind turbines. Acoust. Today 9(4), 7–9 ance due to low frequency environmental noise. Appl. Acoust. (2013) 10, 57–69 (1977). https://doi.or g/10.1016/0003-682X(77)90007 55. Jakobsen, J.: Danish guidelines on environmental low frequency -X noise, infrasound and vibration. J. Low Freq. Noise Vib. Act. 74. Lee, S., Kim, K., Choi, W., Lee, S.: Annoyance caused by ampli- Control 20(3), 141–148 (2001). https ://doi.org/10.1260/2F026 tude modulation of wind turbine noise. Noise Control Eng. J. 30920 11493 091 59(1), 38–46 (2011). https ://doi.org/10.3397/1.35317 97 56. van den Berg, G.P., Passchier-Vermeer, W.: Assessment of low 75. von Hünerbein, S., King, A., Piper, B., Cand, M.: Wind Turbine frequency noise complaints. Paper Presented at the Internoise Amplitude Modulation: Research to Improve Understanding as 1999, Fort Lauderdale, 06–08 December 1999 to its Cause and Effect Work Package B(2): Development of an 57. Broner, N.: A simple outdoor criterion for assessment of low AM Dose-Response Relationship, pp. 140–265. University of frequency noise emission. Acoust. Aust. 39(1), 7–14 (2011) Salford, Acoustics Research Centre, Manchester (2013) 58. Hessler, G.F.: Proposed criteria in residential communities 76. Bockstael, A., Dekoninck, L., Can, A., Oldoni, D., De Coensel, for low-frequency noise emissions from industrial sources. B., Botteldooren, D.: Reduction of wind turbine noise annoy- Noise Control Eng. J. 52(4), 179–185 (2004). https ://doi. ance: an operational approach. Acta Acust. United Acust. 98, org/10.3397/1.28397 48 392–401 (2012). https ://doi.org/10.3813/AAA.91852 4 59. Broner, N., Leventhall, G.: Low frequency noise annoyance 77. Ioannidou, C., Santurette, S., Jeong, C.-H.: Effect of modulation assessment by low frequency noise rating (LFNR) curves. J. Low depth, frequency, and intermittence on wind turbine noise annoy- Freq. Noise Vib. 2, 20–28 (1983). https: //doi.org/10.1177/02630 ance. J. Acoust. Soc. Am. 139(3), 1241–1251 (2016). https://doi. 92383 00200 103org/10.1121/1.49445 70 60. Inukai, Y., Taya, H., Utsugi, A., Nagamur, N.: A new evaluation 78. Yokoyama, S., Sakamoto, S., Tachibana, H.: Study on the method for low frequency noise. Paper presented at the Internoise amplitude modulation of wind turbine noise: part 2- Auditory 90 experiments. Paper Presented at the Inter-noise 2013, Innsbruck, 61. Vercammen, M.L.S.: Setting limits for low frequency noise. Austria J. Low Freq. Noise Vib. 8, 105–109 (1989). https ://doi. 79. Institute of Acoustics United Kingdom.: A Method for Rat- org/10.1260/2F026 30920 11493 091 ing Amplitude Modulation in Wind Turbine Noise. Institute of 62. Vercammen, M.L.S.: Low frequency noise limits. J. Low Freq. Acoustics United Kingdom (2016) Noise Vib. 11, 7–13 (1992). https:// doi.org/10.1177/2F026309 23 80. Large, S.: A quantitative and qualitative review of amplitude 92011 00102 modulated noise from wind energy development. Paper Presented 63. Evans, T., Cooper, J., Lenchine, V.: Low frequency noise near at the Inter-noise, Hamburg (2016) wind farms and in other environments. Environment Protection 81. Hansen, K.L., Nguyen, P., Zajamsek, B., Catcheside, P., Hansen, Authority, South Australia and Resonate Acoustics, Adelaide C.H.: Prevalence of wind farm amplitude modulation at long- (2013) range residential locations. J. Sound Vib. 455, 136–149 (2019). 64. Hansen, K., Zajamsek, B., Hansen, C.: Identification of low https ://doi.org/10.1016/j.jsv.2019.05.008 frequency wind turbine noise using secondary windscreens of 82. Perkins, R.A., Lotinga, M.J., Berry, B., Grimwood, C.J., Stans- various geometries. Noise Control Eng. J. 62(2), 69–82 (2014) feld, S.A.: A review of research into the human response to 65. Hansen, K., Zajamsek, B., Hansen, C.: Comparison of the noise amplitude-modulated wind turbine noise and development of levels measured in the vicinity of a wind farm for shutdown and a planning control method. Paper Presented at the Inter-noise, operational conditions. In: INTER-NOISE and NOISE-CON Hamburg (2016) Congress and Conference Proceedings 2014, vol. 2, pp. 5192– 83. Wright, J., Perkins, R.A.: Wind Turbine AM Review Phase 1 5202. Institute of Noise Control Engineering Report. WSP Parsons Brinckerhoff, Bristol (2015) 66. ANSI/ASA.: ANSI/ASA S12.9-2016/Part 7 American National 84. Lotinga, M.J., Perkins, R.A.: Wind Turbine AM Review Phase 2 Standard Quantities and Procedures for Description and Meas- Report. WSP Parsons Brinckerhoff, Bristol (2016) urement of Environmental Sound, Part 7: Measurement of Low- 85. Bowdler, D., Cand, M., Hayes, M., Irvine, G.: Wind turbine noise frequency Noise and Infrasound Outdoors in the Presence of amplitude modulation penalty considerations. Proc. Inst. Acoust. Wind and Indoors in Occupied Spaces. ANSI/ASA (2016) 40(1), 253–261 (2018) 67. Crichton, F., Dodd, G., Schmid, G., Gamble, G., Cundy, T., 86. Department of Planning and Infrastructure.: Draft NSW Planning Petrie, K.J.: The power of positive and negative expectations to Guidelines: Wind Farms, pp. 1–55. Department of Planning and influence reported symptoms and mood during exposure to wind Infrastructure, State of New South Wales, Sydney (2011) farm sound. Health Psychol. 33(12), 1588–1592 (2014). https :// 87. Cooper, J., Evans, T., Petersen, D.: Method for assessing tonal- doi.org/10.1037/hea00 00037 ity at residences near wind farms. Int. J. Aeroacoust. 14(5–6), 68. Crichton, F., Dodd, G., Schmid, G., Gamble, G., Petrie, K.J.: Can 903–908 (2015) expectations produce symptoms from infrasound associated with 88. International Organization for Standardization: Acoustics- wind turbines? Health Psychol. 33(4), 360–364 (2014). https :// Description, Measurement and Assessment of Environmental doi.org/10.1037/a0031 760 Noise-Part 2: Determination of Environmental Noise Levels. 69. Tonin, R., Brett, J., Colagiuri, B.: The effect of infrasound and International Organization for Standardization, Geneva (2007) negative expectations to adverse pathological symptoms from 89. Pedersen, T.H., Søndergaard, M., B., A.: Objective Method for wind farms. J. Low Freq. Noise Vib. Act. Control 35(1), 77–90 Assessing the Audibility of Tones in Noise, Joint Nordic Method- (2016). https ://doi.org/10.1177/02630 92316 62825 7 Version 2, Report AV 1952/99. DELTA Acoustics & Vibration, 70. Cowan, J.P.: The Kokomo Hum Investigation. Acentech Incor- Hørsholm, Denmark (1999) porated, Moulton (2003) 90. Hansen, C.H., Doolan, C.J., Hansen, K.L.: Wind Farm Noise: 71. Leventhall, G.: Low frequency noise and annoyance. Noise Measurement, Assessment, and Control. Wiley, Chichester Health 6(23), 59–72 (2004) (2017) 1 3 Acoustics Australia (2020) 48:181–197 197 91. International Organization for Standardization: ISO/PAS 102. Leventhall, G., Robertson, D., Benton, S., Leventhall, L.: Help- 20065:2016 Acoustics—Objective Method for Assessing the ing sufferers to cope with noise using distance learning cognitive Audibility of Tones in Noise—Engineering Method. Interna- behaviour therapy. J. Low Freq. Noise Vib. Act. Control 31(3), tional Organization for Standardization, Geneva (2016) 193–203 (2012). https://doi.or g/10.1260/2F0263-0923.31.3.193 92. International Organization for Standardization: ISO 1996–2:2017 103. van den Berg, F., de Boer, K.: The effect of brown and black Acoustics—Description, Measurement and Assessment of Envi- noise on persons suffering from a low frequency sound. Paper ronmental Noise—Part 2: Determination of Sound Pressure Presented at the International Congress on Acoustics 2019, Levels. International Organization for Standardization, Geneva Aachen, Germany (2019) (2017) 104. Voicescu, S.A., Michaud, D.S., Feder, K., Marro, L., Than, J., 93. Standards New Zealand.: NZS 6808:2010 Acoustics-Wind Farm Guay, M., Denning, A., Bower, T., van den Berg, F., Broner, Noise, pp. 1–43. Standards New Zealand (2010) N., Lavigne, E.: Estimating annoyance to calculated wind tur- 94. Rogers, P., Sweetman, G., Burgemeister, K.: Decision of Hearing bine shadow flicker is improved when variables associated with Commissioners on a Review of Resource Consent Conditions wind turbine noise exposure are considered. J. Acoust. Soc. Am. Relating to the Te Rere Hau Wind Farm Operated by New Zea- 139(3), 1480–1492 (2016). https ://doi.org/10.1121/1.49424 03 land Windfarms Limited, vol. PGR-120496-5-208-V1, p. 151. 105. Poulsen, A.H., Sørensen, M.: Wind turbine noise and health, a Palmerston North City Council (2017) nationwide prospective study in Denmark. Paper Presented at the 95. Smith, M., Chiles, S.: Analysis techniques for wind farm sound Inter-noise 2016, Hamburg, Germany, 21–24 August (2016) level measurements. Acoust. Aust. 40(1), 51–56 (2012) 106. Backalacz, C., Søndergaard, L.S., Laursen, J.E.: “Big noise data” 96. South Australian Environment Protection Authority: Wind Farms for wind turbines. Paper Presented at the Inter-noise 2016, Ham- Environmental Noise Guidelines 2019—Draft for Consultation. burg, Germany, 21–24 August (2016) South Australian Environment Protection Authority, Adelaide 107. Poulsen, A.H., Raaschou-Nielsen, O., Peña, A., Hahmann, A.N., (2019) Nordsborg, R.B., Ketzel, M., Brandt, J., Mette Sørensen, M.: 97. Søndergaard, L.S., Pedersen, T.H.: Tonality in wind turbine Long-term exposure to wind turbine noise and redemption of noise. IEC 61400-11 ver. 2.1 and 3.0 and the Danish/joint nor- antihypertensive medication: a nationwide cohort study. Envi- dic method compared with listening tests. Paper Presented at the ron. Int. 121, 207–215 (2018). https ://doi.org/10.1016/j.envin Wind Turbine Noise (2013) t.2018.08.054 98. Yokoyama, S., Kobayashi, T., Tachibana, H.: Perception of tonal 108. Poulsen, A.H., Raaschou-Nielsen, O., Peña, A., Hahmann, A.N., components contained in wind turbine noise. Paper Presented at Nordsborg, R.B., Ketzel, M., Brandt, J., Sørensen, M.: Impact the Inter-noise 2016, Hamburg (2016) of long-term exposure to wind turbine noise on redemption of 99. Oliva, D., Hongisto, V., Haapakangas, A.: Annoyance of low- sleep medication and antidepressants: a nationwide cohort study. level tonal sounds—factors ae ff cting the penalty. Build. Environ. Environ. Health Perspect. 127(3), 037005 (2019). https ://doi. 123, 404–414 (2017)org/10.1289/EHP39 09 100. Office of the National Wind Farm Commissioner: 2018 Annual Report by the Office of the National Wind Farm Commissioner Publisher’s Note Springer Nature remains neutral with regard to to the Parliament of Australia. Office of the National Wind Farm jurisdictional claims in published maps and institutional affiliations. Commissioner, Melbourne (2019) 101. Leventhall, G., Benton, S., Robertson, D.: Coping strategies for low frequency noise. J. Low Freq. Noise Vib. Act. Control 27(1), 35–52 (2008). https://doi.or g/10.1260/2F02630920 87844 25460 1 3

Journal

Acoustics AustraliaSpringer Journals

Published: Aug 27, 2020

There are no references for this article.