PROCEEDINGS of the23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

How do audio and visual characteristics of wind turbines contributeto noise annoyance?
Beat SCHÄFFER1; Reto PIEREN1; Ulrike WISSEN HAYEK2;
Nadine BIVER2, Adrienne GRÊT-REGAMEY2
1

Empa, Swiss Federal Laboratories for Materials Science and Technology, Switzerland
2ETH Zurich, Institute for Spatial and Landscape Development, Switzerland

ABSTRACTWind farms often evoke strong annoyance reactions in residents. Literature suggests that both acousticalcharacteristics and the visibility of wind turbines may contribute to noise annoyance. However, studies on themutual audio-visual effects on annoyance are still rare. The objective of this study was to investigate theshort-term noise annoyance reactions to different wind turbine noise situations in a controlled laboratory
experiment. A set of 24 audio-visual rural scenarios containing a single wind turbine was synthesized, i.e.,visualized and auralized. Combined with the full factorial experimental design, this allowed separating theindividual contributions of the following variables to noise annoyance: distance to the wind turbine, periodicamplitude modulation of the sound (with, without) and visual setting (landscape with or without windturbine; grey background). The experiment revealed that both visual and acoustical characteristics strongly
affect noise annoyance. Annoyance increased with periodic amplitude modulation and/or decreased when alandscape was visible. For the latter case, the visibility of a wind turbine increased annoyance. While theacoustical effects could be reliably assessed, the visual effects were less straightforward to reveal, as they areafflicted with carryover effects. The presentation order of audio-visual stimuli was therefore found to be
crucial for study outcomes.
Keywords: Wind turbine noise, Noise annoyance, Audio-visual effects

1. INTRODUCTIONWind farms often evoke strong annoyance reactions in residents at comparably low sound pressurelevels, more so than other sources such as transportation noise (1). The visual as well as acoustical
impacts of wind farms have therefore recently been much discussed. Literature suggests that bothacoustical characteristics (e.g., (2)) and the visibility of wind turbines (e.g., (3)) may contribute tonoise annoyance. However, studies on the mutual audio-visual effects on annoyance are still relativelyrare. Only in recent years, such studies were conducted (e.g., (4, 5)). They confirmed that indeed bothacoustical characteristics and visual impacts of wind farms contribute to (noise) annoyance.
When performing experiments on audio-visual effects, one should also consider the presentation
order of the stimuli. The latter may strongly affect the results due to two serial position effects: simple
order effects and/or differential carryover effects (6). While simple order effects can be averaged out
by counterbalancing, carryover effects cannot. Here, other strategies such as sufficiently long timeintervals between presented stimuli need to be applied. To date, however, studies on audio-visualeffects did not systematically consider these two serial position effects.
The objective of this study therefore was to investigate the short-term noise annoyance reactions todifferent wind turbine (WT) noise situations in a controlled laboratory experiment, considering also
possible serial position effects.
This study has already been published in the journal “Landscape and Urban Planning”, and all study
details may be found there (7).

1beat.schaeffer@empa.ch1437

2. METHODS
A set of 24 audio-visual scenarios with a single WT was synthesized, i.e., visualized and auralized.
Combined with the full factorial design of the experiment, this allowed separating the contributions of
the following variables to noise annoyance: observer distance to the WT, periodic amplitude
modulation (AM) of the sound (no, with), and visual setting (landscape with WT, landscape without
WT, grey background) (Table 1). For the cases with landscape, the same rural, hilly landscape waschosen for both situations, with and without WT. For the case without landscape (which is a typicalsetting in classical psychoacoustic experiments with acoustical stimuli only), a grey background waschosen (Table 1).
Table 1 – Factorial design of the experiment with audio-visual wind turbine (WT) stimuli covering observer
distances to the WT of 100–600 m, two situations of periodic amplitude modulation (“no”, “with”), and threevisual settings. The table shows the resulting A-weighted equivalent continuous sound pressure levels (LAeq)
in dB per variable combination.
Visual setting
Distance

Landscape with WT

to WT [m]Landscape without WTGrey background

Amplitude Modulation
nowithnowith

nowith

100

48.6

49.4

48.6

49.4

48.6

49.4

200

43.6

44.6

43.6

44.6

43.6

44.6

350

38.2

39.2

38.2

39.2

38.2

39.2

600

33.0

34.0

33.0

34.0

33.0

34.0

The visualization was created using the game engine CRYENGINE (https://www.cryengine.com)
as described in (8). The auralization was done with the sound synthesis models described in (9, 10).
The resulting videos and audio data were time synchronized and linked as described in (8).
Forty-three subjects (22 females, 21 males) participated in the study. The laboratory experiments
were conducted in the "Mobile Visual-Acoustic Lab" (MVAL) (11) at the authors' institution ETH
Zurich. The experimental procedure largely followed the description in (2). In the experiments, thesubjects attentively watched and listened to the simulations and rated each stimulus after playback
regarding noise annoyance using the ICBEN 11-point scale (12).
A preliminary experiment to this study revealed that the visual (but not the acoustical) effects wereafflicted by differential carryover effects. Therefore, the three visual settings were presented in threeblocks in completely counterbalanced order, while the 8 acoustical situations per block were presented
in randomized order. With this design, the visual settings of the first block (first 8 stimuli) are freefrom potential carryover effects, while only the subsequent two blocks (remaining 16 stimuli) may
contain such effects.
The resulting data set was first visualized, and subsequently analyzed with linear mixed-effects
models (procedure MIXED of IBM SPSS Version 23 and 25).

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3. RESULTS AND DISCUSSION
Figures 1 and 2 present boxplots of the individual annoyance ratings, showing the median (50%,horizontal line in boxes), the first and third quantiles (25% and 75%, lower and upper boundaries ofboxes), the whiskers (data within 1.5 times the interquartile range), and outliers (outside the whiskers).
The acoustical characteristics strongly affect noise annoyance (Figure 1). For the first block ofvisual setting, noise annoyance strongly increases with the A-weighted equivalent continuous soundpressure level (LAeq ) and is larger in situations with AM compared to situations without AM (Figure1a). In fact, AM led to an annoyance increase of ~0.6 units on the 11-point scale, which would also be
evoked by an equivalent sound level increase of ~2 dB. This corroborates the findings of (2). Theeffects revealed by the whole set of 24 stimuli (Figure 1b) are very similar to those of the first block,
except that the annoyance ratings tend to be higher. Apparently, the subjects became increasingly
annoyed by the stimuli over the experiment. This indicates a simple order effect, as was also observedin (2).
Also the visual setting is important for noise annoyance (Figure 2). For the first block of visualsetting (free from potential differential carryover effects), noise annoyance decreases in the order grey
background > landscape with WT > landscape without WT. Compared to the landscape without visible
WT, WT visibility led to an annoyance increase of ~0.7 points on the 11-point scale. This corresponds
to an equivalent sound level increase of ~2 dB (i.e., similar as for AM). Thus, a visible WT was linked
to increased annoyance, which is in line with literature (3). The visible WT may have drawn the focusof the subjects to the WT noise, while the subjects were more distracted by the landscape without WT.
Similarly, the grey background may be associated with the highest annoyance because it did not allow
for any (visual) distraction from the noise. Contrary to the quite stable acoustical effects, the visual
effects of the first block were completely lost over the whole experiment (Figure 1b). Here, the threesettings were linked to very similar annoyance reactions. This may be attributed to a differential
carryover effect. It cannot be eliminated by counterbalancing, but must be dealt with using otherstrategies such as sufficiently long time intervals between stimuli.
The above observations were all corroborated with mixed-effects models.
10(b)

(a)

9
Noise annoyance [-]

876
5
4
32
with AM
no AM

with AM
no AM

1033.0 34.0

38.2 39.2 43.6 44.6
LAeq [dB]

48.6 49.4

33.0 34.0

38.2 39.2 43.6 44.6
LAeq [dB]

48.6 49.4

Figure 1 – Boxplots of the individual noise annoyance ratings as a function of the A-weighted equivalentcontinuous sound pressure level (LAeq) and amplitude modulation (no or with AM), (a) for the first block(first 8 stimuli) and (b) all three blocks of visual settings (24 stimuli). Note that the x-axis is not to scale.

4. CONCLUSIONSThe present study revealed that both visual and acoustical characteristics strongly of WTs affectnoise annoyance in a laboratory setup. In particular, annoyance increased with periodic AM and/ordecreased when a landscape was visible. For the latter case, the visibility of a WT led to an annoyance
increase corresponding to an equivalent sound level increase of 2 dB. While the acoustical effects
could be reliably assessed, the visual effects were less straightforward to reveal, as they were afflictedwith carryover effects. The presentation order of audio-visual stimuli was therefore found to be crucial
for study outcomes.

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109(a)(b)

Noise Annoyance [-]876543210

Landscapewith WTLandscapewithout WTVisual settingGreybackgroundLandscapewith WT

Landscapewithout WTGreybackground

Visual setting

Figure 2 –Boxplots of the individual noise annoyance ratings as a function of the visual setting, (a) for the
first block (first 8 stimuli) and (b) all three blocks of visual settings (24 stimuli).

ACKNOWLEDGEMENTS
We are very grateful to the subjects participating in the study. The study was funded by the authors’
institutions Empa and ETH Zurich, and approved by the Ethics Commission of ETH Zurich.

FULL PUBLICATIONThis study has already been published in the journal “Landscape and Urban Planning”, DOI
10.1016/j.landurbplan.2019.01.014, and all study details may be found there (7).

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