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

Non-acoustic and acoustic variables associated with wind turbine
noise annoyance
Jenni RADUN 1; Valtteri HONGISTO11Turku University of Applied Sciences, Finland

ABSTRACTBACKGROUND. Previous residential surveys have been conducted in areas involving wind turbines (WTs)less than 3 MW. However, modern WTs are usually larger than 3 MW and the applicability of the previous
results must be re-examined. Previous results show that sound level explains only a small portion of noiseannoyance in WT areas.
AIM. The purpose was to determine how various non-acoustic factors are associated with WT noiseannoyance.
METHODS. The survey was conducted around three areas involving WTs sizing from 3 to 5 MW in Finland.
Altogether 318 permanent residents living within 2 km from the WTs answered the survey. The modelled
WT noise outside their houses ranged from 27 to 44 dB LAeq.
RESULTS. The concern for health effects of WT noise was the strongest associate of WT noise annoyance.
Other factors were area, noise sensitivity, gender, and general attitude towards wind power as an energy
production form. Sound level of WTs had only a weak association with annoyance outdoors, but not indoors.
PRACTICAL IMPLICATIONS. Provision of fact-based information to the residents about the health effectsof wind turbines could reduce the health concerns and thereby noise annoyance.
Keywords: Wind turbine noise, Non-acoustic factors, Annoyance

1. INTRODUCTIONWind energy is a renewable energy form, which, however, produces special type of sound that canbe considered as noise, i.e. unwanted sound. Therefore, it can be considered an environmental stressor.
Wind turbine noise (WTN) can be perceived annoying by people living nearby and it can also cause
subjective sleep disturbances (1). However, the relationship between noise annoyance and sound levelis modest (2,3), which means other factors besides sound level play an important role in becoming
annoyed by the sound. Previous studies have involved wind turbines of 3 MW at most (3). There is aneed to study the noise annoyance caused by larger WTs since modern WTs are usually larger than 3MW.
Non-acoustic variables related to WTN annoyance can be divided into three categories: personal,situational, and contextual. Personal factors are related to person’s characteristics, attitudes, andexpectations. Personal factors related to WTN annoyance are, for example, noise sensitivity (2,4),
safety concerns (2), and attitudes towards wind turbines (5). Situational factors are related to generalsituation and environment, as for example, the visibility of wind turbines to the property (4), theownership of the property (2). Contextual factors are not readily present, but influence attitudes
towards WTN, which can be for example benefitting from the wind turbines (2,4), or unfair politics
and a siting process that can be reflected to inefficient coping mechanisms and noise annoyance (6).
The purpose was to determine how various non-acoustic factors are associated with WT noise
annoyance in three Finnish wind power areas with large wind turbines (3-5 MW). From eachparticipant, we collected the questionnaire data as well as the modeled sound level of WTN outside
their houses. We formed models of variables related to WTN annoyance. We expected the sound levelto have a small but significant influence on annoyance. Other variables we expected to be related toWTN annoyance were noise sensitivity, attitude towards wind power, visibility of wind turbines andownership of the house. A more detailed report of the study has been published in Ref. (7) and a1jenni.radun@turkuamk.fi; valtteri.hongisto@turkuamk.fi

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detailed dose-response relationship of the data used here was published in Ref. (3).

2. METHOD
2.1 Sample
The sample consisted of the residents close to three wind power areas in Finland. Variable area
describes the area the participants live in (area 1, area 2, and area 3). These areas were chosen torepresent different types of WT areas. The areas differed from each other in three factors: general
resistance (area 1 was the most against), population density (area 3 was the most densely populated),
and history of land use (area 1 was located near industrial area, while areas 2 and 3 were in recreational
areas). The residents living within 2 km from the nearest WT were invited to participate. The survey
was conducted using both face-to-face interviews and in-mail questionnaires.
2.2 Sound level predictions
Outdoor sound pressure level (SPL) in each participants yard was predicted according tointernational standard (8). The method used in this study was described in more detail by Hongisto etal. (3). The outcome was the A-weighted equivalent SPL, L Aeq, (later: sound level) at a height of 4 m
from the ground. The predicted sound level corresponds to the weather conditions when the WTs
operate at their maximum power. The sound level predictions were verified in each area using
measurements during maximum electric power and the predicted sound levels corresponded well withmeasured sound levels (3). In addition to sound levels, 5-dB wide sound level categories are used inthis study.
2.3 Questionnaire
Table 1 describes the set of questions used in this study and Table 2 their response scales. The
questionnaire included a vast set of questions. Here we included only those, which were presented in
all three areas, and were not correlated with other questions in the set. Questions dealing with sleepwere left out because we focus on annoyance. The full set of questions can be found both from Refs.
(3) and (7).
2.4 Dependent variables
We used %A indoors and %A outdoors as the dependent variables in our study. %A means thepercentage of annoyed respondents. A participant belongs to the group of %A indoors, if he/she
responded “4” or “5” to variable annoyance indoors. We used similar dichotomization protocol for %Aoutdoors.
2.5 Statistical analysis
Different areas were compared with each other using Fisher’s exact test for dichotomous variables
and analysis of variance for continuous variables. In addition, the response rates from different soundlevels were compared using Fisher’s exact test. Absolute sound levels were used instead of sound level
categories. The binary logistic regression models were used to get a predictive power of different
variables related to %A indoors and %A outdoors. The final variables in the binary logistic regression
model were: noise sensitivity, health concern, energy attitude, landscape attitude, sound level,visibility, and the background factors of gender, age, and area. We used a stepwise model withconditional forward selection with an entry threshold of 0.05 and a removal criterion of 0.10.

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Table 1 – Variables, their explanations and response scales. The response scales are defined in Table 2.
Variable nameAnnoyance outdoors

Question(Q)/explanation
Q16a. How annoying do you find the WT sound oudoors in your yard?

Scale
A

Annoyance indoors

Q18a. How annoying do you find the WT sound indoors inside your apartment?

ANoise sensitivity

Sum of questions 10a. (reversed) and 10b.

Health concern

Q10a. I easily get used to most sounds.

B

Q10b. Sounds annoy me easily.

B

Q31. Are you concerned about possible effects of WT sound on your health?

CLandscape attitude

Q24. The influence on WTs for the scenery is…

DChange attitude

Q25. Has your opinion changed about the WTs after building it in the area?

DCommunity benefit

Q28. Has your community benefited from WTs?

EEnergy attitude

Q30. What is your opinion of the wind power electricity as a form of energy?

FTrust for operators

Q33a. Do you think the operators of wind farms have done enough to control possible damages?

E

Trust for authorities

Q33b. Do you think the authorities have done enough to control possible damages?

EVisibility

From Q22 and Q23 if one is yes, WT is visible

E

Q22. Can you see a WT from your yard?

E

Q23. Can you see a WT from your window?

ETable 2 – The response scales of questions.
Scale

Response categories

A

1 Sound not audible. 2 Sound audible, but not annoying. 3 Sound annoys a little. 4 Sound annoys
quite much. 5 Sound annoys a lot.
1 Disagree strongly, 2 Disagree to some extent, 3 Neither disagree nor agree, 4 Agree to some extent,5 Agree strongly
1 Not at all, 2 Only slightly, 3 To some extent, 4 To a great extent, 5 To a very great extent.

BCDEF

1 Clearly positive, 2 Somewhat positive, 3 No influence/neutral, 4 Somewhat negative, 5 Clearly
negative
0 No, 1 Yes
1 I am very positive, 2 I am more positive than negative, 3 I am neutral, 4 I am more negative thanpositive, 5 I am clearly negative

3. RESULTSTable 3 describes the samples from different areas.
%A indoors was 8.0% and %A outdoors was 15.4% in the whole sample. According to Figure 1, %Aindoors and %A outdoors depended on the area (%A indoors p<0.001 and %A outdoors p<0.001) andsound level (%A indoors p=0.001 and %A outdoors p<0.001).
We examined with logistic regression which are the most important variables associated with WTN
annoyance (Table 4). Health concern was the most important variable and area was the second-mostimportant variable in both models of %A indoors and %A outdoors.
The results of logistic regression can be interpreted by the following example: when a participant
gave a step higher answer in health concern, he/she was 4.5 times more likely to be annoyed by WTN.
Other important variables were energy attitude and noise sensitivity. Women were more often annoyed
by WTN indoors than men were. Sound level was included in the model only with %A outdoors.

4. DISCUSSION

We cannot suggest any causality relationship between the subjective variables involved in our study.
However, noise annoyance has been found to be the most usual health effect of WTs (1). Therefore, it
was justified to develop a model for annoyance indoors and annoyance outdoors and not for healthconcerns.

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Table 3 – The description of participants in different areas, in total, and whether the areas differed fromeach other.
Area 1

Area 2

Area 3Total

No. of households within 2 km

107

189

457

753

No. of all respondents

7091

268

429

Response rate [%]

65.4

48.1

58.6

57

Permanent residents [%]54419577

No. of participants (No. ofpermanent residents)
Age [yr]

3037251318

Mean (SD)60 (14)59 (14)53 (15)55 (15)

Range

24–85

23–85

17–89

17–89

Gender , Females [%]

56.7

32.4

48.6

47.5

p -value

0.01

Sound level [dB L Aeq ]Mean (SD)38 (3)

36 (3)

34 (3)

34 (3)

Range

34–44

32–41

27–46

27–46

ns
<0.001Distance [m]<0.001

Mean (SD)1395 (372) 1317 (327) 1542 (244) 1503 (279)Range

672– 2005

785– 1901

479– 1996

480– 2005

Trust in authorities [%]

12.5

66.7

48.6

46.00.001

12.066.750.848.3<0.001

18.5

51.7

21.8

24.60.003

Trust in operators [%]Community benefit [%]SD=Standard deviation
ns=non-significant

Figure 1 – (a) The percentage of annoyed residents, %A, per area. (b) The percentage of annoyed residents
as a function of sound level category, LAeq.

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Table 4 – The logistic regression models for %A outdoors and %A indoors.
Logistic regression model%A outdoors
VariableGroups in the variablea(N=280, R 2 =0.710,c H-L,d p =0.651)
OR (Cl)bp-value eOrder of entry into model:
R 2 at each step

Health concern

Scale: 1-5

2.71 (1.78, 4.11)<0.01

Step 1: 0.43

Area

Area 1

10.32 (2.22, 47.84) <0.01

Step 2: 0.58

Area 20.29 (0.03, 3.21)

0.31

Area 3

Reference<0.01

Energy attitude

Scale: 1-5

1.89 (1.24, 2.87)<0.01

Step 3: 0.63

Noise sensitivity

Scale: 2-10

1.69 (1.23, 1.32)<0.01

Step 4: 0.67

Sound level [dB]

Continuous

1.41 (1.14, 1.74)<0.01

Step 5: 0.71

Logistic regression model%A indoors
VariableGroups in the variablea(N=281, R 2 =0.667,c H-L,d p =0.992)
OR (Cl)bp-value eOrder of entry into model:
R 2 at each step

Health concern

Scale: 1-5

4.46 (2.41, 8.26)<0.01

Step 1: 0.47

Area

Area 1

5.69 (1.25, 25.97) 0.03

Step 2: 0.55

Area 2
Area 3f

0.00 (0.00, 0.00)

1Reference

0.08

Noise sensitivity

Scale: 2-10

1.81 (1.15, 2.84)

0.01

Step 3: 0.60

GenderFemale/Male8.30 (1.63, 42.19) 0.01

Step 4: 0.63

Energy attitude

Scale: 1-5

1.92 (1.10, 3.35)

Step 5: 0.67

a0.02

The reference category in categorical variables is always the last category.

bOdds ratio (OR) and 95% confidence interval CI based on the binary logistic regression model; an OR indicates how
much the odds of belonging to a dependent group changes with one step of independent variable. OR > 1 indicates thatodds of belonging to dependent group were higher relative to the reference group or category and OR < 1 means they
were lower.
c2The Nagelkerke pseudo R gives an estimate of the proportion of deviance explained by the model. Its values arebetween 0 and 1, 1 indicating perfect fit.

dH-L: Hosmer-Lemeshow test, p>0.05 indicates a good fit.

ep-values indicate whether the variable was significantly contributing to the model.

fArea 2 had no-one reporting annoyance indoors larger than 3.

Health concern is the most important variable related to both annoyance indoors and annoyanceoutdoors. In other words, if a person is concerned that WTN might have an influence on their health,he/she is more likely to be annoyed by the noise. The second variable related to annoyance is area.
This is somewhat surprising, even though we selected areas to represent different types of windturbine areas. The negative attitude of people in area 1 is clearly reflected to the annoyance scores ofthat area (62% annoyed outdoors and 31% indoors), whereas in area 2, no one belongs to the groupof %A indoors and only 6% belongs to the group of %A outdoors. Table 3 shows that the respondents
from different areas have also different opinions on whether they trust the authorities and operators
and whether their community has benefited from the WTs. The benefit has been linked to annoyancealready earlier, but mainly on a personal level (2,9). In our sample, there were just six persons
benefiting personally from WTs. Based on other information we have received, we believe that also
differences in land use history are reflected in the attitudes of people from different areas.

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Other variables related to annoyance were noise sensitivity and energy attitude. Noise sensitivity
is reported as a personal variable in previous studies (2,4). Sound level was included only in the modelof %A outdoors. This might reflect the fact that indoors the noise is reduced by building façade andits direct importance is reduced. However, the sound insulation of building façades differs a lot (10)and it may partially explain the variance between respondents. Gender was included in the model %Aindoors. Women reported more annoyance of WTN indoors than men did. A previous study on WTN
annoyance did not report a gender difference in annoyance indoors (4).

5. CONCLUSIONSTo reduce annoyance, we suggest that factual knowledge should be used to answer people’sconcerns. This could reduce people’s concern and sensitive people would feel they are being listened
to.

ACKNOWLEDGEMENTS

The study was part of Anojanssi –project, which was funded by Business Finland, Turku Universityof Applied Sciences, Ministry of Environment Finland, Ministry of Social Affairs and Health Finlandand collaborating companies and associations.

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