FACTORS AFFECTING SUBJECTIVE PERCEPTION OF ANNOYANCE FROM WIND TURBINE NOISE

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1 FACTORS AFFECTING SUBJECTIVE PERCEPTION OF ANNOYANCE FROM WIND TURBINE NOISE Małgorzata Pawlaczyk-Łuszczyńska, Kamil Zaborowski, Adam Dudarewicz, Małgorzata Zamojska-Daniszewska and Małgorzata Waszkowska Nofer Institute of Occupational Medicine, 8 Sw. Teresy, Lodz, Poland mpawlusz@imp.lodz.pl A questionnaire inquiry on response to the wind turbine noise was carried out in 538 people living in the vicinity of wind farms. For areas where respondents lived, A-weighted sound pressure levels were determined and random noise measurements were performed. Wind turbine noise at the calculated A-weighted sound pressure levels of 33 5 db was perceived as annoying outdoors and indoors by 27.3% and 18.% of respondents, respectively. The perception of annoyance was associated with noise levels or the distance from the nearest wind turbine, general attitude to wind farms, noise sensitivity and shape of terrain (annoyance outdoors) or road traffic intensity (annoyance indoors). About 49 66% of variance in noise annoyance rating might be explained by the aforesaid factors. The percentage of annoyed respondents increased with increasing sound pressure level and noise sensitivity, while it decreased with increasing distance and positive attitude to wind farms. Hilly or mountainous terrain increased the risk of being annoyed compared with flat ground. Increased traffic intensity showed the opposite effect. 1. Introduction Wind power has been recognized as a clean renewable energy source that does not contribute to global warming and is without known emissions or harmful wastes. However, its dynamic development around the world is associated with increasing number of people being exposed to noise emitted by wind turbines. It has been shown that noise from wind farms is perceived as annoying by a proportion of respondents living in the nearby areas, apparently at much lower noise levels in comparison to other sources of environmental noise [1]. Generally, people are more likely to be annoyed when A-weighted sound pressure levels exceed 35 4 db. Proportion of people perceiving wind turbine noise and annoyed by it increases with increasing noise levels [2 4]. Subjective factors such as having turbines visible from the dwelling, negative opinion about wind turbines in general and/or their visual impact on landscape and self-reported sensitivity to noise increase the probability of being annoyed by wind turbine noise [2, 3, 5], while economic benefits obtained from wind turbines reduce the risk of annoyance [4]. It has been also found that terrain characteristics and urbanization affect the perceived annoyance from the wind turbine noise. In particular, people living in the areas with other background noises are less affected than those from quiet areas [3, 6]. ICSV22, Florence (Italy) July 15 1

2 The main objective of this study was to evaluate the perception and annoyance of noise from wind turbines in populated areas in Poland. The further objective was to analyse factors affecting subjective perception of annoyance. 2. Methodology A cross-sectional study on response to wind turbine noise was carried out involving people living in the vicinity of ten wind farms located in the north, central and the south-eastern parts of Poland. Of the 213 wind turbines in the selected areas, 136 had power of MW, of 1.5 MW, 6 of.6.8 MW, while others had power ranging kw. Nine areas totalling km 2 were investigated. A questionnaire was applied as the main research tool. The study group comprised 538 subjects aged years. They were personally asked to complete questionnaires. No exclusion criteria were applied. For investigated areas, A-weighted sound pressure levels were calculated as the sum of the contributions from the wind power plants in the neighbourhood. In addition, noise conditions outside the dwellings were at random verified by in situ measurements. 2.1 Questionnaire survey Subjects completed a questionnaire developed to enable evaluation of their living conditions, including prevalence of annoyance due to noise from wind turbines, and the self-assessment of physical health and wellbeing. This questionnaire was based on the one previously used in Swedish studies [2, 3]. In addition, the current mental health status of respondents was assessed using 12-item Goldberg General Health Questionnaire (GHQ-12) which was adapted for Polish conditions [7]. In the present study, response to wind turbine noise was analysed based on answers to inquiries on: (a) occurrence ( yes or no ) and the degree of annoyance experienced outdoors and indoors from this type of noise ( not at all annoying =, a little annoying =1, rather annoying =2, annoying =3, or extremely annoying =4), (b) sensitivity to noise, landscape littering ( definitely no =, no =1, no opinion =2, yes =3, or definitely yes =4), (c) general opinion on (attitude towards) wind turbines and on the visual impact of wind turbines ( very negative =, negative =1, no opinion =2, positive =3, very positive =4), and (d) different auditory aspects of wind turbines during various subjects activities (e.g., relaxing, taking walks). 2.2 Noise exposure evaluation For areas where respondents lived, A-weighted sound pressure levels (SPLs) were calculated as the sum of the contributions from the wind turbines in the neighbourhood based on the sound propagation model described in ISO :1996 [8]. In these calculations, the A-weighted sound power levels of wind turbines specified by manufactures were used. The arrangement of turbines within each of the farms was obtained from the internet maps [9], while the distances between dwellings and turbines were calculated from the GPS data collected in front of residential premises. In addition, for about 37% (n=) of respondents, noise levels were measured outside their dwellings at the height of 1.5 and/or 4 meters using a sound analyser (SVANTEK type SVAN 958). These measurements were carried out taking into account Polish recommendation concerning assessment of environmental noise []. 2.3 Statistical analysis Answers to the questionnaire were presented as the proportions with 95% confidence intervals (CI). When relevant, the data from multi-score verbal rating scales were dichotomized, e.g. the answers annoying and extremely annoying were classified as annoying, while the others ( not at all annoying, a little annoying and rather annoying ) as not annoying. ICSV22, Florence, Italy, July 15 2

3 Binary logistic regression was used to study the influence of various objective and individual/subjective factors (e.g., noise level or attitude to wind turbine) on annoyance related to wind turbine noise. The same tool was applied to determine the relationships between percentage of respondents annoyed by wind turbine noise and various factors, including calculated A-weighted sound pressure level. The Nagelkerke pseudo-r 2 was applied as a measure of explained variance while the correct classification rate (CCR) was considered as a measure of fit of logistic model. The statistical analysis was carried out with an assumed level of significance α=.5 using STA- TISTICA (version 9.1. StatSoft, Inc.) software package. 3. Results 3.1 Study population Generally, the majority of respondents (83.3%) lived in privately owned detached or semi-detached houses in the countryside or in small villages, in rural or suburban areas with diversified terrain shape and traffic intensity. Almost all respondents (93.1%) could see one or more wind turbines from their dwelling, backyard or garden. Only a few (5.6%) of them had profits from the wind turbines. The mean age in the study population was 46.3±16. years. Women were more numerous than men (58.9% vs. 41.1%). Over half of the subjects were classified as sensitive to noise (65.4%) and landscape littering (61.%). Of the respondents,.7% and 35.3% declared negative ( very negative or negative ) attitude towards wind turbines in general and their visual impact in particular, respectively. Respondents examined using the GHQ-12 obtained a mean score at the level of 12.5±6. which was close to the normative result for the reference Polish population (11.2±5.1) [7]. 3.2 Noise exposure evaluation The study subjects lived at the distance from 4 m to 1726 m from the nearest wind turbine. They were exposed to the wind turbine noise at the measured equivalent-continuous: (a) A-weighted SPLs of 33 5 db (42.6±3.4 db), (b) C-weighted SPLs of db (56.1±5.8 db), and (c) G-weighted SPLs of 53 9 db (72.4±8.7 db). In areas where respondents lived, the calculated A-weighted SPLs ranged from 33.5 to 49.5 db (42.1±3. db). Over half of subjects (58.2%) were exposed to noise at the calculated A-weighted sound pressure levels of 4 45 db, while over two-thirds (67.8%) lived at the distance of 4 8 m from the nearest wind turbine. 3.3 Results of questionnaire survey Generally, the wind turbine noise was noticed outdoors by 65.6% (95% CI: %) of subjects, while indoors it was noticed by 45.5% (95% CI: %) of them. Moreover, this type of noise was perceived as annoying outdoors (i.e. as annoying or extremely annoying ) by 27.3% (95% CI: %) of respondents. On the other hand, 18.% (95% CI: %) of subjects said that they were annoyed indoors. The wind turbine noise was most frequently reported when relaxing outdoors (54.1%, 95% Cl: %), taking walks (48.5%, 95% Cl: %) and during quiet outdoor activities and get-together outdoors such as barbecue (48.1%, 95% Cl: %). However, the subjects were most often annoyed by the wind turbine noise when relaxing outdoors (26.%, 95% Cl: %) and taking walks (25.5%, 95% Cl: %). About two-thirds of the respondents (65.1%, 95% CI:.9 69.%) indicated rotor blades as the main source of the wind turbine noise, while noise from the turbine machinery was reported only by 21.% (95% CI: %) of them. Over one-third (39.2%, 95% CI: %) of the respondents frequently ( almost every day or at least once a week / several times a week ) noticed the wind turbine noise. Furthermore, subjects were most often annoyed outdoors in the evening (4.%, ICSV22, Florence, Italy, July 15 3

4 Percentage of annoyed outdoors [%] Percentage of annoyed indoors [%] The 22 nd International Congress on Sound and Vibration 95% C*I: %), while indoors in the evening and night (29.7%, 95% CI: % and 29.2%, 95% CI: %). Recently, based on the accessible data from Swedish and Dutch cross-sectional studies [2 4], the exposure-response relationships between the exposure metric Lden (annual day-evening-night noise level according to 2/49/EC) and self-reported annoyance indoors as well as outdoors of the dwellings due to wind turbine noise were determined using the method previously applied to derive the exposure-response relationships for transportation and industrial noise (Fig. 1) [1]. However, to obtain the exposure metrics Lden, a correction of +4.7 db, calculated by van der Berg [11], was added by Janssen et al. [1] to the predicted A-weighted sound pressure levels. To compare the proportions of subjects annoyed by wind turbine noise in this study with the predictions of the aforesaid exposure-response relationships, the respondents were classified into subgroups (according to noise level). Furthermore, the calculated A-weighted sound pressure levels, like in Jansen et al. study [1], were corrected to obtain the exposure metrics Lden (i.e. a correction factor of +4.7 db was added to those data). As can be seen in Fig. 1, the percentages observed in this study, of respondents being annoyed (outdoors or indoors) by wind turbine noise at given Lden levels fitted quite well the proposed exposure-relationships. 8 7 %Highly annoyed %Annoyed 8 7 %Highly annoyed %Annoyed Noise exposure metric L den [db] a) b) 4 5 Noise exposure metric L den [db] Figure 1. Comparison of observed proportions (with 95% confidence levels) of respondents being annoyed outdoors (a) and indoors (b) by wind turbine noise to proposed exposure-response relationship for wind turbine annoyance [1]. Dots with whiskers represent survey data with 95% CI Factors affecting perception of annoyance and self-reported health In order to analyse the impact of objective and individual / subjective factors on noise annoyance rating, the binary logistic regression was applied with the logistic model expressed as follows: (bo b1x1 b 2x2... bnxn ) e (1) p (bo b1x1 b2x2... bnxn ) 1 e where: p is the probability of being annoyed ( annoyed or extremely annoyed ) by noise from wind turbines outdoors/indoors, x1 xn are the explanatory variables included in the model (e.g., calculated A-weighted sound pressure level), bo, b1, bn are the regression coefficients, i.e. the logarithmic values of the odds ratio for the unit change in the respective variables. Explanatory variables were age, gender, education, sensitivity to noise, attitude to wind farms, self-assessment of physical health and mental health status expressed in the GHQ-12 score, economic benefits obtained from wind turbines ( yes =1 or no =), terrain shape ( flat =, hilly or mountainous =1), traffic intensity ( no traffic or very low-intensity traffic =, increased intensity =1), time since the start-up of the wind farm, turbines visible from the dwelling or backyard ( yes =1 or no =), ICSV22, Florence, Italy, July 15 4

5 power/height of turbine, and distance from the nearest turbine or calculated A-weighted sound pressure level at respondents dwellings. Various models were developed, including those containing each explanatory variable separately. It is worth to underline that neither age nor gender had significant impact on noise annoyance rating. The highest values of explained variance (approx. 66%) in perceived annoyance outdoors were obtained for models containing general attitude to wind turbines, terrain shape, sensitivity to noise and noise level (or distance) as explanatory variables (model no. 1 and 4) (Table 1). Similar results (pseudo-r 2.6) were obtained for models no. 2, 3, 5 and 6, especially those with noise level (or distance) and attitude to wind turbines as the independent variables. On the other hand, noise level (or distance) itself explained only about 1% of the variance in annoyance assessment (see models no. 4 and 8 in Table 1). Table 1. Factors affecting noise annoyance perception outdoors results of logistic regression analyses. Model no. Explanatory variable Odds ratio (95% CI) p Pseudo- R 2 CCR Terrain shape 3.58 ( ). 1 Sensitivity to noise 1.47 ( ).21 Attitude to wind turbines.18 ( ) % Sound pressure level 1.12 ( ).19 Terrain shape 3.79 ( ). 2 Attitude to wind turbines.16 ( ) % Sound pressure level 1.13 ( ).14 3 Attitude to wind turbines.14 (. -.). Sound pressure level 1.12 ( ) % 4 Sound pressure level 1.7 ( ) % Terrain shape 3.83 (2.7-7.). 5 Sensitivity to noise 1.5 (1.7-2.).17 Attitude to wind turbines.18 ( ) % Distance. (.2 -.5).5 Terrain shape 4.9 ( ). 6 Attitude to wind turbines.16 ( ) % Distance. ( ).4 7 Attitude to wind turbines.14 (. -.). Distance.15 ( ) % 8 Distance.35 ( ) % Similar relationships were obtained when analysing noise annoyance perception indoors (Table 2). However, in this case, instead of terrain shape, the traffic intensity was found to have impact on noise annoyance (compare models no. 1, 2, 5 and 6 in Tables 1 and 2). The odds of being annoyed by wind turbine noise increased with increasing noise level (odds ratio OR>1) and sensitivity to noise (OR>1), while it decreased with increasing distance (OR<1) and positive attitude to wind farms (OR<1). Hilly or mountainous terrain increased the risk of being annoyed compared with flat ground (OR>1). Increased traffic intensity showed the opposite effect (OR<1) (Tables 1 and 2). Results of the logistic regression analysis were also used as the basis for determination of exposure-response relationships expressed as probability (percentage) of being annoyed (outdoors or indoors) versus noise level (or distance) and other variables. Tables 3 and 4 present the estimates of regression coefficient i (with estimated standard errors) for the aforesaid models, while Figs. 2 and 3 show the exposure-response curves that were determined by the logistic regression procedure. ICSV22, Florence, Italy, July 15 5

6 Table 2. Factors affecting noise annoyance perception indoors results of logistic regression analyses. Model No. Explanatory variable Odds ratio (95% CI) p Pseudo- R 2 CCR 1 Traffic intensity.26 ( ).3 Sensitivity to noise 1.45 ( ).36 Attitude to wind turbines.28 ( ) % Sound pressure level 1. ( ).49 2 Traffic intensity.28 ( ).5 Attitude to wind turbines.25 ( ) % Sound pressure level 1.11 ( ).36 3 Attitude to wind turbines.22 (.17 -.). Sound pressure level 1. ( ) % 4 Sound pressure level 1.8 ( ) % 5 Traffic intensity.29 ( ).6 Sensitivity to noise 1.46 ( ).31 Attitude to wind turbines.28 ( ) % Distance. ( ).42 6 Traffic intensity.31 ( ). Attitude to wind turbines.25 ( ) % Distance.19 ( ).35 7 Attitude to wind turbines.23 (.17 -.). Distance.14 ( ) % 8 Distance.22 ( ) % According to the aforesaid relationships, namely model no. 7 (Table 3), at the distance of the order of m the wind turbine noise might be perceived as annoying outdoors by 1% and 32% of people with positive and negative attitude towards wind farms, respectively. At the same distance, up to 13% subjects (in particular those with negative attitude to wind farms) might be annoyed by wind turbine noise indoors (see model no. 7 in Table 4). Table 3. Estimated coefficients for the various logistic models of noise annoyance perception outdoors (see Table 1). All coefficients, excluding those in bold, reached statistical significance (p<.5). Explanatory variable /Estimate of coefficient i / Standard error Model Sensitivity to Attitude to wind Sound pressure no. Constant Terrain shape noise turbines level / / / / / / / / / / / / / /.332 Constant Sensitivity to Attitude to wind Terrain shape noise turbines Distance / / / / / / / / / / / / / /.5269 ICSV22, Florence, Italy, July 15 6

7 Percentage of annoyed indoors [%] Percentage of annoyed indoors [%] Percentage of annoyed outdoors [%] Percentage of annoyed outdoors [%] The 22 nd International Congress on Sound and Vibration Table 4. Estimated coefficients for the various logistic models of noise annoyance perception indoors (see Table 2). All coefficients, excluding those in bold, reached statistical significance (p<.5). Explanatory variable /Estimate of coefficient i / Standard error Model Sensitivity to Attitude to Sound pressure no. Constant Traffic intensity noise wind turbines level / / / / / / / / / / / / / /.387 Constant Sensitivity to Attitude to Traffic intensity noise wind turbines Distance 5.615/ / / / / / / / / / / / / / Model no. 1 Model no. 2 Model no. 3 Model no Model no. 5 Model no. 6 Model no. 7 Model no A-weighted sound pressure level [db] a) b) Distance [km] Figure 2. Relationships between percentage of respondents annoyed outdoors and noise level (a) or distance from the nearest wind turbine (b). Eight curves corresponding to various models from Table 3 were drawn (with explanatory variables: terrain shape =1 (hilly terrain), sensitivity to noise =3 and/or attitude to wind farms =2 (median values in the study group), where applicable). Dots with whiskers represent survey data with 95% CI. 5 4 Model no. 1 Model no. 2 Model no. 3 Model no Model no. 5 Model no. 6 Model no. 7 Model no A-weighted sound pressure level [db] Distance [km] a) b) Figure 3. Relationships between percentage of respondents annoyed indoors and noise level (a) or distance from the nearest wind turbine. Eight curves corresponding to various models from Table 4 were drawn (with explanatory variables: traffic intensity = (no traffic or very low-intensity traffic), sensitivity to noise =3 and/or attitude to wind farms =2 (median values in the study group), where applicable). Dots with whiskers represent survey data with 95% CI. ICSV22, Florence, Italy, July 15 7

8 4. CONCLUSIONS To sum up, results of our study evaluating response to wind turbine noise in populated areas in Poland are in line with observations from earlier Swedish and Dutch cross-sectional studies [2 6]. It has been shown that people living in the vicinity of wind farms are at the risk of being annoyed by the noise. The perception of annoyance was associated with the A-weighted sound pressure level or the distance from the nearest wind turbine, general attitude to wind farms, noise sensitivity and terrain shape (annoyance outdoors) or traffic intensity (annoyance indoors). About 49-66% of variance in noise annoyance rating might be explained by the aforesaid factors. According to exposure-response relationships which were determined in this study, in particular those relating the proportion of annoyed subjects with the attitude to wind farms and distance from the nearest turbine, up to 32% of those people negatively oriented towards wind farms are expected to be annoyed by noise from turbines located at a distance of the order of m. Furthermore, up to 13% persons might be annoyed indoors. Generally, the relationships between self-reported annoyance and distance (and other factors) seem to be useful in selecting setback distances to reduce or avoid potential noise complaints from, or potential effects to, people living in proximity to wind farms. This is important, since several unreliabilities related to the calculations might result in over- or underestimation of noise levels experienced in everyday life in the vicinity of wind farms. This study was supported by the Ministry of Science and Higher Education of Poland (Grants IMP 18.5/11 12 and IMP 17.1/13 14). REFERENCES 1 Janssen, S. A., Vos, H., Eisses, A. R., Pedersen, E. A comparison between exposure-response relationships for wind turbine annoyance and annoyance due to other noise sources, Journal of the Acoustical Society of America, 1, (6), (11), 2 Pedersen, E., Persson Waye, K. Perception and annoyance due to wind turbine noise A dose-response relationship, Journal of Acoustical Society of America, 116 (6), (4). 3 Pedersen, E., Persson Waye, K. Wind turbine noise, annoyance and self-reported health and well-being in different living environments, Occupational and Environmental Medicine, 64 (7), (7). 4 Pedersen, E., van den Berg, F., Bakker, R., Bouma, J. Response to noise from modern wind farms in the Netherlands, Journal of Acoustical Society of America, 126 (2), (9). 5 Pedersen, E., Larsman, P. The impact of visual factors on annoyance among people living in the vicinity of wind turbines, Journal of Environmental Psychology, 28 (4), (8). 6 Bakker, R. H., Pedersen, E., van den Berg, G. P., Stewart, R. E., Lok, W., Bouma, J. Impact of wind turbine sound on annoyance, self-reported sleep disturbances and psychological distress, Science of the Total Environment, 425, (12). 7 Makowska, Z., Merecz, D., Mościcka, A., Kolasa W. The validity of General Health Questionnaires, GHQ-12 and GHQ-28, in mental health studies of working people, International Journal of Occupational Medicine and Environmental Health, 15 (4), (2). 8 ISO :1996 Attenuation of sound during propagation outdoors. Part 2: General method of calculation. Geneva: International Organization for Standardization (1996). 9 Geoportal.gov.pl [Internet], Warszawa: Head Office of Geodesy and Cartography (14). The Decree by the Minister of Environment of November 4, 8 on the requirements with respect to the measurements of emission levels and the measurements of the amounts of abstracted water. Official Journal of Laws. 6, 129 (8). 11 van den Berg, F. Criteria for wind farm noise: Lmax and Lden, Proceedings of the 7th European Conference on Noise Control, EuroNoise, Acoustics 8, Paris, France, 29 June 4 July 4 (8). ICSV22, Florence, Italy, July 15 8