Aircraft noise annoyance modeling: Consideration of noise sensitivity and of different annoying acoustical characteristics
TL;DR: In this paper, a verbalization task was performed by the participants of the experiment to collect their whole impression concerning the aircraft flyover noises for which they rated annoyance, and four combinations of noise indices were used to propose multilevel annoyance models, in combination with the individual noise sensitivity.
Abstract: Noise annoyance due to aircraft flyover noise was assessed under laboratory conditions. The main objectives of the study were: (i) to identify influential acoustical features of noise annoyance, (ii) to propose noise indices to characterize these acoustical features and (iii) to enhance annoyance models including influential acoustical and non-acoustical variables. Therefore, a verbalization task was performed by the participants of the experiment to collect their whole impression concerning the aircraft flyover noises for which they rated annoyance. This verbalization task highlights that noise annoyance was influenced by three main acoustical features: (i) the spectral content, (ii) the temporal variation and (iii) the perceived sound intensity. Four combinations of noise indices were used to propose multilevel annoyance models, in combination with the individual noise sensitivity. Noise sensitivity was found to highly contribute to annoyance models and should therefore be considered in future studies dealing with noise annoyance due to aircraft noise. Different combinations of noise indices coupled with noise sensitivity were found to be promising for future studies that aim to enhance current annoyance models.
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TL;DR: In this article, a multivariate model was developed to predict the probability of invoking a high noise annoyance response due to combined water sound and road traffic noise exposure, where participants were presented with a series of acoustical stimuli before being asked to assign their annoyance ratings.
Abstract: People in an urban environment are exposed to different types of natural and man-made sounds. Human sound perceptions due to exposure to a single noise source, in particular road traffic and aircraft noises, have been investigated for a long time. However, only very few studies have been focused on exposure to a combination of sound sources. Also, there is a lack of multivariate models that can help to predict the preferences or annoyance responses as a result of adding a wanted sound to an unwanted sound. Accordingly, this study aimed at developing a multivariate model to predict the probability of invoking a high noise annoyance response due to combined water sound and road traffic noise exposure. A series of laboratory experiments were performed. Participants were presented with a series of acoustical stimuli before being asked to assign their annoyance ratings. Results suggested that other than acoustical properties like sound pressure levels, personality traits were found to exert considerable influences on the maximum likelihoods of the model prediction and thus should not be excluded from the model specification form. Also, the quality of the acoustical environment could be improved by adding water sounds to road traffic noises at high levels. The capability of stream sound to moderate noise annoyance was found to be slightly stronger than that of fountain sound. In addition, the formulated multivariate model enables to reveal the tradeoff decisions performed by people. An increase in the SPL of road traffic noise by 1 dB was considered to be equivalent to a reduction in the SPL of water source by 1.7 dB for a given probability value. Results arising from this study should provide valuable insights on understanding how humans respond to the combined water sound and road traffic noise exposure.
15 citations
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TL;DR: In this article, the authors describe the basis of community engagement as a parallel approach to mitigate noise issues around airports, setting the focus on the noise metrics and the involvement techniques that must be implemented to engage the community.
Abstract: It seems obvious that the noise levels in local communities surrounding airports influences the level of acceptance of an airport. What is not so evident is the effect of non-acoustic factors that increase the societal rejection, like the lack of sensitivity and empathy from the authorities and airport managers, the lack of trust in them, the lack of information and transparency, the perception of being excluded from the decision making and so on. Complementary to the traditional strategies based on the reduction of noise exposure, a community engagement and involvement approach brings new possibilities to manage noise around airports, trying to exploit the non-acoustic factors that have negatively affected the community response. Building trust among the stakeholders is a key factor in this strategy, and it must be based on a long-term, honest, and transparent two-way communication. In the last decade, the huge growth of the information and communication technologies has opened new opportunities that the aviation organizations and stakeholders are starting to explore in depth trying to reduce the degree of rejection of the airport, which may compromise the utilization of existing and future infrastructure. In this review, we make a short introduction on aircraft noise health effects, to focus annoyance and the influence that non-acoustic factors on it. Then, we describe the basis of community engagement as a parallel approach to mitigate noise issues around airports, setting the focus on the noise metrics and the involvement techniques that must be implemented to engage the community.
14 citations
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TL;DR: The proposed comprehensive approach to effectively reduce the impact of perceived air traffic noise in the future is suggested and it is shown that spatially distributed receivers need to be considered for a reliable low-noise aircraft technology evaluation.
Abstract: Residents living in the vicinity of airports are exposed to noise from departing and approaching aircraft. Noise may be reduced by introducing novel aircraft technologies into vehicle retrofit, aircraft design and flight procedures. Nowadays, noise assessment and communication of noise are accomplished using conventional noise indicators that consider neither the perception of sound, nor its health effects. To overcome these limitations, this article presents a more comprehensive approach that supports the movement for perception-influenced design in order to reduce the negative environmental impacts and adverse health effects caused by increased air traffic noise. By means of auralization (the acoustical counterpart of visualization), possible future changes can be evaluated by considering the human perception of sound. In this study, in a virtual acoustic environment flyovers of different aircraft types and flight procedures are auralized for ground-based receiver locations, and subsequently evaluated in a psychoacoustic laboratory experiment with respect to short-term noise annoyance. Flight approaches of an existing reference aircraft, a possible low-noise retrofitted vehicle and a future low-noise vehicle design were simulated along standard and tailored flight procedures. To create realistic listening experiences of synthetic flyovers, auralization technologies were further developed regarding source synthesis, transitions between aircraft conditions, sound propagation effects and immersive sound reproduction. Listening experiments revealed significant annoyance reductions for low-noise aircraft types and tailored flight procedures, and that maximum benefit is achieved by the combined optimization of aircraft design and flight procedure. Further, it is shown that spatially distributed receivers need to be considered for a reliable low-noise aircraft technology evaluation. The reduction potential in terms of perceived noise by retrofitting current vehicles and designing new vehicle architectures is thus demonstrated. These findings suggest applying the proposed comprehensive approach to effectively reduce the impact of perceived air traffic noise in the future.
12 citations
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TL;DR: In this article, noise annoyance is among the most important human responses to noise, which is one of the main health risk factors which has been recently considered in many researches, such as wind turbines.
Abstract: Noise, emitted by wind turbines, is one of the main health risk factors which has been recently considered in many researches. Noise annoyance is among the most important human responses to noise. ...
12 citations
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TL;DR: The Aures tonality method significantly outperforms the EPNL tone correction method when assessing the subjective response to aircraft noise during take-off with the presence of multiple complex tones.
Abstract: The Effective Perceived Noise Level (EPNL) is the primary metric used for assessing subjective response to
aircraft noise. The EPNL comprises calculation of the Perceived Noise Level (in PNdB), and takes into
account flyover duration and the presence of pure tones to arrive at an adjusted EPNL value. With the
presence of a single significant tone, EPNL has been found to be reasonably effective for the assessment
of aircraft noise annoyance. Several authors have, however, suggested that EPNL is not capable of quantifying
the subjective response to aircraft noise that contains multiple complex tones. The noise source
referred to as ‘‘Buzz-saw” noise is a typical example of complex tonal content in aircraft noise with an
important effect on both cabin and community noise impact. This paper presents the results of a series
of listening tests where a number of participants were exposed to samples of aircraft noise with six variants
of aircraft engines, assumed representative of the contemporary twin engine aircraft fleet. On the
basis of the findings of these listening tests, the Aures tonality method significantly outperforms the
EPNL tone correction method when assessing the subjective response to aircraft noise during take-off
with the presence of multiple complex tones. The participants reported ‘high pitch’ as one of the least
preferable aircraft noise characteristics, and consequently, the psychoacoustics metric Sharpness was
found to be another important contributor to subjective response to the noise of two specific aircraft
engine groups (out of the six considered). The limitations of Aures tonality are discussed, in particular
for aircraft noise with both a series of complex tones spaced evenly across the frequency spectrum with
relatively even sound levels and less subjectively dominant single frequency tones (compared to broadband
noise). In line with these limitations, further work is proposed for more effective assessment of subjective
response to aircraft noise containing significant tonal content in the form of numerous closely
spaced or other complex tones.
12 citations
Cites background from "Aircraft noise annoyance modeling: ..."
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References
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01 Apr 2002
TL;DR: This work focuses on the development of a single model for Multilevel Regression, which has been shown to provide good predictive power in relation to both the number of cases and the severity of the cases.
Abstract: 1. Introduction to Multilevel Analysis. 2. The Basic Two-Level Regression Model. 3. Estimation and Hypothesis Testing in Multilevel Regression. 4. Some Important Methodological and Statistical Issues. 5. Analyzing Longitudinal Data. 6. The Multilevel Generalized Linear Model for Dichotomous Data and Proportions. 7. The Multilevel Generalized Linear Model for Categorical and Count Data. 8. Multilevel Survival Analysis. 9. Cross-classified Multilevel Models. 10. Multivariate Multilevel Regression Models. 11. The Multilevel Approach to Meta-Analysis. 12. Sample Sizes and Power Analysis in Multilevel Regression. 13. Advanced Issues in Estimation and Testing. 14. Multilevel Factor Models. 15. Multilevel Path Models. 16. Latent Curve Models.
5,390 citations
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03 Dec 1990
TL;DR: This description of the processing of sound by the human hearing system presents the quantitative relationship between sound stimuli and auditory perceptions in terms of hearing sensations, and implements these relationships in model form.
Abstract: Stimuli and Procedures * Hearing Area * Information Processing in the Auditory System * Masking * Pitch and Pitch Strength * Critical Bands and Excitation * Just-Noticeable Sound Changes * Loudness * Sharpness and Sensory Pleasantness * Fluctuation Strength * Roughness * Subjective Duration * Rhythm * The Ear's Own Nonlinear Distortion * Binaural Hearing * Examples of Application.
2,104 citations
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TL;DR: Better estimates of the confidence intervals due to the improved model of the relationship between annoyance and noise exposure are provided, which is easier to use for practical calculations than the model itself.
Abstract: We present a model of the distribution of noise annoyance with the mean varying as a function of the noise exposure. Day-night level (DNL) and day-evening-night level (DENL) were used as noise descriptors. Because the entire annoyace distribution has been modeled, any annoyance measure that summarizes this distribution can be calculated from the model. We fitted the model to data from noise annoyance studies for aircraft, road traffic, and railways separately. Polynomial approximations of relationships implied by the model for the combinations of the following exposure and annoyance measures are presented: DNL or DENL, and percentage "highly annoyed" (cutoff at 72 on a scale of 0-100), percentage "annoyed" (cutoff at 50 on a scale of 0-100), or percentage (at least) "a little annoyed" (cutoff at 28 on a scale of 0-100). These approximations are very good, and they are easier to use for practical calculations than the model itself, because the model involves a normal distribution. Our results are based on the same data set that was used earlier to establish relationships between DNL and percentage highly annoyed. In this paper we provide better estimates of the confidence intervals due to the improved model of the relationship between annoyance and noise exposure. Moreover, relationships using descriptors other than DNL and percentage highly annoyed, which are presented here, have not been established earlier on the basis of a large dataset.
710 citations
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TL;DR: A review of the relationship between noise exposure and the subjective reactions to it was conducted by as mentioned in this paper, which indicated that remarkably similar results have been obtained across different nationalities with different measurement techniques.
Abstract: Social surveys of the relationship between noise exposure and the subjective reactions to it were reviewed This review indicated that remarkably similar results have been obtained across different nationalities with different measurement techniques Only a small percentage (typically less than 20%) of the variation in individual reaction is accounted for by noise exposure Analysis of potential errors in both measurement of noise and reaction suggests that elimination of errors would only slightly increase the observed correlations Variables, such as attitude to the noise source and sensitivity to noise, account for more variation in reaction than does noise exposure The weaker relationship between noise exposure and attitude than between reaction and attitude suggests that the attitude/reaction relationship is not entirely due to noise exposure causing a change in attitude itself Noise/reaction correlations based on individual data are significantly lower in studies of impulsive noise than nonimpulsive noise This may be caused, in part, by the restricted range of noise exposure studied in some socioacoustic investigations of impulsive noise However, the significantly higher correlations of attitude and reaction in impulsive noise studies suggest that attitude plays an even larger part, while noise exposure plays a lesser part in determining reaction to impulsive noise, relative to nonimpulsive noise
295 citations
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TL;DR: Noise sensitivity has relatively little influence on reactions to nonenvironmental conditions, and its relationship with noise exposure, its working mechanism, and the scope of its influence are discussed.
Abstract: This article integrates findings from the literature and new results regarding noise sensitivity. The new results are based on analyses of 28 combined datasets (N=23 038), and separate analyses of a large aircraft noise study (N=10939). Three topics regarding noise sensitivity are discussed, namely, its relationship with noise exposure, its working mechanism, and the scope of its influence. (1) A previous review found that noise sensitivity has no relationship with noise exposure. The current analyses give consistent results, and show that there is at most a very weak positive relationship. (2) It was observed earlier that noise sensitivity alters the effect of noise exposure on noise annoyance, and does not (only) have an additive effect. The current analyses confirm this, and show that the relation of the annoyance score with the noise exposure is relatively flat for nonsensitives while it is steeper for sensitives. (3) Previous studies showed that noise sensitivity also influences reactions other than noise annoyance. The current analyses of the aircraft noise study extend these results, but also indicate that noise sensitivity has relatively little influence on reactions to nonenvironmental conditions. © 2003 Acoustical Society of America.
192 citations
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