Noise Annoyance Research Articles

Antiquated Canadian Aircraft Noise Guidance—Setting the grounds for encroachment and adverse community impacts

A comprehensive research project at the University of Windsor entitled Prediction and Management of Aircraft Noise Annoyance Around Canadian Airports reviewed multiple components of Canada’s TP 1247 Land Use in the Vicinity of Aerodromes. Using noise, complaints and survey data from Toronto Pearson International Airport, researchers evaluated the Noise Exposure Forecast (NEF) system as a tool for aircraft noise annoyance prediction and management. The NEF metric and its correlation to annoyance was examined as well as applicability of the NEF 30 threshold for the onset of significant annoyance. Further, the guideline for expected community response to noise was tested. The research found that most components of the NEF system are antiquated and in need of revision. A lack of prompt action to update Canadian guidelines for aircraft noise is setting the grounds for conflicts between stakeholders with competing interests and increasing the risks for greater noise impacts on future communities.

Risks and benefits of air taxis as perceived in Germany

In a telephone survey on the acceptance of civilian drones in Germany conducted at the end of 2022 a certain part of questions was dedicated to air taxis explicitly. While the attitude towards civilian drones tended to be slightly more positive than in the preceding study, in the again nationwide representative study attitudes concerning air taxis were revealed to be relatively balanced, with a slight negative tendency. Inferential statistical analyses showed factors such as age, gender, active experience with drones, and interest in environmental protection to be significantly associated with the attitudes towards both, civilian drones and air taxis. According to prior findings on the relevance of noise concerns for drone acceptance in general, the current study asked for some noise related information, revealing subjective noise sensitivity and general noise annoyance being associated with the acceptance of civilian drones as well as air taxis. Evaluating information from answers to free format questions about air taxis, this contribution reveals reasons why in Germany—although the contributing factors are the same—the general attitude towards air taxis is less positive compared to civil drones, and what role noise considerations might play.

Road Traffic Noise Annoyance and Cardiovascular Disease Risk in Population: A Case Series Study in Kota Bharu, Malaysia

Noise pollution can cause annoyance, significantly threatening the population’s health and well-being. This study aimed to find an association between road traffic noise exposure and cardiovascular disease (CVD) risk among residents in Kota Bharu, Malaysia. This descriptive study used a case series approach and surveyed 34 residents in selected residential areas near main roads. An adapted questionnaire was distributed to residents using a purposive sampling method. Questions related to sociodemographic information, self-reporting about CVD, and road traffic noise assessment were asked to investigate the underlying risk factors for CVD. The average score of CVD assessment was classified as moderate risk. No significant association between noise annoyance and CVD was found using multiple linear regression. However, the association between cardiovascular risk and sociodemographic variables, particularly the length of residency at the current address, was statistically significant. Although noise annoyance was not associated with CVD, the length of residency could mediate CVD risk as those living longer in residence might be less vulnerable to the noise. Future longitudinal studies are recommended, which include a noise exposure assessment with a larger sample.

The Effects of Environmental Noise on Annoyance, Stress, and Urine Cortisol Levels Among Residents Living Near Industrial Sites in Bangkok, Thailand

People are exposed to environmental noise each day. It may be annoying, cause stress, induce hormonal changes, and negatively affect long-term health. This study aimed to determine the effects of environmental noise on annoyance, perceived stress, stress symptoms, and urine cortisol in people living in a selected area. This cross-sectional study was conducted from April to October 2022 on 142 participants. Urine samples were collected to determine cortisol levels, and perceived stress, stress symptoms, and environmental noise annoyance were evaluated using questionnaires. Stress symptoms correlated with traffic, industrial, and community noise, but not aircraft noise. Community noise correlated most strongly with all stress symptoms. Only community noise exposure was correlated with perceived stress. People reported that industrial and community noise affected their health and daily activities. Cortisol correlated with only traffic noise annoyance. Environmental noise was associated with stress symptoms and stress hormones. In brief, sound level is not the onlyindicator of stress or health impacts, but annoyance and concern over the effects of noise may negatively affect stress and health.

Residential greenspace exposure, particularly green window-views, is associated with improved sleep quality among older adults: Evidence from a high-density city

Preliminary evidence suggests a potential link between greenspace exposure and better sleep quality. Here we aimed to investigate the specific associations between residential greenspace exposure, green-window views, and sleep quality among older adults and determine whether these associations were mediated through mitigation (i.e., perceived noise annoyance, air pollution, and artificial light pollution) and restoration (i.e., psychological stress) pathways. A total of 1007 older adults with an average age >70 years were recruited from 40 residential communities in the Old City District of Nanjing, China. We developed a set of fine-grained greenspace exposure indices based on 3D point cloud data derived from unmanned aerial vehicle photogrammetry, incorporating vegetation coverage and green volume ratio at the community level and green window ratio at the individual level. Sleep quality was assessed using the Pittsburgh Sleep Quality Index. We examined the complex interrelationships between residential greenspace exposure, environmental stressors (air pollution, artificial light pollution, and noise), perceived mental stress, and sleep quality using multilevel linear regression models. The results suggested the following: (1) Vegetation coverage, green volume ratio, and green window ratio were significantly associated with sleep quality in older adults. (2) The green window ratio was more strongly associated with improved sleep quality than other greenspace exposure metrics. (3) These associations may be partially explained by noise mitigation and mental stress reduction. In conclusion, it seems advantageous to consider immediate residential greenspace, particularly through green-window views, as part of the interventions aimed at supporting sleep quality improvement among older adults.

Relationship among Noise Exposure, Noise Annoyance, Emotional Intelligence, and Cognitive Emotional Regulation: AGeneralized Structural Equation Modeling

Background and Aim: There is evidence of associations between noise exposure and psychological outcomes from noise annoyance. This study aims to examine the mediating role of noise annoyance in the relationship of noise exposure with Emotional Intelligence (EI) and Cognitive Emotion Regulation (CER). Methods: This is a cross-sectional study that was conducted on 58 male workers of a lead mine in Yazd, Iran. Noise exposure was determined based on ISO 9612:2009. Noise annoyance was assessed using the ISO/TS 15666:2003’s numerical rating scale. The Schutte Self-Report Emotional Intelligence Test (modified version) and the Cognitive Emotion Regulation Questionnaire (CERQ) were used for data collection. Mann-Whitney U test, correlation test, and Generalized Structural Equation Modeling (GSEM) were used to analyze the data. Results: The mean age of workers was 35.78±7.10 years. A significant relationship was found between noise annoyance and noise exposure, such that a unit increase in noise exposure had a multiplicative effect on the odds of experiencing more annoyance (p<0.001). Also, for every one-unit increase in noise annoyance, mean scores for EI and CER decreased by 0.192 and 0.172, respectively. Conclusion: Noise exposure is directly related to noise annoyance and indirectly related to EI and CER. Further studies in this area are recommended to clarify the issue and the relationships between these variables. Keywords: Noise; noise exposure; emotional intelligence; cognitive psychology

Audiovisual effects of roadside tree plantings on perception of road traffic sounds

This study investigated the psychological influence of the surrounding landscapes related to the plantings along roadside areas on the subjective impressions of road traffic noise. Herein a subjective evaluation scheme incorporating the semantic differential and magnitude estimation methods was adopted. Under the virtual experimental environment, the conditions with only a visual stimulus and with both visual and auditory stimuli were comparatively evaluated. The results revealed significant differences between when only the visual environment was presented and when the auditory environment was also presented. It suggested that a realistic evaluation of the living environment is possible only when both the visual and auditory environments are explored together. Tree plantings located along the road were found to interact with the SPL of the road traffic noise and the urban environment visible through the windows. It indicated that the psychological noise reduction effect of plantings on noise annoyance varies significantly depending on the audiovisual environment.

Annoyance penalty due to the spectrum shape of wideband noise

Environmental noise exposure is usually evaluated by measuring the A-weighted equivalent sound pressure level, LAeq [dB]. However, it cannot alone explain the resulting noise annoyance. It is common to apply penalties, such as +5 dB correction, to measured LAeq when the noise contains annoyance accentuating features, such as tonality or impulsiveness. Although previous studies suggest that the noise spectrum also influences annoyance, and spectrum is easy measure, the need of penalty due to spectral shape of noise has not been studied. Our study investigated the relationship between spectral shape and annoyance. The purpose was to determine whether spectrum-related penalties should be integrated with measured LAeq values. We conducted a psychoacoustic laboratory experiment involving 40 participants. We collected their annoyance ratings for 23 spectrally different steady-state wideband noises presented at three LAeq levels, 32, 40, and 48 dB. In addition, annoyance ratings were collected for a spectrally neutral reference noise played within 28–60 dB in 4 dB steps to enable the determination of penalty. The annoyance strongly depended on the spectrum of noise, for all three LAeq levels. Higher concentrations of sound energy in high frequencies were associated with increased annoyance ratings across all three LAeq levels. The penalty values of spectrally modified noises varied within −2 to +12 dB. The penalty values exhibited minimal dependence on LAeq. That is, the same spectrum-related penalties were valid at least within 32–48 dB. Our findings suggest that noise spectrum also deserves a penalty procedure to better explain human perception of noise.

Auralization of electric vehicles for the perceptual evaluation of acoustic vehicle alerting systems

Electric vehicles (EVs) typically emit little noise at low driving speeds, which increases the risk of accidents for vulnerable road users such as pedestrians. To reduce this risk, regulations demand that newly sold EVs have to be equipped with an acoustic vehicle alerting system (AVAS), which radiates artificial warning sounds. Developing AVAS sounds that provide a sufficient warning capability while limiting traffic noise annoyance requires laboratory listening experiments; such experiments need accurate auralization methods. Even though several auralization tools are already established in the research field, those frameworks require additional data to simulate EVs. This paper presents an electric vehicle auralization toolchain combined with an open-access database, including AVAS measurements, synthesis algorithms, and numerically calculated sound source directivities for three different electric passenger cars. The auralization method was validated numerically and in a listening experiment, comparing simulated EV passages to binaural in-situ recordings. The results of this perceptual validation indicate that stimuli generated with the presented method are perceived as slightly less plausible than in-situ recordings and that they result in a similar distribution of annoyance ratings but a higher perceived vehicle velocity compared to the reference recordings.

Wind farm noise prediction and auralization

This work presents the application and validation of a novel auralization approach for the evaluation of wind turbine noise annoyance under diverse conditions. The approach is based on the decomposition of each turbine blade into elementary short-segment sources, whose acoustic radiation in the far field is obtained by coupling Amiet’s emission model with the Harmonoise engineering model for outdoor sound propagation. The transfer functions between the elementary source positions and receivers are obtained. Then, the average and instantaneous sound pressure levels are calculated over one blade rotation. The realism of the audio signals is evaluated through listening tests with audio signals of the real and simulated environments. The predicted noise spectra from five wind turbines capture well the measured trends and the absolute levels. Finally, we present a study of the weather effects on noise emissions and propagation by using the numerical model developed.

Спектральные характеристики сигналов для их классификации по уровню раздражительности методами машинного обучения

The popularity of using machine learning methods to classify audio signals continues to grow. Although the recognition of qualitative parameters of noise is becoming increasingly important, its negative aspects have been rarely studied. Methods for determining the level of noise annoyance are presented. These methods can be useful for creating systems that control the noise level of the environment, as well as for evaluating not only acoustic characteristics, but also aesthetic and cognitive effects exerted by noise on a person. A comparison of the results of a neural network in determining the degree of noise annoyance in terms of the psychoacoustic parameter using various spectral characteristics is presented.

The Relationship between the Environmental Noise Intensity, Feeling and Annoyance with the Shiftwork in the Emergency Department

Background: Noise pollution is a serious issue in hospitals, especially in emergency departments where high noise levels from emergency patients and treatments can negatively affect medical personnel and patients. This study aimed to measure noise levels during day and night shifts in three major hospitals affiliated with Tehran University of Medical Sciences (Imam Khomeini, Shariati, and Sina hospitals) and investigate the level of annoyance experienced by medical staff.
 Methods: In this cross-sectional studyTES-1351B sound level meter was used to measure sound pressure levels and the measurement stations were determined according to ISO 9612 standard. A general questionnaire was used to determine demographic characteristics. Also, by a valid self-reporting questionnaire, the feeling about environmental noise intensity and noise annoyance was measured. Statistical analysis was done by SPSS software using ANOVA and t-test.
 Results: The average sound pressure level in the emergency departments of the studied hospitals was 67.940±7.70 dB. Significant differences were found between morning and evening shift noise levels. (p-value=0.001). The highest average sound pressure level occurred during the evening shift with an average of 72.382±4.35 db. Also, there was a significant difference between the feeling about environmental noise intensity and noise annoyance in Imam Khomeini and Sinai hospitals respectively, (p-value=0.037) (p-value=0.011).
 Conclusion: The study concludes that noise pollution in the emergency departments of these hospitals needs attention. Implementing administrative and technical-engineering measures to reduce noise pollution is essential to enhance the well-being of medical staff and patients and ensure a more satisfactory healthcare environment.

Comparison between noise annoyance and noise sensitivity

This study examined the relationship between noise sensitivity and noise annoyance. As part of a collaboration between the National Institute of Advanced Industrial Science and Technology in Japan and the National Research Council Canada related to the acoustic requirements for dwellings intended for aging in place, a pilot subjective study of noise annoyance was conducted. Sixty participants in the subjective study were asked to also complete a shortened Weinstein Noise Sensitivity Scale. The results were divided into two groups based on their hyper- or hypo-sensitivity to noise. The results showed that the noise annoyance of impact sound was perceived differently by the hyper-sensitivity group and the hypo-sensitivity group.

Acoustical environments in the textile industry facilities: A case study of Malatya Province, Türkiye

In the past few decades, the textile industry in Türkiye has been developing rapidly with raw materials, industrialization, and employment opportunities. The use of complex machine processes in mass production methods in the textile industry, creates working conditions with high noise levels are created. In this paper, indoor acoustic performance in the textile industry was discussed and the interpretation of the acoustic environment by the employees was analyzed. The textile industry facility in Malatya, Türkiye was examined as a case study. The employees' daily noise exposure levels (LEX,8h) and sound pressure levels were measured. Additionally, Weinstein's Noise Sensitivity Scale (WNSS) and noise annoyance structured questionnaire were applied to the employees. The highest noise exposure level was 92,8 dB, and the lowest noise exposure level was 86,9 dB. In conclusion, the statistical relationship between noise sensitivity and noise annoyance of employees with the demographic properties was examined and the noise annoyances were analyzed in detail. It was found that there was a significant and positive relationship between the noise sensitivity and noise annoyance of the employees (r = 0,523, p = 0,000 < 0,05). Suggestions have been developed to improve indoor acoustic performance and reduce noise in the textile industry.

Experimental study on the effect of visual information of source image to evaluate the annoyance of aircraft noise

Laboratory tests in anechoic chambers are effective for evaluating environmental noise. In the actual environment, it is said that human reactions are greatly influenced not only by a sense of hearing but also by various senses, especially visual sensation. In this study, we experimentally evaluated the annoyance of environmental noise using an audio-visual simulation system that combines a three-dimensional sound field system in an anechoic room and a video playback system equipped with a dome-shaped screen. Previous studies have shown that the annoyance of traffic noise changes depending on the image presented, but aircraft noise is less affected by visual effects than other traffic noises. Therefore, in this study, we focused on aircraft noise and made experimental investigations. We considered two reasons why the annoyance evaluation of aircraft noise seems to be less affected by vision: the small size of the visible image, and the high sound power level relative to the image. Accordingly, we experimentally evaluated the difference in perception of annoyance due to changes in the image size by presenting images of artificially changed sizes of aircraft images as stimuli.

Introducing ICBEN's new socio-acoustic survey archive ISAR

The International Committee on Biological Effects of Noise (ICBEN) has recently started an international archive of original survey response data from so called socio-acoustic noise surveys, named ISAR (ICBEN Socio-Acoustic Survey Archive). The ISAR archive caters to noise effects researchers around the globe and enables pooled analyses, establishment of generalized exposure-response relationships, trend analyses both spatially and temporally, as well as cross-cultural comparisons of self-reported noise reactions (noise annoyance and noise-induced sleep disturbances in particular). The data in the archive will be freely accessible. Data in the ISAR archive are fully anonymous in order to meet the pertinent data protection regulations in most countries. The ISAR archive is curated by ICBENs officers and the team chairs of Team 6 (Community response to noise and annoyance). The ISAR archive explicitly collects only raw survey response data, rather than data that have been aggregated on a higher level. We are constantly seeking to extend the archive with new study data and thus, every new contribution is highly welcome. In this talk, we would like to publicize and promote the archive and encourage our colleagues to share their survey data with the archive.

Noise by neighbours: an update

RIVM conducts an annual survey of residents' perceptions of their living environment. This includes monitoring data on residents' perception of noise, odours and vibrations. Between 2019 and 2022, more than 8,000 Dutch residents aged 16 and over took part in these surveys. Online questionnaires presented people with a range of possible sources of annoyance and sleep disturbance in their homes and neighbourhoods. Road traffic noise is a major source of severe annoyance and sleep disturbance. Mopeds and motorcycles in particular cause severe noise annoyance. Compared to 2016, more people experience severe annoyance from the sound of vans. Road traffic also causes annoyance through vibrations. Neighbours are the second most important source of noise annoyance and the most important source of severe odour annoyance in the Netherlands. The latter is mainly due to odours from fireplaces, fire pits and barbecues. Neighbours' activities also cause severe annoyance due to vibrations.

Subjective evaluation on vibratory feeling to noises containing a low-frequency tonal component

Machinery noises sometimes contain low-frequency tonal components and cause an increase in noise annoyance due to the tones. It is also known that the oppressive or vibratory feeling is a unique sensation to low-frequency sounds below 100 Hz, which may also account for the increase in noise annoyance. In this study, auditory experiments were conducted to investigate the relationship between the intensity and frequency of the tonal components and the vibratory feeling. The test stimuli were broadband noises that simulated environmental noises with one additional tonal component. The frequency and the tonal audibility were varied in the range of 31.5 to 400 Hz, and 0, 3, 6, 9, and 12 dB, respectively. As a result, the energy of the component below 100 Hz was found to be strongly correlated with the vibratory feeling. Furthermore, the relationship between sound pressure level and the vibratory feeling was examined using LSL weighting characteristics, which have been proposed for the evaluation of vibration and oppression sensation caused by low-frequency sound.

Annoyance Prediction of Civil Aircraft Cabin Noise Based on Generalized Additive Models

Noise in civil aircraft cabin is a major contributor to passenger comfort. It is of great significance to predict the noise annoyance by developing a model. However, the low accuracy of linear model and the poor intelligibility of the neural network are the critical problems to be solved. Generalized additive models (GAMs) have become a leading choice for explainable machine learning. This study examines the effectiveness of GAMs in noise annoyance prediction. First, the annoyance of the cabin noise was collected through subjective listening test. Subsequently, three physical acoustic features (sound pressure level, A-weighted sound pressure level, preferred speech interference level) and five psychoacoustic features (loudness, sharpness, roughness, fluctuation strength, tonality) were applied to describe the stimuli. In the third step, three algorithms were used to construct GAMs based on annoyance (dependent variable) and feature parameters (independent variables), and the prediction accuracy was computed by ten-fold cross-validation. The result indicated that GAMs have higher prediction accuracy than linear regression model. The importance of features was evaluated, which is more intelligible than the neural network. This study provides the first assessment of GAMs in the annoyance prediction of civil aircraft cabin noise, and the findings may be of assistance to engineering noise control.

Subjective evaluation test on the effect of tonal components on broadband noise

Environmental noise sometimes contains tonal components, and it has been pointed out that this can be responsible for increasing the annoyance of noise. In Japan, noise problems related to tonal noises generated from wind turbines and heat pump systems have recently been occurring. To solve the noise problem, it is necessary to quantitatively understand the effect of tonal components on noise annoyance. In this study, annoyance evaluation experiments were conducted using broadband noise containing a tonal component. Four types of noise were used for the auditory test: white noise, pink noise, and low-frequency prominent noise that simulated indoor- and outdoor environmental noise. The frequencies of tonal components added to the broadband noise were from 50 to 2000 Hz, with intensities where the tonal audibility was 0, 5, 10, and 15 dB. The results show that the annoyance increases with the intensity of the tonal component, but the amount of increase depends on the frequency characteristics of the background noise and the tonal frequency. This increase in annoyance was quantified as a penalty in A-weighted sound pressure level.