Human response to aircraft noise

The human auditory system and the perception of sound are discussed. The major concentration is on the annnoyance response and methods for relating the physical characteristics of sound to those psychosociological attributes associated with human response. Results selected from the extensive laboratory and field research conducted on human response to aircraft noise over the past several decades are presented along with discussions of the methodology commonly used in conducting that research. Finally, some of the more common criteria, regulations, and recommended practices for the control or limitation of aircraft noise are examined in light of the research findings on human response

Spatio-Temporal Analysis of Urban Acoustic Environments with Binaural Psycho-Acoustical Considerations for IoT-based Applications

Sound pleasantness or annoyance perceived in urban soundscapes is a major concern in environmental acoustics. Binaural psychoacoustic parameters are helpful to describe generic acoustic environments, as it is stated within the ISO 12913 framework. In this paper, the application of a Wireless Acoustic Sensor Network (WASN) to evaluate the spatial distribution and the evolution of urban acoustic environments is described. Two experiments are presented using an indoor and an outdoor deployment of a WASN with several nodes using an Internet of Things (IoT) environment to collect audio data and calculate meaningful parameters such as the sound pressure level, binaural loudness and binaural sharpness. A chunk of audio is recorded in each node periodically with a microphone array and the binaural rendering is conducted by exploiting the estimated directional characteristics of the incoming sound by means of DOA estimation. Each node computes the parameters in a different location and sends the values to a cloud-based broker structure that allows spatial statistical analysis through Kriging techniques. A cross-validation analysis is also performed to confirm the usefulness of the proposed system.Ingeniería, Industria y Construcció

How urban noise can be influenced by the urban form

The noise propagation is influenced by the behavior of the sound trajectory. The temperatures, the wind, the type of soil are other elements that influence the noise propagation. But the mainly causer of trajectory alterations are the barriers or the urban obstacles. Therefore the study will allow monitoring the interaction of noise propagation effects in the studied urban forms. Using urban indicators and a noise prediction model is possible to associated noise categories to urban façades forms. The effects of noise in façades can be minimized in advance with the creation of different scenarios and foresee in a preliminary phase the most exposed façade to a higher noise level

The influence of urban form on facades noise levels

The urban form affects directly the natural habitats, ecosystems and the different species. Indirectly the urban form influences the behavior of the trajectory, which in turn affects the air quality, the global climate and of course the noise propagation. This paper seeks to address the problems of the urban environment as an area of interaction between urban forms and urban noise. This interaction is intended to be monitored by urban indicators, comparing the effects of noise propagation in model of urban forms. The model of noise prediction (NMPB96), allowed to develop studies about noise in facades (Ld, level of noise during the day), resulting in colors associated to noise categories. The study will allow the creation of different scenarios and foresee still in the draft fase, the facades exposed to a higher noise level. The effects of noise in facades can be then minimized in advance, by adjusting the layout of their typology.(undefined

Probabilistic modelling of the temporal variability of urban sound levels

Relying on monitoring networks to compute or improve noise maps is an increasingly used approach. To be able to use this approach to provide adequate temporal treatments, a good understanding of the temporal variations within urban sound level time series is required. This paper provides an in-depth statistical analysis of the temporal characteristics of urban sound environments, on the basis of a wide measurement campaign during 8 month, at 23 measurement stations in Paris, which cover a large variety of urban sound environments. The time series of sound levels were recorded continuously with a 125 ms-time resolution, from which LA(50,1h) values were extracted. In total, 72 time-slots of interest are defined (24 1h-periods covering all days of the week). The statistical analysis determines for each station the Daily Average Noise Pattern (DANP), and for each of the 72 time-slots the 1h-Generalized Extreme Values distributions. The Generalized Extreme Values distributions are found to outperform the normal distributions to model the LA(50,1h) distributions. In addition, the average sound level differences between these 72 1h-time periods are calculated along with their variability, resulting in 72x72 delta matrices that describe the temporal relations between sound levels. This database is then used to develop two models, which aim to estimate DANP based on a limited amount of measurements. The model M1 relies on the delta matrices, whereas the model M2 consists of a weighted average of the DANP that are stored in the database in which the weights are based upon measures of similarity between the stations. Both models rely on probability density functions, and provide a measure for the reliability of the estimated noise levels. A test of both modelling approaches through simulated measurements shows that the model M1 seems to be more robust in case measurements are inaccurate. Beyond these two models, the proposed database could serve in the development of further models that aim to estimate sound levels based on a limited amount of measurements

Short-term exposure sequences and anxiety symptoms: A time series clustering of smartphone-based mobility trajectories

Background Short-term environmental exposures, including green space, air pollution, and noise, have been suggested to affect health. However, the evidence is limited to aggregated exposure estimates which do not allow the capture of daily spatiotemporal exposure sequences. We aimed to (1) determine individuals’ sequential exposure patterns along their daily mobility paths and (2) examine whether and to what extent these exposure patterns were associated with anxiety symptoms. Methods We cross-sectionally tracked 141 participants aged 18–65 using their global positioning system (GPS) enabled smartphones for up to 7 days in the Netherlands. We estimated their location-dependent exposures for green space, fine particulate matter, and noise along their moving trajectories at 10-min intervals. The resulting time-resolved exposure sequences were then partitioned using multivariate time series clustering with dynamic time warping as the similarity measure. Respondents’ anxiety symptoms were assessed with the Generalized Anxiety Disorders-7 questionnaire. We fitted linear regressions to assess the associations between sequential exposure patterns and anxiety symptoms. Results We found four distinctive daily sequential exposure patterns across the participants. Exposure patterns differed in terms of exposure levels and daily variations. Regression results revealed that participants with a “moderately health-threatening” exposure pattern were significantly associated with fewer anxiety symptoms than participants with a “strongly health-threatening” exposure pattern. Conclusions Our findings support that environmental exposures’ daily sequence and short-term magnitudes may be associated with mental health. We urge more time-resolved mobility-based assessments in future analyses of environmental health effects in daily life

An investigation into human response to unmanned aerial vehicle noise

It is predicted that urban air mobility, including the use of small to medium sized unmanned aerial vehicle (UAV) delivery systems, will be introduced into cities across the globe within the next 15 years. It is known, however, that noise is one of the main limiting factors for the wider adoption of these vehicles. Neither the metrics nor the methods used for conventional aircraft seem to be optimal for this novel source of noise. This research will aid in developing suitable psychoacoustic methodologies and metrics, specifically designed to quantify the community noise impact of these vehicles. This paper describes a psychoacoustic experiment used to gather participant responses to UAV sound recordings, performing a variety of different operations at differing distances. Results from this psychoacoustic experiment will be used to correlate perceptions of UAV noise with objective sound quality metrics, and build new regression relationships that could describe the impact of a given UAV on a community, as well as give insight into the key sound quality metrics that contribute to the perceived annoyance. Future extension to the research may include assessing the impact of introducing drone noise to a variety of soundscapes, evaluating the differences in psychoacoustic responses when introducing more accurate reproduction methods, such as virtual reality systems, and how these could be incorporated into a standardised human response measurement procedure

New Indicators for the Assessment and Prevention of Noise Nuisance

This Special Issue was launched to promote a subject that is deserving of more attention: the study of new metrics, indicators or evaluation methods for noise exposure, and the relationship of noise with annoyance or other health effects, thus not relying only on an average noise exposure measure. This Special Issue on the theme of the New Indicators for the Assessment and Prevention of Noise Nuisance has attracted the interest of authors from all over the world, with the publication of two reviews and two communications, as well as original research papers. Progress has been made in the investigated topic; however, it is still necessary to increase the awareness of the population, both in geographical terms and for workers in specific sectors, such as the marine industry. It emerged that it is essential to carry out future studies that distinguish better between different sound sources with respect to their sound quality in terms of frequency, time pattern (fluctuation, emergence), and psychoacoustic indices, because a differential human reaction to sound sources is increasingly evident. More longitudinal studies are required. However, cross-sectional studies employing a more detailed soundscape description (including background) by competing sound indices are also useful to further the required knowledge to understand the human response in terms of the broad spectrum of potential adverse effects on health and quality of life

Predictive Modelling of Complex Urban Soundscapes: Enabling an engineering approach to soundscape design

Conventional noise control methods typically limit their focus to the reduction of unwanted noise, ignoring the benets of positive sounds and struggling to reflect the totality of noise impacts. Modern approaches to achieve improved health outcomes and public satisfaction aim to incorporate the perception of an acoustic environment, an approach known as ‘soundscape’. When attempting to apply soundscape in practice, it is apparent that new methods of analysing soundscape perception in urban spaces are required; in particular, a predictive model of the users’ perceptual response to the acoustic environment is necessary. This thesis is intended to enable a move towards applying engineering approaches to soundscape design. This is achieved by developing predictive models of soundscape perception through empirical studies examining a large scale soundscape assessment database. The results are presented in three parts: first, the data collection protocol and modelling methods developed for this work are presented; the second part demonstrates an initial development and application of a predictive soundscape model; the final section expands upon this initial model with two empirical studies exploring the potential for additional information to be included in the model. This thesis begins by establishing a protocol for large scale soundscape data collection based on ISO 12913-2 and the creation of a database containing 1,318 responses paired with 693 binaural recordings collected in 13 locations in London and Venice. The first study then presents an initial development and application of a model designed to predict soundscape perception based on psychoacoustic analysis of the binaural recordings. Through the collection of an additional 571 binaural recordings during the COVID-19 lockdowns, sound level reductions at every location are seen, ranging from a reduction of 1.27 dB(A) in Regents Park Japan to 17.33 dB(A) in Piazza SanMarco, with an average reduction across all locations of 7.27 dB(A). Multi-level models were developed to predict the overall soundscape pleasantness (R2 = 0.85) and eventfulness (R2 = 0.715) of each location and applied to the lockdown recordings to determine how the soundscape perception likely changed. The results demonstrated that perception shifted toward less eventful soundscapes and to more pleasant soundscapes for previously traffic-dominated locations but not for human- and natural-dominated locations. The modelling process also demonstrated that contextual information was important for predicting pleasantness but not for predicting eventfulness. The next stage of the thesis considers a series of expansions to the initial model. The second piece of empirical work makes use of a dataset of recordings collected from a Wireless Acoustic Sensor Network (WASN) which includes sound source labels and annoyance ratings collected from 100 participants in an online listening study. A multilevel model was constructed using a combination of psychoacoustic metrics and sound source labels to predict perceived annoyance, achieving an R2 of 0.64 for predicting individual responses. The sound source information is demonstrated to be a crucial factor, as the relationship between roughness, impulsiveness, and tonality and the predicted annoyance varies as a function of the sound source label. The third piece of empirical work uses multilevel models to examine the extent to which personal factors influence soundscape perception. The findings suggest that personal factors, including psychological wellbeing, age, gender, and occupational status, account for approximately 1.4% of the variance for pleasantness and 3.9% for eventfulness, while the influence of the locations accounted for approximately 34% and 14%, respectively. Drawing from the experience gained working with urban soundscape data, a new method of analysing and presenting the soundscape perception of urban spaces is developed. This method inherently considers the variety of perceptions within a group and provides an open-source visualisation tool to facilitate a nuanced approach to soundscape assessment and design. Based on this empirical evidence, a framework is established for developing future predictive soundscape models which can be integrated into an engineering approach. At each stage, the results of these studies is discussed in terms of how it can contribute to a generalisable predictive soundscape model

Social-ecological soundscapes: examining aircraft-harvester-caribou conflict in Arctic Alaska

Thesis (M.S.) University of Alaska Fairbanks, 2017As human development expands across the Arctic, it is crucial to carefully assess the impacts to remote natural ecosystems and to indigenous communities that rely on wild resources for nutritional and cultural wellbeing. Because indigenous communities and wildlife populations are interdependent, assessing how human activities impact traditional harvest practices can advance our understanding of the human dimensions of wildlife management. Indigenous communities across Arctic Alaska have expressed concern over the last four decades that low-flying aircraft interfere with their traditional harvest practices. For example, communities often have testified that aircraft disturb caribou (Rangifer tarandus) and thereby reduce harvest opportunities. Despite this longstanding concern, little research exists on the extent of aircraft activity in Arctic Alaska and on how aircraft affect the behavior and perceptions of harvesters. Therefore, the overarching goal of my research was to highlight the importance of aircraft-harvester conflict in Arctic Alaska and begin to address the issue using a scientific and community-driven approach. In Chapter 1, I demonstrated that conflict between aircraft and indigenous harvesters in Arctic Alaska is a widespread, understudied, and complex issue. By conducting a meta-analysis of the available literature, I quantified the deficiency of scientific knowledge about the impacts of aircraft on rural communities and traditional harvest practices in the Arctic. My results indicated that no peer-reviewed literature has addressed the conflict between low-flying aircraft and traditional harvesters in Arctic Alaska. I speculated that the scale over which aircraft, rural communities, and wildlife interact limits scientists' ability to determine causal relationships and therefore detracts from their interest in researching the human dimension of this social-ecological system. Innovative research approaches like soundscape ecology could begin to quantify interactions and provide baseline data that may foster mitigation discourses among stakeholders. In Chapter 2, I employed a soundscape-ecology approach to address concerns about aircraft activity expressed by the Alaska Native community of Nuiqsut. Nuiqsut faces the greatest volume of aircraft activity of any community in Arctic Alaska because of its proximity to intensive oil and gas activity. However, information on when and where these aircraft are flying is unavailable to residents, managers, and researchers. I worked closely with Nuiqsut residents to deploy acoustic monitoring systems along important caribou harvest corridors during the peak of caribou harvest, from early June through late August 2016. This method successfully captured aircraft sound and the community embraced my science for addressing local priorities. I found aircraft activity levels near Nuiqsut and surrounding oil developments (12 daily events) to be approximately six times greater than in areas over 30 km from the village (two daily events). Aircraft sound disturbance was 26 times lower in undeveloped areas (Noise Free Interval =13 hrs) than near human development (NFI = 0.5 hrs). My study provided baseline data on aircraft activity and noise levels. My research could be used by stakeholders and managers to develop conflict avoidance agreements and minimize interference with traditional harvest practices. Soundscape methods could be adapted to rural regions across Alaska that may be experiencing conflict with aircraft or other sources of noise that disrupt human-wildlife interactions. By quantifying aircraft activity using a soundscape approach, I demonstrated a novel application of an emerging field in ecology and provided the first scientific data on one dimension of a larger social-ecological system. Future soundscape studies should be integrated with research on both harvester and caribou behaviors to understand how the components within this system are interacting over space and time. Understanding the long-term impacts to traditional harvest practices will require integrated, cross-disciplinary efforts that collaborate with communities and other relevant stakeholders. Finally, my research will likely spark efforts to monitor and mitigate aircraft impacts to wildlife populations and traditional harvest practices across Alaska, helping to inform a decision-making process currently hindered by an absence of objective data