Urban Sound Environments Research Articles

Investigating contextual influences on urban soundscape evaluations with structural equation modeling

Previous soundscape research has shown a complex relationship between soundscapes, public space usage and contexts of users’ visits to the space. Yet many of these findings are restricted to one study site at a time and may not generalize to a global understanding of urban sound environments. The present study is a comparative analysis of in situ questionnaires collected over four study sites in Montreal (N = 1429) in both French and English. At each site, the questionnaire included items from the Swedish Soundscape Quality Protocol and other soundscape variables, as well as person-related (age, gender, extraversion, noise sensitivity) and situation-related (social interaction) variables. We first tested measurement invariance between the French and English versions of the used soundscape questionnaire. We then investigated the influence of contextual factors (combining person-related and situation-related variables) on soundscape evaluations. The analyses confirmed the underlying conceptualizations of proposed soundscape assessment questionnaires, confirmed metric invariance between French and English questionnaires, and revealed significant influences of contextual factors on soundscape dimensions. Our analysis further suggests that younger people, women, and extraverted people occupy the public space more in groups, and that people in groups rate the soundscape as more pleasant and less eventful. Older people and women were found to be more sensitive to noise, and more sensitive people tended to perceive the soundscape as less pleasant and less monotonous. This research represents a critical step in rigorously assessing soundscape evaluation methods and establishes solid groundwork to build more complex models of contextual influences on soundscape evaluation.

How can we plan for a good urban sound environment, focusing on road traffic noise?

Introduction. The sound environments in our cities are affected by unwanted sounds, i.e. noise, to an extent that is largely undesired, affecting health and wellbeing. The World Health Organization (WHO) has estimated the burden of disease from traffic-related noise within the western part of Europe and concluded that we each year lose at least one million disability-adjusted life years (DALYs) and that only air pollution has a larger disease burden among environmental factors. The burden of environmental noise is mainly sleep disturbance and annoyance. And the dominant source is road traffic.Methods. This paper describes the mechanisms behind road traffic noise and how we can use them in an urban sound planning perspective to improve the sound environment, as an integral part of sustainable cities and communities. The results are based on calculations and measurements made in previous and ongoing projects.Results. Treatments at source consider tyre, road, engine (whether electric or combustion), driving speed and acceleration, and further vehicle restrictions. Methods for reduction of noise during propagation and more general urban planning aspects include low-height barriers and ground treatments; acoustically absorbing facades and roofs of buildings, e.g. including vegetation; and building morphology and quiet side. Quantitative reductions, in decibels, as well as qualitative aspects are presented.Conclusions. The described possible improvements to the urban sound environment, with focus on road traffic noise as the dominant impairing factor, inform us about how a good urban sound environment can be reachable. However, to reach a good sound environment in reality, the work process of applied urban sound planning demands work across disciplines, also at early-stage planning, instead of traditional noise control applied late in the planning process.

Spatial-temporal dynamic simulation of anti-noise urban expansion based on fuzzy intelligent control system and GIS

On the basis of FHWA model of the Federal Highway Administration and the combination with the geographic information system (GIS) and Fuzzy intelligent control system, the group independently researches and develops a simulation and evaluation system for the traffic noise in the urban road. This system is able to simulate the influence of traffic source, point source, and arbitrary shape area source on the urban sound field environment. It is combined with the noise radiation and the communication model, and the occlusion and attenuation by the buildings and forest belts on the traffic noise have been considered. It can calculate the traffic noise in urban areas and directly render the predicted results on the GIS map, and form a traffic noise map, which visually and clearly displays the pollution degree and distribution map of the traffic noise in urban areas. The noise maps of Guangzhou inner ring roads and Zhujiang New Town are drawn to provide scientific decision-making basis for the control of urban traffic noise pollution.

Improving Smart Cities Safety Using Sound Events Detection Based on Deep Neural Network Algorithms

In recent years, security in urban areas has gradually assumed a central position, focusing increasing attention on citizens, institutions and political forces. Security problems have a different nature—to name a few, we can think of the problems deriving from citizens’ mobility, then move on to microcrime, and end up with the ever-present risk of terrorism. Equipping a smart city with an infrastructure of sensors capable of alerting security managers about a possible risk becomes crucial for the safety of citizens. The use of unmanned aerial vehicles (UAVs) to manage citizens’ needs is now widespread, to highlight the possible risks to public safety. These risks were then increased using these devices to carry out terrorist attacks in various places around the world. Detecting the presence of drones is not a simple procedure given the small size and the presence of only rotating parts. This study presents the results of studies carried out on the detection of the presence of UAVs in outdoor/indoor urban sound environments. For the detection of UAVs, sensors capable of measuring the sound emitted by UAVs and algorithms based on deep neural networks capable of identifying their spectral signature that were used. The results obtained suggest the adoption of this methodology for improving the safety of smart cities.

The future of urban sound environments: Impacting mobility trends and insights for noise assessment and mitigation

The degradation of the sound environment contributes significantly to the external costs of mobility and is an obstacle to the development of cities. Action plans aiming at fighting traffic noise often take a long time to reach mature implementation. Therefore, it is advantageous to envisage how societal and urban changes and associated changes in mobility practices will modify the urban sound environment of tomorrow. In this article, an interdisciplinary team of seven researchers, whose work focuses on different fields of acoustics and mobility, reviews the potential impact of ongoing mobility and society changes on sound environments. First, the team identified the trends dealing with urban renewal, societal changes and new mobility drivers that have the greatest influence on sound environments, and analyzed in detail. From this analysis, insights emerged for urban noise impact and innovative noise mitigation solutions in the light of improved assessment of the links between mobility and urban sound environments.

Let the Children Listen: A First Approximation to the Sound Environment Assessment of Children through a Soundwalk Approach.

The urban sound environment is one of the layers that characterizes a city, and several methodologies are used for its assessment, including the soundwalk approach. However, this approach has been tested mainly with adults. In the work presented here, the aim is to investigate a soundwalk methodology for children, analyzing the sound environment of five different sites of Gothenburg, Sweden, from children’s view-point, giving them the opportunity to take action as an active part of society. Both individual assessment of the sound environment and acoustic data were collected. The findings suggested that among significant results, children tended to rank the sound environment as slightly better when lower levels of background noise were present (). Moreover, traffic dominance ratings appeared as the best predictor among the studied sound sources: when traffic dominated as a sound source, the children rated the sound environment as less good. Additionally, traffic volume appeared as a plausible predictor for sound environment quality judgments, since the higher the traffic volume, the lower the quality of the sound environment. The incorporation of children into urban sound environment research may be able to generate new results in terms of children’s understanding of their sound environment. Moreover, sound environment policies can be developed from and for children.

Valuing transport noise impacts in public urban spaces in the UK: Gaps, opportunities and challenges

Transport noise is the dominant noise source in urban areas. Its impacts on people at their residential locations are included in economic appraisal in the UK and many other countries, and guidance and analysis tools were developed for the valuation of the impacts. However, for transport noise impacts on people in public urban spaces, e.g., urban streets, squares and parks, there is still a lack of national methodologies. This paper will discuss the gaps, opportunities and challenges in developing a national methodology for these places in the UK. Currently, evidence is lacking on pathways of transport noise impact on people and dose–response relationships at non-residential locations, and the values people place on sound environment quality at these locations. However, opportunities are emerging, with increasing attention to the urban realm in UK transport policy, and recent progress and transitions in urban sound environment research, including association between public health and urban soundscape, standardisation in soundscape research and practice, and crowdsourcing sound environment evaluations. The associated challenges, as compared to methodology for residential locations, may include calculating noise from non-free-flow traffic, defining and adding diverse receptor types, estimating dynamic affected population, accounting for diversity in level and source of background sound, and obtaining large and consistent data for dose–response or willingness-to-pay analyses.

Assessing the changing urban sound environment during the COVID-19 lockdown period using short-term acoustic measurements

AbstractThe implementation of lockdown measures due to the COVID-19 outbreak has resulted in wide-ranging social and environmental implications. Among the environmental impacts is a decrease in urban noise levels which has so far been observed at the city scale via noise mapping efforts conducted through the framework of the Environmental Noise Directive. This study aims to understand how lockdown measures have manifested at a local level to better determine how the person-level experience of the urban soundscape has been affected and how these affects differ across urban space typologies. Taking London as a case study, a series of 30-second binaural recordings were taken at 11 locations representing a cross-section of urban public spaces with varying compositions of sound sources during Spring 2019 (pre-lockdown, N = 620) and Spring 2020 (during-lockdown, N = 481). Five acoustic and psychoacoustic metrics (LAeq,LA10,LA90, Loudness, Sharpness) were calculated for each recording and their changes from the pre-lockdown scenario to the lockdown scenario are investigated. Clustering analysis was performed which grouped the locations into 3 types of urban settings based on their acoustic characteristics. An average reduction of 5.4 dB (LAeq) was observed, however significant differences in the degree of reduction were found across the locations, ranging from a 10.7 dB to a 1.2 dB reduction. This study confirms the general reduction in noise levels due to the nationally imposed lockdown measures, identifies trends which vary depending on the urban context and discusses the implications for the limits of urban noise reduction.

Estimation of the Perceived Time of Presence of Sources in Urban Acoustic Environments Using Deep Learning Techniques

The impact of urban sound on human beings has often been studied from a negative point of view (noise pollution). In the two last decades, the interest of studying its positive impact has been revealed with the soundscape approach (resourcing spaces). The literature shows that the recognition of sources plays a great role in the way humans are affected by sound environments. There is thus a need for characterizing urban acoustic environments not only with sound pressure measurements but also with source-specific attributes such as their perceived time of presence, dominance or volume. This paper demonstrates, on a controlled dataset, that machine learning techniques based on state of the art neural architectures can predict the perceived time of presence of several sound sources at a sufficient accuracy. To validate this assertion, a corpus of simulated sound scenes is first designed. Perceptual attributes corresponding to those stimuli are gathered through a listening experiment. From the contributions of the individual sound sources available for the simulated corpus, a physical indicator approximating the perceived time of presence of sources is computed and used to train and evaluate a multi-label source detection model. This model predicts the presence of simultaneously active sources from fast third octave spectra, allowing the estimation of perceptual attributes such as pleasantness in urban sound environments at a sufficient degree of precision.

Sound Stories: A Context-Based Study of Everyday Listening to Augmented Soundscapes

Abstract With an increasing number of everyday operations and communications becoming both automated and autonomous, ambient intelligent soundscapes are transforming to accommodate additional sonic feedback, and with it, new frameworks of listening. While this type of research and design of audio augmented technology is not new, the impact pre-existing acoustic environments upon listeners’ sense-making activities is rarely considered holistically. Much of the study into the design of effective auditory displays focuses on perceptual acuity and correct source identification, often at the expense of understanding the context of meaning-making. This paper presents a study involving 70 participants who listened to unidentified audio recordings of two archetypal everyday urban sound environments naturally containing artificial signals as well as typical sounds. Using a ThinkAloud protocol we investigated listeners’ approaches to meaning-making in both semantic and temporal dimensions. Through a semantic content analysis, we articulate five aspects of sonic meaning-making: spatial, descriptive, experiential, associational and narrative. We further analyse the use of these perceptual elements on a temporal plane, in order to investigate how listeners construct a narrative of what they hear in real-time, naturally evolving as each subsequent sound event is interpreted. Results suggest that while listeners attend to sound events and spatial characteristics of a sound environment at the beginning of a new listening situation, as the soundscape unfolds they utilize associations and familiarity in order to place individual sounds into increasingly coherent narratives. Finally, we suggest that this approach could provide sound designers and human–computer interaction specialists with a model for investigating the context aspects of a soundscape more holistically, allowing them to evaluate the effect of any new designed sounds prior to introduction into real-world environments.

Investigating the perception of soundscapes through acoustic scene simulation.

This paper introduces a new experimental protocol for studying mental representations of urban soundscapes through a simulation process. Subjects are asked to create a full soundscape by means of a dedicated software tool, coupled with a structured sound data set. This paradigm is used to characterize urban sound environment representations by analyzing the sound classes that were used to simulate the auditory scenes. A rating experiment of the soundscape pleasantness using a seven-point bipolar semantic scale is conducted to further refine the analysis of the simulated urban acoustic scenes. Results show that (1) a semantic characterization in terms of presence/absence of sound sources is an effective way to characterize urban soundscape pleasantness, and (2) acoustic pressure levels computed for specific sound sources better characterize the appraisal than the acoustic pressure level computed over the overall soundscape.

Effect of immersive visual stimuli on the subjective evaluation of the loudness and annoyance of sound environments in urban cities

The subjective evaluation of the sound environment of urban areas has been widely investigated in laboratories using various acoustic simulation methods. However, visual stimuli, such as videos of the original measurement environment, can also be considered to influence the sound evaluation. This paper proposes a system for the simulation of the target audiovisual environment using headphones and a head-mounted display. The inclusion of the head-mounted display provides insight into the influence of the provision of a realistic panoramic video of the target visual environment on the subjective evaluation. To provide realistic sound environments, variation in the direction of incidence of the sound caused by the rotation of the subject’s head is taken into consideration in the proposed system by dynamically updating the simulated direction of incidence using sound data recorded with a six-channel directional microphone, head-related transfer functions, and the angular data of the orientation of the head obtained by a gyro sensor installed in the head-mounted display. To validate the basic performance of the proposed sound simulation system, a subjective sound localization test was performed, and it was confirmed that appropriate sound localization performance can be achieved with the system when the subjects can freely rotate their heads. With the proposed system, a subjective evaluation experiment targeting urban sound environments was performed, and the effect of the visual stimulus on the evaluated loudness and annoyance of the sound was assessed. The evaluation scores of the loudness and annoyance of the sounds were significantly lower when panoramic videos of the original measurement locations were presented to the subjects than when videos of an anechoic chamber were presented. This suggests that the subjective evaluation of the environmental sounds without any visual information concerning the environments give a bias to the evaluated results.

Changing the Urban Sound Environment in Greece: A Guide Based on Selected Case Studies of Strategic Noise Maps (SNM) and Noise Action Plans (NAP) in Medium and Large Urban Areas

Within the frame of European directive 2002/49 for Strategic Noise Mapping and the relevant environmental Noise Action Plans, which included preparation for the management of environmental noise and the rehabilitation of the sound environment, Greece had the opportunity to develop an innovative and comprehensive methodology to analyze the sound environments of several urban and semi-urban residential neighborhoods in the large and medium-size cities of the country e.g., Volos, Larissa, Heraklion, Chania, Agrinio, Corfu, and Thessaloniki, between 2012 and 2016. This paper presents the determined multidisciplinary approach, showing how the environmental noise data are cross-analyzed with urban and architectural data and perception descriptors by inhabitants. Furthermore, it shows how these specific results have been implemented in the developed noise actions plans that have been proposed to the authorities for immediate implementation. Finally, the paper discusses the necessary development of this approach to reduce noise exposure problems, as well as assist the cities in their evolution toward the introduction of a sustainable urban sound environment.

Evaluation of the sound environment of the city of Biskra (Algeria)

This research concerns the quantitative evaluation of the urban sound environment of the city of Biskra. The aim was to determine the quality of the soundscape based on in situ measurement, using a Landtek SL5868P sound level meter. 62 points have been identified to represent the whole city. The results show that that the noise level varies from 54.1 to 75.8 dB(A) during the weekdays and from 50.4 to 74.2dB(A) during the weekend. In addition,90% of the results of the weekday measurements and 81% of the results of the weekend measurements exceed the recommended levels given by the World Health Organization. The present urban sound exposure could have a substantial impact on the overall comfort of inhabitants and increase the risk of the syndrome of the sick cities.

Speech Identification and Comprehension in the Urban Soundscape

Urban environments are characterised by the presence of copious and unstructured noise. This noise continuously challenges speech intelligibility both in normal-hearing and hearing-impaired individuals. In this paper, we investigate the impact of urban noise, such as traffic, on speech identification and, more generally, speech understanding. With this purpose, we perform listening experiments to evaluate the ability of individuals with normal hearing to detect words and interpret conversational speech in the presence of urban noise (e.g., street drilling, traffic jams). Our experiments confirm previous findings in different acoustic environments and demonstrate that speech identification is influenced by the similarity between the target speech and the masking noise also in urban scenarios. More specifically, we propose the use of the structural similarity index to quantify this similarity. Our analysis confirms that speech identification is more successful in presence of noise with tempo-spectral characteristics different from speech. Moreover, our results show that speech comprehension is not as challenging as word identification in urban sound environments that are characterised by the presence of severe noise. Indeed, our experiments demonstrate that speech comprehension can be fairly successful even in acoustic scenes where the ability to identify speech is highly reduced.

Probabilistic modeling framework for multisource sound mapping

The process of modeling noise maps is now well defined: long-term aggregated indicators are calculated based on a collection or estimation of road, air and rail traffic variables. This framework however disregards the sound levels variations, and hence prevents the production of statistical or emergence indicators, and does not allow for the study of competition between typical urban sound sources that can improve the characterization of urban sound environments. A modeling framework in four steps is proposed to answer these issues: (i) a spatial distribution of the potential sound source of interest, (ii) the calculation of a sound propagation matrix, (iii) the stochastic activation of a sound sources ratio for n iterations of the sound map, and (iv) the calculation of specific sound indicators. The stochastic approach proposed in this study enables the estimation of the temporal sound distribution per sound source. It permits in particular to deduce source-oriented indicators such as the percentage of the time when a given sound source emerges from an urban sound mixture. An example of application of this framework is exposed for a district in the city of Nantes, France. It shows the interest of such approaches, in particular for soundscape and urban sound environment studies.

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.

Dynamic traffic noise assessment tool: A comparative study between a roundabout and a signalised intersection

Considering traffic flow as a steady noise source is common practice when studying traffic alternatives and its impact on the sound environment. However, vehicle dynamics have a strong influence on both transport behaviour and noise emission. One of the most relevant elements of traffic design is the intersection, where replacement of crossing intersections with roundabouts is common. In order to understand the features of these two traffic configurations, microscopic approaches are needed, making it possible to study time-pattern fluctuations relevant for the urban sound environment perception. A model based on individual-vehicle characteristics as function of time is developed and implemented in a real case study at a development stage. The model incorporates state-of-art microscopic traffic simulation software combined with the recent noise emission model, CNOSSOS-EU, applied through an in-house developed dynamic traffic noise tool, including both internal combustion engine and all-electric vehicles at different traffic flows. The tool is described in general terms incorporating the randomisation of source power. The propagation considers a flat-city configuration up to 100m range. The tool enables study of different statistical indicators, including descriptors of probability density functions, calm periods through the novel indicator Centre of Mass Time (CMT) and noise events. The outcomes are presented through graphs and maps explaining traffic disruptions, acceleration effects, vehicle configurations and flows, source strengths, contribution and difference maps. Among the results, it is shown that, for the signalised crossing, the acceleration of the simulated traffic has a large effect on the source strength. It is however also shown that, for an unbalanced roundabout intersection leading to congestions, it can become noisier than the signalised crossing. It is furthermore shown that, when reducing the traffic flow, the two intersection types behave more similarly; however the roundabout having the best performance for the majority of the studied analysis. Further results are shown, e.g. for removing heavy vehicles, removing also medium heavy vehicles and assuming only all-electric light vehicles, including analysis from using various indicators. A discussion about the presented tool, the current results and ideas for future work concludes the paper.The present paper goes along a series of studies with the overall intention to provide a more solid basis for justifying decisions in traffic planning regarding the outdoor sound environment.

A demonstrator tool of web-based virtual reality for participatory evaluation of urban sound environment

Using virtual reality (VR) for environmental evaluation is one of the innovations in planning process to support the involvement of local population in decision making. The power of VR in public participation is further enhanced by its application online. However, current online VR applications for public participation is mostly restricted as visualisation tools. Evaluation of the virtual sound environment is rarely supported. This study developed a demonstrator tool of web-based online VR for participatory evaluation of urban sound environment. Piazza Vittoria in Naples, Italy was used as the case site to create the virtual environment. The tool employed affordable visualisation and auralisation for the general public to use online in mainstream web browsers with their own devices. The tool was tested online and the results were analysed to discuss the applicability, potential and challenges of online VR for participatory evaluation of urban sound environment.

Characterization of urban sound environments using a comprehensive approach combining open data, measurements, and modeling

Urban noise reduction is a societal priority. In this context, the European Directive 2002/49/EC aims at producing strategic noise maps for large cities. However, nowadays the relevance of such maps is questionable, due to considerable uncertainties, which are rarely quantified. Conversely, the development of noise observatories can provide useful information for a more realistic description of the sound environment, but at the expense of insufficient spatial resolution and high costs. Thus, the CENSE project aims at proposing a new methodology for the production of more realistic noise maps, based on an assimilation of simulated and measured data, collected through a dense network of low-cost sensors that rely on new technologies. In addition, the proposed approach tries to take into account the various sources of uncertainty, either from measurements and modeling. Beyond the production of physical indicators, the project also includes advanced sound environments characterization, through sound recognition and perceptual assessments. CENSE is resolutely a multidisciplinary project, bringing together experts from environmental acoustics, data assimilation, statistics, GIS, sensor networks, signal processing, and noise perception. As the project is in launch state, the present communication will focus on a global overview, emphasizing the innovative and key points of the project.