Letteratura scientifica selezionata sul tema "NoiseModelling"

The Environmental Noise Directive (END) requires the realization of strategic noise maps, every 5 years, in order to evaluate the noise impact of roads, railways, airports and the main industries on the inhabitants. To achieve round 4 for major roads and major railways, France has decided to create a national database called PlaMADE, which gathers all the necessary input data (traffic, building, population, relief...) in a unique format, a COVADIS GeoStandard. On the basis of these data, and using the open-source noise propagation calculation tool NoiseModelling, all the indicators and maps have been produced for the first time in an automatic way at a national scale. This paper presents the technical and methodological details of the coupling between the PlaMADE database and the NoiseModelling tool.

The urbanisation phenomenon and related cities expansion and transport networks entail preventing the increase of population exposed to environmental pollution. Regarding noise exposure, the Environmental Noise Directive demands on main metropolis to produce noise maps. While based on standard methods, these latter are usually generated by proprietary software and require numerous input data concerning, for example, the buildings, land use, transportation network and traffic. The present work describes an open source implementation of a noise mapping tool fully implemented in a Geographic Information System compliant with the Open Geospatial Consortium standards. This integration makes easier at once the formatting and harvesting of noise model input data, cartographic rendering and output data linkage with population data. An application is given for a French city, which consists in estimating the impact of road traffic-related scenarios in terms of population exposure to noise levels in relation to both a threshold value and level classes.

Beyond the estimation of daily exposure profiles of agents, agent-based models can be used to investigate the role of different urban areas in noise exposure. This study explores this potential by proposing a new approach to spatio-temporal mapping of the accessibility to quiet areas in agglomerations, integrating mobility into the analysis of place effects. Using an agent and activity-based framework, composed of EQASim, MATSim and NoiseModelling, the Nantes Metropolitan Area (France) is modeled. The definition of the quiet areas conditions and the accessibility metric are analyzed in order to understand the influence of these parameters on the identification of critical urban areas where agents don't have their access to quiet areas assured. The results show a great variability of accessibility according to its definition and emphasize the need to include new variables in the assessment.

Extensive noise mapping has been crucial in shaping noise mitigation policies; however, assessing noise exposure in different scenarios remains challenging due to static maps that only represent pre-calculated sound levels. To fill this gap, this study introduces a novel noise mapping framework tailored to calculate sound levels in specific environments within small, arbitrary regions. Using the open-source noise prediction tool NoiseModelling and global databases of road networks, buildings, terrain, and population distribution on QGIS, this framework seamlessly integrates noise mapping procedures, including comprehensive data collection, receiver placement, sound level calculation, and visualization. The user-friendly graphical interfaces enable quick and easy generation of noise maps. The approach offers flexibility through customizable geometry and parameter settings to account for variations in noise sources and propagation characteristics, thereby providing stakeholders with valuable insights for policy formulation, environmental impact assessment, and community engagement. This methodology not only improves the accessibility and relevance of noise mapping but also empowers decision makers to implement tailored noise mitigation strategies that promote healthier and more livable environments.

In order to more accurately estimate health outcomes related to environmental noise exposure such as sleep disturbance and noise annoyance, indicators beyond long-term equivalent sound pressure levels might be needed (such as statistical levels, number of events, psycho-acoustical indices etc). In urban noise mapping, predicting these more advanced noise indicators is especially challenging. In the current work, an open source noise mapping code (NoiseModelling) is combined with micro-traffic simulations. However, in most cities, traffic data availability is poor, especially in low traffic streets. To overcome this issue, the noise mapping procedure developed here assumes no access at all to traffic information and fully relies on Open Street Map street categorization. These street categorizations were then assigned sets of plausible traffic compositions, counts and speeds; various scenarios were explicitly simulated. In a next step, these traffic scenarios were weighted to best fit a set of 29 noise indicators on 23 measurement stations deployed in the city of Barcelona, during various periods of the day. It was shown that this procedure leads to adequate assessments of a wide range of noise indicators in a specific city.

Human voice plays a pivotal role as a sound source in urban environments. Despite the plethora of natural sound sources present in urban spaces, human voice often stands out as one of the sound source, exerting a significant influence on the perception and affection of these spaces. However, compared to other aspects of urban soundscapes, such as traffic noise (air, road, rail), human voice cartography and modelling remains relatively underexplored, with limited historical development and scholarly attention. This research gap led to the deployment of an experimental protocol in Nantes, France, to produce a comprehensive voice sound map and compare it to perceptual data. This protocol involved the collection of sound level measurements during two distinct measurement campaigns using the NoiseCapture smartphone application, coupled with surveys capturing perceptual information such as the circumplex circle of affect, perceived presence of sound sources, emergence of sound sources, and variability of the sound environment. Additionally, sound environment simulations were conducted using NoiseModelling. The present paper shows the method used to evaluate the audibility of human speech in urban spaces. During the presentation, comparisons with perceptual measurements will be presented.

Since road traffic is the most impactful noise source in the European cities, the evaluation of citizens' exposure is crucial. Although the noise map accuracy is affected by uncertainties in traffic volume, to perform extensive traffic monitoring is not practical and expensive, even in small cities. Traffic simulation software uses routing algorithms to suggest the fastest path to distribute vehicles from an origin through a network to a desired destination which interacts within the urban environment. Therefore, it could represent an important tool for noise mapping in the critical task to fill the data gaps in traffic volumes, also for implementing action plans using a suitable traffic management approach. However, there is a lack of evidence on how the choice of traffic simulation parameters influences noise estimation. In this work, we design a simulation framework to evaluate the impact of routing algorithms on the estimation of population noise exposure in an urban area. Using an open-source pipeline based on public databases and open-source software SUMO and NoiseModelling, we evaluated the implication on the traffic distribution and resulting noise exposure for a set of traffic model key parameters.

Abstract The civil security sirens are used by the authorities in a wide range of countries to signal an imminent or ongoing threat. Even if their sound level is known, it is nevertheless difficult to evaluate their audibility across a given zone, especially in complex urban environments. An experimental protocol was deployed around a siren installed in a town in France, to assess its audibility perceptually and through modeling. Sound level measurements during source activation were made with the NoiseCapture smartphone application at different distances and on several axes by a group of 25 participants. They were also asked to fill in a questionnaire on perceptual information about the siren such as its audibility, the perceived sound level, or the masking of the siren by passing vehicles. A comparison between acoustic measurement levels using NoiseCapture and simulated sound levels using NoiseModelling was performed. The results of this study validate the use of the Common Noise Assessment Methods in Europe model to evaluate the audibility of a warning system located in an urban environment within a radius of 2.8 km around the siren. Finally, a metric linking audibility to modeled sound level is proposed, enabling the development of siren audibility maps in the study area.

Le nombre de personnes vivant dans les villes ne cesse d'augmenter et l'on estime que d'ici 2050, près de 66 % des 9,5 milliards d'habitants de la planète seront des citadins. Avec l'urbanisation rapide, de nouveaux défis environnementaux en matière de développement durable et de santé publique sont devenus essentiels. De nombreux travaux de recherche ont mis en lumière les effets négatifs d'une exposition prolongée au bruit sur la santé humaine : augmentation du risque de maladies cardiovasculaires, santé mentale et troubles du sommeil. Selon le rapport de l'Agence européenne pour l'environnement de 2017, au moins 18 millions de personnes sont fortement gênées et 5 millions sont fortement perturbées dans leur sommeil en raison d'une exposition prolongée au bruit dans l'Union européenne. Des actions politiques telles que la Directive Européenne de 2002 ont été mises en place pour évaluer l'impact du bruit par les États et les acteurs territoriaux. À cette fin, des cartes de bruit sont proposées pour évaluer l'exposition au bruit sur un territoire, mais elles se limitent à de simples indicateurs de l'environnement acoustique : le niveau sonore moyen lorsqu'il dépasse un certain seuil, calculé uniquement pour quelques sources considérées comme gênantes ou nuisibles (trafic routier, ferroviaire, aérien et industriel). Ces approches négligent souvent la dynamique et la complexité intrinsèque des environnements sonores urbains, négligeant ainsi leur dynamique temporelle et la multiplicité des sources qui intègrent la composition urbaine.En effet, les environnements sonores urbains abritent une grande diversité de sources sonores, chacune contribuant à sa manière à l'expérience sonore d'un lieu. Ils se caractérisent par leur complexité, leur variabilité et leur nature dynamique, façonnés par des facteurs tels que l'aménagement urbain, les modes d'occupation des sols, les infrastructures et le comportement humain. Alors que les méthodes traditionnelles se concentraient exclusivement sur les sources de bruit, une nouvelle approche pluridisciplinaire a vu le jour : le paysage sonore. Introduit par R. M. Schafer dans les années 1970, le concept de paysage sonore s'écarte de la vision négative et réactive des réglementations en matière de contrôle du bruit et offre une perspective de l'identité acoustique d'un lieu, naturellement liée à la perception humaine. À l'origine, le concept de paysage sonore était présenté comme une « expérience de reconnexion avec l'environnement sonore autour » avant d'évoluer vers une approche multidisciplinaire centrée sur l'humain et impliquant des architectes, des concepteurs urbains et des autorités locales et nationales. S'appuyant souvent sur des évaluations perceptives, des données acoustiques et des modèles statistiques, l'approche du paysage sonore est utilisée pour estimer la dimensionnalité des attributs du paysage sonore et la perception qui y est liée, fournissant ainsi de riches informations sur la qualité sonore des espaces urbains et sur la manière dont les êtres humains s'y rapportent. Néanmoins, en raison de la nature complexe de ces environnements, la prise en compte physique de la multiplicité des sources et de leur dynamique constitue actuellement un verrou scientifique dans la modélisation de ces environnements. Ainsi, toute représentation pertinente de ces systèmes complexes devrait englober tous les sons audibles, tels que les voix humaines, les chants d'oiseaux, l’eau ou la musique et sa dynamique, en plus des sources « négatives » traditionnelles (par exemple, le trafic routier). Dans ce contexte, la modélisation multi-sources apparaît comme un cadre prometteur pour caractériser les environnements sonores urbains. Cette approche permet l'intégration simultanée de diverses sources sonores et leur représentation à l'aide de techniques cartographiques.(...)
The number of people living in cities is constantly increasing, and it is estimated that by 2050, almost 66% of the world's 9.5 billion inhabitants will be urban dwellers. With rapid urbanization, new environmental challenges of sustainable development and public health have become central. Evidence from numerous research endeavors have shed light on the negative impacts of prolongated exposure to noise on human health: increase in the risk of cardiovascular diseases, mental health, and sleep disturbance. According to the European Environment Agency report in 2017, at least 18 million people are highly annoyed and 5 million are highly sleep disturbed because of long-term exposition to noise in the European Union. Political actions such as the 2002 European Directive have been introduced to assess the impact of noise by states and territorial players. To this end, noise maps have been enforced in the evaluation of the exposure to noise in a territory, however, they are limited to simple indicators of the acoustic environment: the average sound level when it exceeds a certain threshold, calculated only for a few sources considered as annoying or harmful (road, rail, air traffic, and industrial). These approaches often oversee the intrinsic dynamics and complexity of urban sound environments, thus neglecting their temporal dynamics and the multiplicity of sources that integrate the urban composition. Indeed, urban sound environments host a great diversity of sound sources, each contributing in its own way to the sonic experience of a place. They are characterized by their complexity, variability, and dynamic nature, shaped by factors such as urban design, land use patterns, infrastructure, and human behavior. As traditional assessment methods focused exclusively on noise sources, a new, multi-disciplinary approach emerged: the soundscape. Coined by R. M. Schafer in the 1970s, the soundscape concept diverges from the negative and reactive vision of noise control regulations and offers a perspective of the acoustical identity of a place, naturally intertwined with human perception. At its origins, the soundscape concept was coined as a “reconnecting experience with the sonic environment around” prior to evolving into a multidisciplinary approach centered around the human and that involves architects, urban designers, and local to national authorities. Often relying on perceptual assessments, acoustical data, and statistical models, the soundscape approach is used for estimating the dimensionality of soundscape attributes and the perception related to them, thus providing rich insights about the sonic quality of urban spaces and how humans relate to it. Nevertheless, due to the complex nature of these environments, a current scientific bottleneck in the modeling of such environments is the physical consideration of the multiplicity of sources and their dynamics. Thus, any pertinent representation of such complex systems should encompass all audible sounds, such as human voices, birdsong, water, or music and its dynamics; in addition to traditional “negative” sources (e.g. road traffic). In this context, multi-source modelling emerges as a promising framework to characterize urban sound environments. This approach allows for the simultaneous integration of diverse sound sources and their representation through the use of cartographic techniques. The ultimate goal of the work presented in this thesis is to develop and explore a numerical modelling framework for urban sound environments based on a multi-source principle that accurately conveys the dynamics of urban compositions.(...)