Environmental noise tagging via audio spectrogram transformer

With the advent of reliable and continuously operating noise monitoring systems, we are now faced with an unprecedented amount of noise monitor data. In the context of environmental noise monitoring, there is a need to automatically detect, separate, and classify all environmental noise sources. This is a complex task because sources can overlap, vary by location, and have an unbounded number of noise sources that a monitor device may record. In this study, we synthetically generate datasets that contain Gaussian noise and overlaps for several pre-labeled environmental noise monitoring datasets to examine how well deep learning methods (e.g., autoencoders) can separate environmental noise sources. In addition to examining performance, we also focus on understanding which signal features and separation metrics are useful to this problem.

High spatial resolution environmental noise assessment and its associations with risks of cardiovascular diseases based on digital healthcare data in China.

Unattended and continuously running environmental noise monitoring systems can capture an intractable amount of data. The signals captured can include a multitude of sources (e.g., wind noise and anthropogenic noise sources) in addition to the environmental noise sources of interest (e.g., aircraft, vehicles, trains, and military weapons). In this presentation, we explore the use of machine-learning methods to effectively isolate and identify environmental noise sources captured on such a noise monitoring system. Specifically, we consider the use of both unsupervised (e.g., principle components analysis, clustering methods, and deep belief networks) and supervised (e.g., logistic regression, support vector machines, and neural networks) pattern-learning methods to derive the features of interest and classify the signals based on the obtained features. The generalization performance of each method is assessed using a dataset of over 120,000 human classified signals, and the strengths and weaknesses of each approach are discussed.

There are many reports on the noise pollution and its hazards from many cities around the world. The aims of these investigations were the environmental noise pollution in the populated cities in the world. This issue is not looked at as a severe problem and has not been paid much attention to in Iran. However, we intended to study noise pollution in the urban city of Tabriz ‐ one of the crowded and prominent cities of Iran. We carried out our research at 1000 stations over the city and found that sound level was lower than 65 dB in 7.7% of stations, over 75 dB in 59.8% of stations and 37.5% in the range of 65-75 dB (in particular in the service zones and city centre) during the day.

Environmental noise monitoring is an important link in improving the quality of life and strengthening environmental protection. In the bustling neighborhoods and residential areas of major cities, large-scale of environmental noise pollution have erected the streets. The design is mainly based on MCS89C5 1 microcontroller, which is the core of the audio detection system design. Capacitive electret microphone work by the principle of the sensor, the sound signal converts into electrical signal output when the microphone receiving noise, and then through the hardware circuit: amplify the signal, filtering A / D conversion circuit and software program control to complete the sound frequency detection function. Detection of the sound frequency display through the LED digital display, this design of the audio detection system is low cost, portable, can display environment noise digitally and so on. This can be widely used in industrial and mining enterprises, institutions and schools that need to measure and control the environment noise.

: The airborne microwave remote sensing was performed during EuroSTARRS using the Naval Research Laboratory STARRS instrument (Salinity, Temperature, and Roughness Remote Scanner). This leading edge passive L-Band instrument was acquired by NRL shortly before the campaign. Development of techniques for its use, and studies to understand its performance, are important parts of the acquisition process. In this paper we will examine instrument calibration and noise issues for STARRS which are associated with the flights conducted as part of the EuroSTARRS campaign, from November 16-23, 2001 in Germany, France and Spain. The issues we will address here are: pitch and roll improvements, L-Band absolute and ocean calibration, instrument stability, and environmental noise sources. A strong environmental noise source, located in the direction of Barcelona, was noticed during the Casablanca flight. A second environmental source was noted in the analysis later. The high altitude section of the Casablanca flight has elevated TB (most notably in all the outboard beams) relative to the low altitude section of the flight. The effects such environmental (presumably man-made) sources. Will have on satellite observations of L-Band brightness temperature may be significant.

Urbanization and industrialization present significant challenges to public health, particularly in managing environmental noise pollution. This study addresses the critical issue of noise pollution at the study area by developing a comprehensive noise map that encompasses industrial zones, construction sites, and areas with heavy traffic. Utilizing ArcGIS modeling software, the research visualizes the spatial dynamics of noise pollution, resulting in a detailed map that represents noise levels throughout the area. The analysis reveals that noise levels during weekday peak hours average 70.5 dBA, markedly higher than the 65.5 dBA average recorded during weekend peak hours. During weekdays morning peak, noise levels indicate three monitoring points in the red zone, two in the yellow zone, and five in the green zone. Notably, noise levels at all ten monitoring locations during weekdays peak hours exceeded the maximum permissible sound level of 60 dBA set by the Department of Environment for residential and commercial areas. These findings contribute to the development of targeted noise mitigation strategies and serve as a valuable resource for environmental authorities, policymakers, and urban planners. This research underscores the importance of a comprehensive approach to addressing environmental noise pollution and provides a practical framework for urban areas facing similar challenges.

As cities in sub-Saharan Africa become more crowded, noise pollution is also emerging as an important environmental concern, after air pollution. Yet, unlike air pollution, which is enjoying relatively more public attention, there is limited measurement data and policy efforts on environmental noise pollution. We followed a recent city-wide measurement approach used in Accra (Ghana) and characterized environmental noise patterns in Kigali, a contrasting city with very different topography and regulatory system than Accra to inform urban policy. We established 10 ‘fixed’ (yearlong) and 120 ‘rotating’ (weeklong) monitoring sites to capture both the temporal and spatial patterns in Kigali’s sound environment. The measurement occurred between November 2022 and December 2023, and samples were collected at 1 min interval, resulting in 5155 014 (3580 site-days) and 1190 620 (827 site-days) site-minutes of valid data from the fixed and rotating sites, respectively. The 130 monitoring sites covered a variety of geographic and land-use factors across diverse neighborhoods and sources. We computed several noise metrics, including 1 h (LAeq1 h), daily (LAeq24 h), day-time (Lday), and night-time (Lnight). Daily noise (LAeq24 h) levels across the city ranged between 38 dBA and 85 dBA. Commercial, business, and industrial (CBI) and high-density residential (HD) communities experienced the highest noise levels, with some sites constantly above 70 dBA at day and 65 dBA at night. About 63% of our observed day-time values (up to ~72% in some areas) exceeded the Rwandan day-time standard (55 dBA) for residential areas, whereas 69% of the observed night-time values (up to 80% in some areas) exceeded the corresponding night-time standard (45 dBA). In Nyarugenge, the most urbanized district, as much as 75% of our site-days data exceeded day-time standard. However diurnal patterns throughout the city were similar, rising from ~5 am, peaking at about 8 am and plateauing until 6 pm before falling to their lowest at midnight. Overall, noise levels in the city did not vary much by day of the week, weekdays vs weekend, or dry vs wet seasons. Environmental noise in Kigali often exceeded both Rwandan standards and international guidelines, with residents in the city center district, CBI and HD areas at risk of higher exposure, and hence higher risk of adverse effects. Detailed assessment of the sources, at-risk population, and associated health effects may inform Rwandan’s environmental policy efforts and city initiatives in the face of the ongoing urban growth and densification.

The impact of environmental noise, poor biodiversity, and air pollution on urban populations poses a significant challenge to public health. Addressing these concerns requires a comprehensive approach that considers the perceptual experiences of citizens and objective environmental data. The Conscious Walks introduce a hybrid methodology designed to address the perceptive impact of citizens on their environment. Conscious Walks are citizen-science participative projects that combine the active involvement of citizens with scientific data collection. Implemented and tested in Barcelona, Conscious Walks provide a unique opportunity to assess urban soundscapes, and this contribution specifically evaluates the soundscapes of the Ciutadella Park in Barcelona for three consecutive years. The gathered data is carefully cross-referenced with information on air quality and biodiversity obtained during the walks. The novelty of this research lies in the development of integrated indicators that comprehensively capture the interplay between biodiversity, noise pollution, and air pollution. These indicators provide an understanding of urban environmental quality, offering valuable insights for sustainable urban planning and policy-making. The results presented in this contribution underscore the significance of adopting holistic methodologies to address the complex challenges posed by urban environments, emphasizing the need for integrated indicators in assessing the multifaceted aspects of urban sustainability.

Full data coverage of urban environments is crucial to monitor the status of the area to detect, for instance, trends and detrimental environmental changes. Collecting observations related to environmental factors such as noise pollution in urban environments through classical approaches implies the deployment of Sensor Networks. The cost of deployment and maintenance of such infrastructure might be relatively high for local and regional governments. On the other hand recent mass-market mobile devices such as smartphones are full of sensors. For instance, it is possible to perform measurements of noise through its microphone. Therefore they become low-cost measuring devices that many citizens have in their pocket. In this paper we present an approach for gathering noise pollution data by using mobile applications. The applications are designed following gamification techniques to encourage users to participate using their personal smartphones. In this way the users are involved in taking and sharing noise pollution measurements in their cities that other stakeholders can use in their analysis and decision making processes.

Currently, noise pollution deriving from traffic, industry and leisure activities is one of the main environmental problems that affect people quality of life and health. However, it is very difficult to quantify noise effects, because they depend on people noise level tolerance, environmental noise sources, methods of definition of noise exposure and indicators. The acoustic descriptors currently used, indeed, are hardly understandable for those who do not deal with the topic, thus limiting the comprehension of the damage caused by noise. Consequently, it is essential to provide information that is easier to understand and closer to the noise pollution perceived by people. Innovative acoustic indices, like the Harmonica Index, have been defined in recent years, to overcome the aforementioned limits. Their application to different spatial contexts, with the identification of the background and the event-based components of the environmental noise, can contribute to understand the influence of human activities on the quality of an acoustic environment. In this paper, starting from data acquired both in crowdsourcing and with traditional instruments, the application of the Harmonica Index to urban, peri-urban and rural areas in south Italy will show their acoustic characteristics that could be understood also by a non-technical public.

BackgroundWhile the adverse health effects of civil aircraft noise are relatively well studied, impacts associated with more intense and intermittent noise from military aviation have been rarely assessed. In recent years, increased training at Naval Air Station Whidbey Island, USA has raised concerns regarding the public health and well-being implications of noise from military aviation.ObjectiveThis study assessed the public health risks of military aircraft noise by developing a systematic workflow that uses acoustic and aircraft operations data to map noise exposure and predict health outcomes at the population scale.MethodsAcoustic data encompassing seven years of monitoring efforts were integrated with flight operations data for 2020–2021 and a Department of Defense noise simulation model to characterize the noise regime. The model produced contours for day-night, nighttime, and 24-h average levels, which were validated by field monitoring and mapped to yield the estimated noise burden. Established thresholds and exposure-response relationships were used to predict the population subject to potential noise-related health effects, including annoyance, sleep disturbance, hearing impairment, and delays in childhood learning.ResultsOver 74,000 people within the area of aircraft noise exposure were at risk of adverse health effects. Of those exposed, substantial numbers were estimated to be highly annoyed and highly sleep disturbed, and several schools were exposed to levels that place them at risk of delay in childhood learning. Noise in some areas exceeded thresholds established by federal regulations for public health, residential land use and noise mitigation action, as well as the ranges of established exposure-response relationships.Impact statementThis study quantified the extensive spatial scale and population health burden of noise from military aviation. We employed a novel GIS-based workflow for relating mapped distributions of aircraft noise exposure to a suite of public health outcomes by integrating acoustic monitoring and simulation data with a dasymetric population density map. This approach enables the evaluation of population health impacts due to past, current, and future proposed military operations. Moreover, it can be modified for application to other environmental noise sources and offers an improved open-source tool to assess the population health implications of environmental noise exposure, inform at-risk communities, and guide efforts in noise mitigation and policy governing noise legislation, urban planning, and land use.

Chapter 8 - Conclusions and Future Directions

Background: Epidemiological studies indicate that both traffic noise and outdoor air pollution may be associated with risk for cardiovascular disease. Only few studies consider these two environmental exposures together. Aims: To provide an overview of the latest knowledge on the association between environmental noise and outdoor air pollution on related cardiovascular health effects. To examine whether the evidence suggests that noise and air pollution interact or confound with each other. Methods: A search was conducted on Pubmed electronic database, retrieving the papers on the cardiovascular health effects of combined exposure to noise and outdoor air pollution. The search was limited to peer-reviewed papers published in English between 2005 and February 2013. Results: Few studies have considered the joint effect of traffic noise and air pollution on the cardiovascular system. 13 papers on cardiovascular efects of combined exposure to noise and outdoor air pollution were identified and reviewed. Road traffic noise was the most commonly investigated noise source. The main reviewed cardiovascular health outcomes included: arterial blood pressure and hypertension, coronary heart disease, myocardial infarction and stroke. The effects of additional adjustment for either noise or air pollution varied between studies. Conclusions: Both traffic noise and outdoor air pollution seemed to have an independent effects on cardiovascular health end points. There is a need of more well-designed longitudinal studies to further investigate the combined exposure from noise and outdoor air pollution.

For public health policy and planning it is important to understand the relative contribution of environmental noise on health compared to other environmental stressors. Air pollution is the primary environmental stressor in relation to cardiovascular morbidity and mortality. This paper reports a narrative review of studies in which the associations of both environmental noise and air pollution with health have been examined. Studies of hypertension, myocardial infarction, stroke, mortality and cognitive outcomes were included. Results suggest independent effects of environmental noise from road traffic, aircraft and, with fewer studies, railway noise on cardiovascular outcomes after adjustment for air pollution. Comparative burden of disease studies demonstrate that air pollution is the primary environmental cause of disability adjusted life years lost (DALYs). Environmental noise is ranked second in terms of DALYs in Europe and the DALYs attributed to noise were more than those attributed to lead, ozone and dioxins. In conclusion, in planning and health impact assessment environmental noise should be considered an independent contributor to health risk which has a separate and substantial role in ill-health separate to that of air pollution.