scholarly journals Road traffic noise assessment in a hospital area in Umuarama - Brazil

2021 ◽  
Vol 9 (74) ◽  
Author(s):  
Samantha Junqueira Moreira ◽  
Warde Antonieta Da Fonseca-Zang ◽  
Cecília de Castro Bolina ◽  
Stella Alonso Rocha ◽  
Paulo Henrique Trombetta Zannin
Keyword(s):  
Strong Correlation ◽  
Sound Pressure ◽  
Road Traffic ◽  
Traffic Noise ◽  
Noise Pollution ◽  
Road Traffic Noise ◽  
Vehicular Traffic ◽  
Noise Levels ◽  
Hospital Environments ◽  
Noise Assessment

In hospital environments, high noise levels can result in damage to patients' treatments, delaying their rest and recovery. The sound pressure level (SPL) in hospital areas during the day must not exceed 50 dB and 45 dB (A) at night, according to NBR 10.151/2019. This research aimed to carry out environmental monitoring of equivalent sound pressure levels (LAeq) at fifteen points in the vicinity of three hospitals in the central region of the municipality of Umuarama-PR, during working days, at four different times, in the months of August, September and November 2018 and continued in March 2019. To this end, we sought to map the LAeq of the points, compare them with data from municipal and federal legislation and relate the LAeq to the volume of vehicular traffic. The collected SPL were higher than recommended by NBR 10.151 at all times and measurement points, during the week, and when considering the municipal regulations, only one point is in the equipment's accuracy limit. From the statistical analysis, a very strong correlation was observed between LAeq and the total volume of vehicles, and also a strong correlation between the descriptors L10 and L50 and the volume of vehicles. The Traffic Noise Index (TNI) was also calculated and the LAeq values ​​were compared with a subjective noise rating. The results show a scenario of noise pollution in the area and there is a need for the application of mitigating measures.

ConvTasNet-based anomalous noise separation for intelligent noise monitoring

2021 ◽  
Vol 263 (4) ◽  
pp. 2044-2051
Author(s):  
Han Li ◽  
Kean Chen ◽  
Bernhard U. Seeber
Keyword(s):  
Road Traffic ◽  
Low Cost ◽  
Traffic Noise ◽  
Real Life ◽  
Noise Pollution ◽  
Road Traffic Noise ◽  
Scale Invariant ◽  
Acoustic Sensor Networks ◽  
Noise Assessment ◽  
Sound Separation

Noise pollution has become a growing concern in public health. The availability of low-cost wireless acoustic sensor networks permits continuous monitoring of noise. However, real acoustic scenes are composed of irrelevant sources (anomalous noise) that overlap with monitored noise, causing biased evaluation and controversy. One classical scene is selected in our study. For road traffic noise assessment, other possible non-traffic noise (e.g., speech, thunder) should be excluded to obtain a reliable evaluation. Because anomalous noise is diverse, occasional, and unpredictable in real-life scenes, removing it from the mixture is a challenge. We explore a fully convolutional time-domain audio separation network (ConvTasNet) for arbitrary sound separation. ConvTasNet is trained by a large dataset, including environmental sounds, speech, and music over 150 hours. After training, the scale-invariant signal-to-distortion ratio (SI-SDR) is improved by 11.40 dB on average for an independent test dataset. ConvTasNet is next applied to anomalous noise separation of traffic noise scenes. We mix traffic noise and anomalous noise at random SNR between -10 dB to 0 dB. Separation is especially effective for salient and long-term anomalous noise, which smooth the overall sound pressure level curve over time. Results emphasize the importance of anomalous noise separation for reliable evaluation.

scholarly journals Development of Traffic Noise Prediction Model in an Educational Urban Area

2018 ◽  
Vol 4 (11) ◽  
pp. 2588 ◽  
Author(s):  
Hasan Mosa Al-Mosawe ◽  
Dhirgham Alobaydi ◽  
Amjad Albayati
Keyword(s):  
Prediction Model ◽  
Road Traffic ◽  
Traffic Noise ◽  
Noise Pollution ◽  
Future Research ◽  
Road Traffic Noise ◽  
Vehicle Speed ◽  
Noise Levels ◽  
Education Environment ◽  
The University

This paper studies the problem of noise pollution on the roads of the campus of University of Baghdad in Baghdad, Iraq. Due to the continuous redevelopment process conducted on the masterplan of the university, the noise levels have significantly impacted the education environment. The purpose of this paper was thus to study the sources caused and maximized the noise levels at the campus and also formulate a prediction model, identified the guidelines used for designing or developing future campus masterplans. Then, the noise levels were measured based on three variables: skid number, vehicle speed, and distance from the classrooms at seven selected points of the main ring road surrounding the university campus. Finally, the finding has shown that the classrooms' locations of the new urban additions, built in the last two decades, were laid out in the prohibited distance of road-traffic noise. In addition to that, it has confirmed that students studying in these classrooms are exposed to noise levels beyond the legislative norms and codes. Further, studying the alternatives used to improve the performance of the education environment in the existing campus of University of Baghdad can be considered in the future research directions.

Prediction of L10 and Leq Noise Levels Due to Vehicular Traffic in Urban Area Using ANN and Adaptive Neuro-Fuzzy Interface System (ANFIS) Approach

2019 ◽  
Vol 15 (2) ◽  
pp. 92-105
Author(s):  
Vilas K Patil ◽  
P.P. Nagarale
Keyword(s):  
Noise Level ◽  
Urban Areas ◽  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Vehicular Traffic ◽  
Noise Levels ◽  
Anfis Model ◽  
Neuro Fuzzy ◽  
Interface System

Recently in urban areas, road traffic noise is one of the primary sources of noise pollution. Variation in noise level is impacted by the synthesis of traffic and the percentage of heavy vehicles. Presentation to high noise levels may cause serious impact on the health of an individual or community residing near the roadside. Thus, predicting the vehicular traffic noise level is important. The present study aims at the formulation of regression, an artificial neural network (ANN) and an adaptive neuro-fuzzy interface system (ANFIS) model using the data of observed noise levels, traffic volume, and average speed of vehicles for the prediction of L10 and Leq. Measured noise levels are compared to the noise levels predicted by the experimental model. It is observed that the ANFIS approach is more superior when compared to output given by regression and an ANN model. Also, there exists a positive correlation between measured and predicted noise levels. The proposed ANFIS model can be utilized as a tool for traffic direction and planning of new roads in zones of similar land use pattern.

scholarly journals Aggregate Impact of Anomalous Noise Events on the WASN-Based Computation of Road Traffic Noise Levels in Urban and Suburban Environments

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 609 ◽  
Author(s):  
Francesc Alías ◽  
Ferran Orga ◽  
Rosa Ma Alsina-Pagès ◽  
Joan Claudi Socoró
Keyword(s):  
Sensor Networks ◽  
Road Traffic ◽  
Traffic Noise ◽  
Noise Pollution ◽  
Environmental Noise ◽  
Integration Time ◽  
Road Traffic Noise ◽  
Noise Levels ◽  
Noise Mapping ◽  
Acoustic Data

Environmental noise can be defined as the accumulation of noise pollution caused by sounds generated by outdoor human activities, Road Traffic Noise (RTN) being the main source in urban and suburban areas. To address the negative effects of environmental noise on public health, the European Environmental Noise Directive requires EU member states to tailor noise maps and define the corresponding action plans every five years for major agglomerations and key infrastructures. Noise maps have been hitherto created from expert-based measurements, after cleaning the recorded acoustic data of undesired acoustic events, or Anomalous Noise Events (ANEs). In recent years, Wireless Acoustic Sensor Networks (WASNs) have become an alternative. However, most of the proposals focus on measuring global noise levels without taking into account the presence of ANEs. The LIFE DYNAMAP project has developed a WASN-based dynamic noise mapping system to analyze the acoustic impact of road infrastructures in real time based solely on RTN levels. After studying the bias caused by individual ANEs on the computation of the A-weighted equivalent noise levels through an expert-based dataset obtained before installing the sensor networks, this work evaluates the aggregate impact of the ANEs on the RTN measurements in a real-operation environment. To that effect, 304 h and 20 min of labeled acoustic data collected through the two WASNs deployed in both pilot areas have been analyzed, computing the individual and aggregate impacts of ANEs for each sensor location and impact range (low, medium and high) for a 5 min integration time. The study shows the regular occurrence of ANEs when monitoring RTN levels in both acoustic environments, which are especially common in the urban area. Moreover, the results reveal that the aggregate contribution of low- and medium-impact ANEs can become as critical as the presence of high-impact individual ANEs, thus highlighting the importance of their automatic removal to obtain reliable WASN-based RTN maps in real-operation environments.

scholarly journals Evaluation of road traffic noise near tube-shaped bus rapid transit shelters

2021 ◽  
Vol 9 (72) ◽  
Author(s):  
Geanesson Alberto de Oliveira Santos ◽  
Eriberto Oliveira do Nascimento ◽  
Paulo Henrique Trombeta Zannin
Keyword(s):  
Noise Exposure ◽  
Road Traffic ◽  
Traffic Noise ◽  
Noise Pollution ◽  
Sound Level ◽  
Urban Traffic ◽  
Bus Rapid Transit ◽  
Road Traffic Noise ◽  
Rapid Transit ◽  
Noise Levels

Noise pollution is generally imperceptible, but it can cause various disorders, including psychological disorders, hearing loss and cardiovascular disease. Curitiba Municipal Law 10.625:2002 establishes upper limits of daytime noise exposure according to zoning areas and land use in the City of Curitiba. The purpose of this study was to evaluate noise immissions of urban traffic in the proximities of Bus Rapid Transit (BRT) shelters in Curitiba, Brazil. Daytime traffic noise levels were measured between 8am and 5pm near the entrance of these bus shelters in July and August 2014. Fifty-four measurement points at parks, residences, stores, schools, universities and hospitals in different zoning groups of the municipality were selected as a function of the type of population. The noise levels were recorded using a class I sound level meter. Brazil has no specific standard or law for traffic noise immissions, so the guidelines of the Brazilian standard ABNT NBR 10151:2000 were used. It was concluded that 74% of the measured noise levels varied from 70 to 76 dB(A). Only point 48, close to the Antônio Meireles Sobrinho BRT Shelter, was considered free of noise pollution. Traffic noise accounts for an overall average of 73 dB(A). A few bus shelters installed on the same street had an absolute average difference of 3 dB(A), while bus shelters located farther away from roads were the least noisy. The lowest average traffic noise levels, i.e., 71 dB(A), were recorded on roads for exclusive use by BRT buses.

Road Traffic Noise Levels at Different Types of Residential Areas in Nibong Tebal, Penang

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Herni Halim ◽  
◽  
Nur Fatin Najiyah Hamid ◽  
Mohamad Firdaus Mahamad Yusob ◽  
Nur Atiqah Mohamad Nor ◽  
...  
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Residential Areas ◽  
Noise Levels ◽  
Different Types

A Review of Adverse Effects of Road Traffic Noise on Human Health

2018 ◽  
Vol 17 (01) ◽  
pp. 1830001 ◽  
Author(s):  
Devi Singh ◽  
Neeraj Kumari ◽  
Pooja Sharma
Keyword(s):  
Human Health ◽  
Work Performance ◽  
Road Traffic ◽  
Disease Risk ◽  
Traffic Noise ◽  
Cardiovascular Disease Risk ◽  
Noise Pollution ◽  
Health Hazards ◽  
Road Traffic Noise ◽  
Rapid Urbanization

Noise pollution due to road traffic is a potential threat to human health. Since it is a global hazard, the rapid urbanization and exponential traffic growth have aggravated the problem. Population residing along the busy traffic lanes is continuously exposed to the sound levels which are above the permissible limits. This constant exposure to noise pollution is a cause of concern as it leads to several adverse impacts on human health. Traffic noise causes irritation and annoyance, sleep disturbances, cardiovascular disease, risk of stroke, diabetes, hypertension and loss of hearing. It results in decreased work performance. The present review highlights the serious health hazards of road traffic noise (RTN) which needs to be curbed. Preventive measures of noise pollution can help in combating noise-induced health hazards and increased work performance.

scholarly journals Landscape depressions can create silent zones in noise polluted parks

2021 ◽  
Vol 263 (4) ◽  
pp. 2550-2554
Author(s):  
Timothy Van Renterghem ◽  
Pieter Thomas ◽  
Dick Botteldooren
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Noise Exposure ◽  
Road Traffic ◽  
Traffic Noise ◽  
Pressure Level ◽  
Road Traffic Noise ◽  
Efficient Measure ◽  
Natural Means

Excessive road traffic noise exposure in (sub)urban parks hinders its restorative function and will negatively impact the number of visitors. Especially in such green environments, noise abatements by natural means, well integrated in the landscape, are the most desired solutions. Although dense vegetation bordering the park or raised berms could come first in mind, local landscape depressions are typically underused. In this work, a case-study of a small suburban park, squeezed in between two major arterial roads, is analyzed. The spatially dependent road traffic noise exposure in the park is assessed in detail by mobile sound pressure level measurements. Local reductions of up to 6-7 dBA are found at landscape depressions of only a few meters deep. It can therefore be concluded that this is an efficient measure and should be added to the environmental noise control toolbox for noise polluted parks.

scholarly journals Combining VR Visualization and Sonification for Immersive Exploration of Urban Noise Standards

2019 ◽  
Vol 3 (2) ◽  
pp. 34 ◽  
Author(s):  
Markus Berger ◽  
Ralf Bill
Keyword(s):  
Real Time ◽  
Sound Propagation ◽  
Road Traffic ◽  
Expert Knowledge ◽  
Low Cost ◽  
Traffic Noise ◽  
Urban Traffic ◽  
Road Traffic Noise ◽  
Common Noise ◽  
Noise Assessment

Urban traffic noise situations are usually visualized as conventional 2D maps or 3D scenes. These representations are indispensable tools to inform decision makers and citizens about issues of health, safety, and quality of life but require expert knowledge in order to be properly understood and put into context. The subjectivity of how we perceive noise as well as the inaccuracies in common noise calculation standards are rarely represented. We present a virtual reality application that seeks to offer an audiovisual glimpse into the background workings of one of these standards, by employing a multisensory, immersive analytics approach that allows users to interactively explore and listen to an approximate rendering of the data in the same environment that the noise simulation occurs in. In order for this approach to be useful, it should manage complicated noise level calculations in a real time environment and run on commodity low-cost VR hardware. In a prototypical implementation, we utilized simple VR interactions common to current mobile VR headsets and combined them with techniques from data visualization and sonification to allow users to explore road traffic noise in an immersive real-time urban environment. The noise levels were calculated over CityGML LoD2 building geometries, in accordance with Common Noise Assessment Methods in Europe (CNOSSOS-EU) sound propagation methods.

scholarly journals Association Between Road Traffic Noise and Incidence of Diabetes Mellitus and Hypertension in Toronto, Canada: A Population‐Based Cohort Study

2020 ◽  
Vol 9 (6) ◽  
Author(s):  
Saeha Shin ◽  
Li Bai ◽  
Tor H. Oiamo ◽  
Richard T. Burnett ◽  
Scott Weichenthal ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Cohort Study ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Road Traffic ◽  
Traffic Noise ◽  
Population Based ◽  
Pressure Level ◽  
Road Traffic Noise

Background Exposure to road traffic noise has been linked to cardiometabolic complications, such as elevated blood pressure and glucose dysregulation. However, epidemiologic evidence linking road traffic noise to diabetes mellitus and hypertension remains scarce. We examined associations between road traffic noise and the incidence of diabetes mellitus and hypertension in Toronto, Canada. Methods and Results Using the Ontario Population Health and Environment Cohort, we conducted a retrospective, population‐based cohort study of long‐term residents of Toronto, aged 35 to 100 years, who were registered for provincial publicly funded health insurance, and were without a history of hypertension (n=701 174) or diabetes mellitus (n=914 607). Road traffic noise exposure levels were assessed by the equivalent continuous A‐weighted sound pressure level (dBA) for the 24‐hour day and the equivalent continuous A‐weighted sound pressure level for the night (11 pm –7 am) . Noise exposures were assigned to subjects according to their annual residential postal codes during the 15‐year follow‐up. We used random‐effect Cox proportional hazards models adjusting for personal and area‐level characteristics. From 2001 to 2015, each interquartile range increase in the equivalent continuous A‐weighted sound pressure level (dBA) for the 24‐hour day (10.0 dBA) was associated with an 8% increase in incident diabetes mellitus (95% CI, 1.07–1.09) and a 2% increase in hypertension (95% CI, 1.01–1.03). We obtained similar estimates with the equivalent continuous A‐weighted sound pressure level for the night (11 pm –7 am) . These results were robust to all sensitivity analyses conducted, including further adjusting for traffic‐related air pollutants (ultrafine particles and nitrogen dioxide). For both hypertension and diabetes mellitus, we observed stronger associations with the equivalent continuous A‐weighted sound pressure level (dBA) for the 24‐hour day among women and younger adults (aged <60 years). Conclusions Long‐term exposure to road traffic noise was associated with an increased incidence of diabetes mellitus and hypertension in Toronto.

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