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The Covid-19 crisis forced governments around the world to rapidly enact several restrictions to face the associated health emergency. The Portuguese government was no exception and, following the example of other countries, established various limitations to flat the contagions curve. This led to inevitable repercussions on mobility and environmental indicators including noise. This research aims to assess the impact of the lockdown due to Covid-19 disease on the noise levels recorded in the city of Porto, Portugal. Data from four noise sensors located in strategic spots of the city were used to calibrate and validate Time Series Models, allowing to impute the missing values in the datasets and rebuild them. The trend and the cyclic information were extracted from the reconstructed datasets using decomposition techniques. Finally, a Spearman correlation analysis between noise levels values and traffic volumes (extracted from five inductive loop detectors, located nearby the noise sensors) was performed. Results show that the noise levels series present a daily seasonal pattern and the trends values decreased from 6.7 to 7.5 dBA during the first lockdown period (March-May 2020). Moreover, the noise levels tend to gradually rise after the removal of restrictions. Finally, there is a monotonic relationship between noise levels and traffic volumes values, as confirmed by the positive moderate-to-high correlation coefficients found, and the sharp drop of the former during March-May 2020 can be attributed to the strong reduction of road traffic flows in the city. The authors acknowledge the municipality of Porto for having provided access to the data used in this work. published

Acoustic courtship displays are ubiquitous among animals. Signallers use these acoustics to advertise their willingness to mate, while receivers may be able to infer something of the signaller's quality from them. However, increases in anthropogenic noise may reduce the production, transmission and reception of these signals, leading to consequences for reproductive success. In this study, we conducted behavioural observations of courtship interactions of the Mediterranean field cricket, Gryllus bimaculatus, under anthropogenic noise conditions. We found that the presence of traffic noise had no effect on the outcome courtship interactions in this species, and their behaviour during courtship did not appear to be altered either. However, we found that the presence of white noise led to a reduction in male signal production, resulting in fewer successful matings. Males that did signal under white noise conditions had altered signal characteristics, including increased song frequency and reduced tick rate. Mate-guarding behaviour was also found to differ between individuals that courted and those that did not. The use of typical anthropogenic noise and white noise in this experiment allows us to consider the importance of specific characteristics of the acoustic pollutant in causing this disruption.

Schools are one of the land uses that are sensitive to traffic noise. While schools must be silent zones, many are located in urban areas and are exposed to high noise levels. In this study, an assessment of traffic noise around multiple schools in the city of Doha, Qatar was conducted during school hours. The results indicated that the noise is positively correlated with the traffic volume around the schools, indicating that locations with higher traffic volumes tend to have higher noise. The results also showed that the noise levels exceed the reference value of 53 dBA according to the World Health Organization. Furthermore, the measured noise levels exceeded the Qatar local standards for residential area and public corporation day-time noise level (55 dBA). To address this problem, several solutions were recommended.

Objective This paper aims to determine the level of noise generated by land transportation modes and their impact on the people who live nearby along arterial roads in the city of Parepare, Indonesia. Method This study is a vehicle traffic survey conducted simultaneously with noise level measurements using a sound level meter. The calculation uses the Equivalent Leq formula, to determine the impact arising from noise, using statistical applications. Results The highest noise level results are 88.8 dB (above the standard noise level based on Kep-48, MENLH, 11,1996 of 55–65 dB for each region). The impact of noise on public health by traffic on people who live around the road is a psychological disorder 80%, physiological disorders 35.7%, and the highest is a communication disorder 84.3%. Conclusion The impact of high-noise results needs to be socializing by the government to people who live around along the road.

Urban noise depends on several factors from which Traffic Noise is the most important. City centers and main access roads are usually over exposed that is, average day–evening–night noise level [LDEN] and/or rest expose level [LNIGHT] surpasses a threshold of healthy exposure. About 35M Europeans are over exposed. This is a problem of human health not a comfort one.In another way, energy consumption associated to Urban Traffic is in the center of human concerns. Average vehicles spend more than 3.5MJ/km. That means that one Barrel of Oil Equivalent (BOE) is spent by Urban Traffic for each 1.700km. This is a problem of human sustainability.Based on this problematic a model was developed to correlate traffic noise reduction and energy savings in order to produce guidelines for Urban Noise Management. Model is supported on experimental data and bibliographic review, under the “CNOSSOS model for road noise”. It is then possible to produce guidelines regarding noise reduction and its influence on energy savings. Relationships between “velocity reduction”, “traffic volume” and “noise and energy” are now possible.Results are available in “noise maps” and “energy saving maps” easily understandable by urban traffic managers. A case study is presented. Keywords: Traffic noise, Traffic energy, CNOSSOS-EU, Sustainability

The introduction of electric vehicles in urban areas contributes to the reduction of air and noise pollution in these environments. However, the low noise levels produced by these vehicles, previously seen as an advantage, could pose a new risk to the safety of road users. The real magnitude of this issue is, however, controversial. The present study analyses the perception of experienced electric and hybrid vehicle drivers in work situations, something which had not been studied to date. A total of 95 electric car and motorcycle drivers from different public companies in the city of Malaga, Spain, participated in the study. These drivers described risk situations with pedestrians at low speeds, especially in shared streets. They estimated that the risk caused by the low noise levels of these vehicles is “medium”. To compensate, many drivers stated that they are more alert while driving an electric vehicle. Additionally, the drivers suggested that equipping these vehicles with continuous external sound was not the most appropriate solution. In the scientific community there is no consensus on the best way to resolve this. Nevertheless, electric vehicles are now required to incorporate additional sound in the European Union and USA. This does not mean that this is a more effective solution. More research on this issue is thus needed, such as studying other non-acoustic solutions or analysing how other road users perceive the risk.

This paper studies noise pollution in the urban living environment, using Moskovsky District in Saint Petersburg as an example. We identify the hazards caused by noise pollution and conduct a comparative analysis of apartment market value, depending on the distance from motorways. We find that people living in houses along Vitebsky Prospekt and Kubinskaya Street are subjected to extreme levels of traffic noise; those living in houses along Moskovsky Prospekt and Leninsky Prospekt are subjected to high levels of traffic noise; and those living in houses along Blagodatnaya Street, Novoizmaylovsky Prospekt, Varshavskaya Street, Basseynaya Street, and Kostyushko Street are subjected to increased levels of traffic noise. Our health hazard assessment reveals that traffic noise creates an extreme risk of cardiovascular disease among senior citizens (aged over 65) that live in apartments with windows facing Vitebsky Prospekt and Kubinskaya Street. Besides, the evaluation of the real estate market made up by apartments in the standard “khrushchyovka” buildings of Moskovsky District points to the public becoming more demanding towards the living environment quality: the price for apartments located along noisy highways is approximately 10% lower than the price for apartments in quieter neighborhoods.

Dynamap (DYNamic Acoustic MAPping) is an European Life project whose main scope is to implement “real-time” acoustic maps in a district of the city of Milan. Dynamap is based on the idea of finding a suitable sets of roads displaying similar traffic noise behavior so that one can group them together into single noise maps. Twenty-four monitoring sensors have been installed permanently in appropriate locations within the pilot zone (District 9) to obtain six dynamic noise maps. The project has come to its “Test and Fault Analysis” phase. A set of new traffic noise and traffic flow measurements have been recorded to shed light on the reliability of Dynamap prediction. Besides the expected error due to statistical fluctuations of traffic noise, our preliminary analysis show a systematic error inherent to the adopted traffic flow model, which is an essential ingredient of the whole approach. By correlating the traffic noise prediction error to the one due to the traffic flow model, we succeed in improving the Dynamap prediction thus limiting the overall error to within about 3 dB. We suggest that Dynamap scheme can be applied to large urban conglomerates in general, thus becoming a useful tool for monitoring traffic noise accurately and efficiently in large cities.

In this study, models for predicting traffic-noise annoyance based on noise perception, noise exposure levels, and demographics were developed. By applying machine-learning techniques, in particular artificial neural networks (ANN), support vector machines (SVM) and multiple linear regressions (MLR), the traffic-noise annoyance models were obtained, and the error rates compared. A traffic noise map and the estimation of noise exposure for the case study area were developed. Although, it is quite evident that subjective noise perception and predicted noise exposure levels strongly influence traffic-noise annoyance, traditional statistical models fail to produce accurate predictions. Therefore, a machine-learning approach was applied, which showed a better performance in terms of error rates and the coefficient of determination (R2). The best results for predicting traffic-noise annoyance were obtained with the ANN model, obtaining 42% and 35% error reduction in training subsets compared to the MRL and SVM models, respectively. For testing subsets, the error reductions were 24% and 19% for the corresponding models. The coefficient of determination R2 increased 3.8 and 2.3 times using ANN compared to MRL and SVM models in training subsets respectively, and 1.7 times (in both MRL and SVM models) for testing subsets. In this way, the applied methodology can be used as a reliable and more accurate tool for determining the impact of transportation noise in urban context, promoting the well-being of the population and the creation of suitable public policy.

Vehicle dynamics can play a significant role in the noise emission from heavy vehicles. In this work, a heavy vehicle noise emission model is presented to study the influence of translational vehicle dynamics on the sound power level emitted by heavy-duty trucks. Vehicle speed and acceleration are calculated using an analytical approximation that describes the tractive and retarding forces acting on a heavy vehicle on grade. Heavy vehicle noise emission associated with rolling noise is defined with reference to the Nordic traffic noise model that takes into account the number of axles for different articulated trucks. An expression for engine noise emission in terms of vehicle speed, weight, engine power, aerodynamic properties and road grade is derived. The individual and combined effects of engine noise and rolling noise for different vehicle mass combinations are examined. The influence of road grade on vehicle kinematics and noise emission is also investigated.

The acoustic conditions of classrooms received a lot of attention in the last decades because of its important role in school children’s comfort and performance. In a previous field study of 54 classrooms from 21 schools in the Netherlands, more than 85% of the 1145 primary school children reported that they were bothered by noise in the classroom. The objective of this study is to identify the effect of background sounds on children’s performance, sound evaluation and influence assessment based on a lab study conducted in the SenseLab. 335 school children (9 to 13 years old) from the previous studied schools participated in the lab study. They were subjected to a series of listening tests and evaluations in two acoustic test chambers (acoustically treated or untreated) with one of seven randomly played background sounds: 45 dB(A) or 60 dB(A) traffic noise, 45 dB(A) or 60 dB(A) children talking, 45 dB(A) or 60 dB(A) music, or no sound (≈30 dB(A)). A two-way ANOVA was applied to analyse the interaction effect of sound type and sound pressure level (SPL) on children’s performance, sound evaluation and influence assessment in each of the chambers. Statistically significant interactions between the impact of sound type and SPL on children’s phonological processing performance and their influence assessments were found in the untreated chamber.

Urban road networks significantly influence traffic noise. However, existing studies have neglected the causal chain between road characteristics and traffic noise; thus, clarity on their influencing mechanisms is lacking. In this study, structural equation models were developed to explore the mediated effect of road characteristics on traffic noise through traffic flow using data from field measurement in Dalian City, China; paired comparisons of scenarios though microscopic and macroscopic traffic simulations were performed for further analysis. The results show that lane number influences traffic noise mainly in terms of the number of vehicles in a group (NVG). More lanes indicate increased traffic demand due to connected urban land, which increases the NVG and, in turn, increases noise intensity but decreases noise amplitude. The influence of road segment length (RSL) on traffic noise mainly depends on the suppression effect. A longer RSL allows for higher vehicle speeds, leading to increased noise intensity and reduced noise amplitude. This also indicates that traffic flows disperse more easily, decreasing the NVG and, in turn, reducing noise intensity and increasing noise amplitude. Road junctions (RJ), which are classified according to the presence or absence of traffic lights, have significant direct effects on both noise intensity and noise amplitude, which are both likely to increase as drivers accelerate or decelerate in the middle of the road segment. These findings provide a reference for local governments and urban planners when working to improve quality of life in urban areas.

Porous asphalt courses (PAC) provide environmental and safety benefits by reducing traffic noise and improving drainability. As pressure increases on the cost and availability of natural resources, a greater understanding is needed of field performance to allow maintenance and preservation of resilient, sustainable and economic networks. The main purpose of this paper is to utilize life-cycle cost analysis (LCCA) as a decision-support tool for three pavement rehabilitation strategies. These alternatives included open-graded friction course using natural aggregate (OGFC), porous asphalt course using natural aggregate (PAC), and porous asphalt course using steel slag (SS-PAC). The LCCA followed the Federal Highway Administration’s RealCost procedure and incorporated information collected from highway agencies. Based on the results of the performance analysis, pavement life-cycle models were developed for each alternative. Using the life-cycle models and historical unit costs, deterministic and probabilistic LCCAs were conducted. The results demonstrated the cost saving of SS-PAC in both low and medium price ranges. In order to have economic benefits, the service life of SS-PAC needed to be more than eight years for a high price range. SS-PAC had a 78 and 92 percent chance of being more cost-effective than OGFC and PAC according statistical analysis, respectively. Conclusions from the LCCA supported use of the SS-PAC alternative since SS-PAC was shown to be relatively cost-effective over the 40-year analysis period. Utilization of the SS-PAC alternative would combine cost efficiency and sustainability for highway projects, especially rehabilitation and reconstruction.

Recent studies have discovered that acoustic metasurfaces possess great versatility in designing novel acoustic systems. An earlier theoretical study pointed out that acoustic metasurface constructed using an array of resonant-duct unit cells can provide superior sound insulation while allowing air to ventilate through the openings distributed on the surface. By using such a principle, a full-scale metasurface ventilation window is designed and experimentally demonstrated in this study. The primary goal of this paper is to detail the acoustic design methodology for developing this window prototype and to characterize its sound insulation performance in-situ. The dimensions of the metasurface window and its unit cells are tuned based on acoustic Finite Element (FE) analysis to enhance its noise reduction for traffic noise frequency, as well as to increase the single number quantity (SNQ) noise rating. The measured transmission loss (TL) shows a consistent behavior with the prediction in the design frequency range. Comparing the proposed window to a conventional casement window with an equal opening area, the SNQ from measurement for the metasurface window is 22 dB, which is 7 dB higher than the casement window at 15 dB. The substantial improvement shows the benefit of incorporating metasurface concept into the design of sound insulation components, such as building facade, noise barriers, etc.

AimThis explorative study aimed to investigate the association of residential greenness, traffic noise, and air pollution with birth outcomes in several Alpine areas with unique topography.Methods: We used data from two cross-sectional studies (UIT, n = 573 and BBT, n = 518) in the Tyrol Region (Austria/Italy). Only mothers who had lived in their current residence during the whole pregnancy were included. They completed a questionnaire, and medical records were used to draw data on birth weight, low birth weight (LBW), preterm birth, and small for gestational age (SGA). Normalized Difference Vegetation Index (NDVI) in the year of birth was assigned at the residential address as a measure of greenness. Road/railway traffic noise (L-dn) and air pollution (NO2) were calculated about 10 years after birth and used as surrogates for exposure levels during pregnancy.Results: In the UIT survey, higher NDVI500-m was consistently associated with lower odds for LBW and SGA, while an increase of L-dn was associated with higher odds for 113W. Other effect estimates were in the expected direction albeit non-significant. In the BBT survey, most findings were inconclusive (for NDVI) or present only in subgroups (for L-dn and NO2).Conclusion: This study provides inconclusive evidence that the surrounding environment might be associated with birth outcomes in mountainous areas. Given the disparate associations across the study areas, further research in larger representative samples is warranted. (C) 2019 Elsevier B.V. All rights reserved.

Low noise asphalt pavement mitigates the impact of traffic noise on the ecological environment and surrounding population to a certain extent. To explore the noise reduction characteristics of different asphalt pavements, an indoor simulation device for pavement noise reduction is developed in this paper, based on the principle of pavement noise reduction. The device simulates the process of noise reflection and interference on the surface and inside of the pavement, which consumes the sound energy to achieve the noise reduction effect. The mechanical performance of six different types of asphalt mixtures is first tested. The noise reduction performance of the asphalt mixtures is then studied using the self-made noise testing device and Kundt’s tube method to verify the accuracy of the device. The influence of surface texture on pavement noise is also analyzed, and test results show that the six types of asphalt mixtures used in this study all meet mechanical performance requirements. A strong correlation is also observed between the noise testing device and the traditional Kundt’s tube method. The noise testing device is found to accurately measure the noise reduction characteristics of asphalt mixtures. For noise of different sound pressure levels, the same type of asphalt mixture displays different noise reduction capabilities. The better the noise reduction performance, the lower the sensitivity to sound wave changes, and the more stable the noise reduction effect. Excessive air void content does not significantly improve the pavement noise reduction performance, and it is recommended that the pavement air void content is maintained within the range of 17%–24%. The density of the asphalt mixture is found to be negatively correlated with the noise reduction performance, while the air void content and the mean texture depth is positively correlated with noise reduction. The results of grey relational analysis show that air void content is the most important factor affecting the noise reduction characteristics of asphalt pavement, followed by mean texture depth. Aggregate particle size is also found to exert a significant influence on noise reduction characteristics, and the influence degree of 9.5 mm particles is found to be the greatest, with 1.18 mm and 2.36 mm particles also showing a high degree of influence. Reasonable control of aggregate particle size should therefore be carried out in the design of low noise asphalt pavement.

This study investigated impact of urban traffic on the acoustic comfort of roadside schools through both in-field measurements and on-site survey questionnaires. Six secondary schools were targeted, which are located near various types of roads in a prototype major city, Taiyuan, in the northern China. Noise levels were measured in front of the schools, in the schoolyard, and in the classrooms. The results indicated that noise pollution in these roadside schools was quite serious, and the school noise levels significantly correlated with the road traffic noise. The maximum measured equivalent A-weighted sound level (LAeq, 20min, LAeq) was 74.2 dB(A) near an expressway, which is 35% higher than the exterior threshold value (55.0 dB(A)) recommended by the World Health Organization. The on-site questionnaires revealed that all the students felt being disturbed by the road traffic noise and the degree of disturbance increased with the traffic level. Other noises (e.g., those from adjacent classrooms and that produced by student activities) were found acceptable. Further correlation analysis demonstrated a strong linear correlation between the level of road noise and highly disturbed respondents (R2: 0.928, p

Road Traffic Noise (RTN) is one of the biggest pollutants in modern cities, which is known to affect public health to be the direct cause of many illnesses for their inhabitants. Until recently, RTN maps have been generated using representative static measurements collected by experts, after manually discarding all non-traffic related noise events, or Anomalous Noise Events (ANEs). However, the automation of noise measurements using Wireless Acoustic Sensor Networks (WASNs) is allowing the development of dynamic maps, which require the detection of non-traffic noise sources in real-time in order to provide accurate noise level measurements. In this work, the manual an automatic removal of ANEs are compared. The latter is based on two versions of the Anomalous Noise Event Detector (ANED) designed to detect ANEs within a WASN in real-time as a two-class classifier. The experiments on 4 h and 44 min of real-life audio data show similar error rates among all the considered annotation methods. However, the detailed analysis of the experiments reveal, on the one hand, inconsistent manual annotations in certain non-ANE labelling situations, where non-coincident expert-based decisions are observed; and, on the other hand, the decrease of the overall accuracy of the ANED-based approaches due to the large number of false alarms in the case of RTN class. Thus, although the results demonstrate the viability of the automated removal of ANEs, further research should be conducted to keep improving the automation of ANEs annotation.

Traffic noise is an important area of research in several countries, since it can present a significant environmental health problem. Brazil is currently considered a country with extremely high vehicular noise levels and yet there is currently no specific legislation to reduce traffic noise. Also, with regard to data on the sound pressure levels of highways, acoustic reference levels are non-existent. The aim of this study was to characterize the noise levels of Brazilian highways (specifically in the state of Santa Catarina) with six different types of pavements and textures (dense-graded asphalt mix, dense-graded rubberized asphalt mix, porous friction layer, gap-graded asphalt mix, micro-coating asphalt, rigid concrete pavement) using the first tire-road measurement trailer developed in Brazil and applying the close proximity (CPX) method. The results indicate that the porous friction layer has the lowest noise index (CPXI) when compared to the other pavements studied. In the tests carried out with the CPX trailer on the rigid pavements there was no significant difference between the results for the final CPXI values. The measurements taken with the CPX trailer and the sand patch method showed that the macro-texture of dense mixes has a notable influence on the generation of mechanical noise. Statistical correlations between the results obtained with the CPX, CPB and sand patch methods are reported herein and the data show that it is possible to predict the tire-road noise emission as a function of distance.

A parametric study on the traffic noise transmission loss across plenum windows was carried out experimentally in this investigation in an attempt to establish a simple empirical model for predicting this transmission loss. A total of fourteen full scale plenum windows were included in this study. The results of a site mockup measurement were used for model validation. The present model was developed based on the existing plenum chamber theory in which the sound fields inside the plenum window cavities were assumed to make up of a diffracted wave and a reverberant field. Results suggest that both the diffracted and reverberant field inside the plenum window cavities are weaker than those assumed in existing plenum chamber theory. It is found that a model, which assumes frequency-independent diffraction directivity and percentage reverberant field attenuation, gives the best prediction of traffic noise transmission loss. This prediction model is also able to predict site test results with good accuracy.

This study investigated the effect of a fragrant tree on the perception of traffic noise, aiming to reveal the interaction between odour and sound in urban environment. Field research investigations including on-site measurement and questionnaire distribution were conducted in two conditions (with and without fragrance) in four streets in Harbin, China, where lilac had been planted. The results showed that fragrance could affect the perception of traffic noise, which was reflected in increased overall comfort of the street, decreased annoyance caused by traffic noise, and improvement in auditory and olfactory satisfaction. The subjective evaluation of a street where double rows of lilac were planted was superior to that of single-row streets, and a decrease in traffic noise annoyance was more evident when the streets had lower traffic noise levels. The study also found that the higher the congruency of the fragrance and the environment, the more comfortable and less annoyed people were. Finally, familiarity, preference, and subjective intensity of fragrance did not correlate with overall comfort or traffic noise annoyance.

Using Lorenz-type curves, means tests, ordinary least squares, and locally weighted regressions (LWR), we examine the relative burdens of whites, blacks, and Hispanics in Georgia from road and air traffic noise. We find that whites bear less noise than either blacks or Hispanics and that blacks tend to experience more traffic noise than Hispanics. While every Metropolitan Statistical Area (MSA) showed that blacks experienced relatively more noise than average, such a result did not hold for Hispanics in roughly half of the MSAs. We find much heterogeneity across Census tracts using LWR. For most Census tracts, higher black and Hispanic population shares are associated with increased noise. However, 5.5% of the coefficients for blacks and 18.9% for Hispanics are negative, suggesting larger population shares are associated with less noise. The noise LWR marginal effects for black populations across most tracts in the state are consistent with diminishing marginal noise from additional black population, while those in Atlanta exhibit diminishing marginal noise for Hispanics. In many regions of the state where the potential for health-damaging noise exists, we find relatively high disproportionality in noise experienced by the black and Hispanic populations compared to the rest of the overall population. Our findings underscore the importance of using nonparametric estimation approaches to unveil spatial heterogeneity in applied urban and housing economics analyses.

Successful reproduction in most anurans is associated to acoustic communication and negative effects of auditory masking by natural biotic and anthropogenic noise are known in this group. However, the potential additive effect of both noise types has been scarcely studied. We examine in situ the acoustic variation of 135 males (n = 975 calls) of Odontophrynus americanus in areas from Central Argentina with (TN) and without traffic noise (N-TN) and in presence (Ch) or absence (N-Ch) of chorus. The effect of noise condition on four call properties (call duration [CD], intercall interval [ICI], pulse rate [PR] and dominant frequency [DF]) were analyzed using linear mixed models (LMM and GLMM). A Principal Component Analysis (PCA) was performed to identify the acoustical properties that best accounted for variation among all possible noise conditions (N-TN/N-Ch; N-TN/Ch; TN/N-Ch and TN/Ch). PR and DF showed significant higher values in TN than N-TN sites while a significant increase in ICI and a decrease in DF were found in chorus situation. Analyzing combined effects, PR significantly increased in N-TN/N-Ch condition and decreased under TN/Ch. ICI was significantly higher in N-TN/N-Ch condition. PCA showed a separation of males calling in noisy condition mainly associated to higher values of DF and CD. The acoustic variation observed in noisy environments could have implications in the reproductive strategies of the individuals although new studies should be conducted to analyze the effect of this variation on the recognition and choice by females. Our outcomes highlight the importance of conducting in situ behavioral studies considering the additive effects of different environmental noise sources. Fil: Grenat, Pablo Raúl. Universidad Nacional de Rio Cuarto. Facultad de Cs.exactas Fisicoquimicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Cordoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente.; Argentina Fil: Pollo, Favio Ezequiel. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Departamento de Ciencias Naturales. Cátedra de Ecología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Ferrero, María A.. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Departamento de Ciencias Naturales. Cátedra de Ecología; Argentina Fil: Martino, Adolfo Ludovico. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Departamento de Ciencias Naturales. Cátedra de Ecología; Argentina

In 2015, the Ecuadorian regulation related to noise considered the need to develop noise maps as a strategic tool for the noise pollution management and urban planning. However, no specific methodology has been established yet. Therefore, this study aims to develop Quitos first traffic noise map by using computer-aided predictive model, an official data of road network, buildings and population. Three noise prediction models (RLS-90, STL-86, and NMPB-Routes-08) were initially used to compare the modelled and measured results. Short time noise measurements and vehicle counts were used as a means of prediction model validation. The comparison showed that the RLS-90 model was the most suitable for predicting traffic noise levels, in this case of study. Using simplified information about traffic flow, building sound absorption and road surface, a cost-effective traffic noise assessment was obtained. The results of noise evaluation on building facade estimates that during daytime 25% of the people living in the urban area of Quito is exposed to road traffic noise levels above 65 dBA, considered as high and undesirable. While the results for night-time estimate that 38% of the population are exposed to traffic noise levels, considered as increasingly dangerous for public health. The results of this study may be considered as a starting point for the city urban planning, mobility managing and policy making.

Tyre-road noise is the most important source of traffic noise in the mid-to-high speed range. The use of low noise road surfaces represents an ideal solution to mitigate traffic noise, because it directly affects the source, generating a widespread benefit for all the dwellings near the road and decreasing the number of people annoyed. More knowledge about long-term acoustic performance is required to promote the use of low noise road surfaces as mitigation action. In fact, as for a traditional road surface, the acoustic properties of low noise surfaces worsen over time: only by knowing the initial noise reduction and its time evolution, public administrations can design their application and related maintenance plans. In this work, an innovative approach was used to investigate and model acoustic ageing of some rubberized road surfaces surveyed for several years. This type of quiet pavements represents an efficient road surface technology in terms of traffic noise reduction. A new regression model was applied to estimate the acoustic ageing of the investigated pavements, considering the complex interacting system composed of three main elements: pavement type, traffic loads and climatic conditions.

The effects of indoor water sounds on traffic noise perception were investigated under three room temperatures of 18 °C, 24 °C, and 30 °C through listening experiments with 54 participants. Two types and four levels of water sounds (35, 40, 45, and 50 dBA) were presented with four levels of traffic noise (45, 50, 55, and 60 dBA) in an indoor environmental test laboratory. Water sounds were recorded using a simple indoor fountain comprising a submersible pump and two types of nozzles (foam-jet and mushroom), which generated different water sound spectra. The listeners assessed the thermal and acoustic environments on eleven adjective attributes, representing negative acoustic attributes, positive acoustic attributes, acoustic comfort, thermal comfort, and overall comfort. The results showed that indoor water sounds enhanced pleasantness, calmness, and naturalness without increment of noisiness, loudness, or annoyance in the 30 °C condition, while no perceptual improvement of traffic noise was found in the 18 °C and 24 °C conditions. Room temperature affected both thermal perception and acoustic perception. Water sounds affected not only acoustic perception, but also thermal and overall indoor environmental comfort. A just noticeable water sound level was preferred to mitigate intrusive traffic noise perceptually in a room. The noise perceived in a room should be described by both negative and positive adjectives together, in order to evaluate the effects of indoor environment, such as water sounds and temperature, on noise perception.

A frequency-domain formulation based on Method of Fundamental Solutions (MFS) is used to simulate the sound field generated by a point source in the presence of a T-shaped thin noise barrier. The MFS formulation is here developed by making use of adequate Green's functions, defined by using the image-source technique, that satisfy specific boundary conditions, allowing decreasing the number of discretized surfaces and consequently reducing the computational cost of the numerical model. Both the ground and the building are modeled as infinite rigid plane surfaces, and the barrier is assumed to be absorptive. The surface treatment of the barrier is characterized by a porous material. The Zwikker and Kosten model is here used for predicting the acoustic properties of the porous material. To validate the numerical implementation of the proposed method, the results are compared with solutions of the Dual-BEM formulation. Numerical simulations are carried out in order to demonstrate the efficiency of the proposed method and the performance of the T-shaped thin noise barriers in typical cases of traffic noise.

© 2018 Elsevier Ltd Practical implementation of active noise control (ANC) systems for outdoor traffic noise reduction remains rare. One challenge is the difficulty of configuring an ANC controller due to moving noise sources, which are typically located far from ANC systems. In this paper, a pseudo noise source method is proposed for configuring fixed-coefficient feedforward ANC systems for traffic noise control. First, a minimum of one pseudo noise source is placed near an ANC system to determine the control coefficients in the tuning stage. Second, the ANC systems are run to reduce the noise from far-field traffic noise sources using the optimal control coefficients in the cancelling stage. The feasibility and limitations of the proposed method are investigated by illustrating the effect of the pseudo noise source position on the noise reduction performance of the ANC system. The simulation results show that the performance of the ANC system increases with distance when the pseudo noise sources move farther from the system but approaches a constant when the pseudo noise sources are in the far field. The indoor experimental results are consistent with the simulation results. The outdoor experimental results of a six-channel coupled system show a noise reduction of 3 dB below 500 Hz at the position of a dummy head.

Porous asphalt pavements have been used successfully in practice to improve stormwater management, increase wet-weather driving safety and reduce traffic noise. However, the sustainability of these functional performances is a major practical concern because they are often seriously affected by clogging during service. This paper proposes a laboratory evaluation procedure to compare the clogging potential of two common forms of porous pavement design, and how their drainage capacity, skid resistance and sound absorption properties are affected by clogging. For illustration, the following four designs were considered: (A) Single-layer design with 25% porosity; (B) Single-layer design with 20% porosity; (C) Double-layer design having on top of Design A a 20% porosity upper layer with 11.2 mm top size aggregate; and (D) Double-layer design having on top of Design A a 20% porosity upper layer with 8.0 mm top size aggregate. Test results show that Design A was least prone to clogging, followed by Designs B and C, and Design D was most prone to clogging. However, Designs A and B suffered severe losses in their sound absorption capability when fully clogged, while the other two designs were significantly less affected by clogging. These different behaviors of the porous asphalt designs with respect to clogging potential and sound absorption capability have important implications on pavement drainage capacity, skid resistance and noise management, and the frequency and method of declogging maintenance. They provide useful information for pavement engineers in the selection of porous asphalt surface course design.

Background One of the major environmental problems of the modern world is noise. A health-related marker of environmental noise exposure that can be considered a predictor of annoyance is noise sensitivity. The aim of this study was to ascertain the correlation between levels of exposure to road traffic noise in residential areas and the resulting annoyance based on the perception and sensitivity reported. Methods The study involved noise assessment, with the creation of noise maps of the neighborhood in the city of Sao Paulo, Brazil, and application of a questionnaire to ascertain the perception of the residents of the neighborhood, regarding the effects of this exposure. Results The noise levels at all the measured points were found to exceed the critical level for the area, 55 dB(A). A total of 225 interviews were conducted. Noise-related annoyance was reported by 48.4% of the respondents. Associations were observed between living in areas exposed to traffic noise and feeling annoyed with this noise (p Conclusions These findings suggest the importance of reviewing and updating Brazilian public policies regarding environmental noise. We found a high prevalence of annoyance reports, as well as aspects indicative of sensitivity to noise exposure.

Due to improvements on combustion-engines and electric-engines for cars, tyre noise has become the prominent noise source at low and medium speeds. Models exist that simulate the noise produced by a rolling tyre, as do models that auralize different traffic situations from a basic data set. In this paper, an established model for tyre noise (SPERoN) is combined with an auralization tool. The combined model can predict the spectrum of the sound at 7.5 m, as well as reproduce the sound for a given listener position. The auralization uses a methodology where recorded sounds are converted to source signals for engine and tyre/road-interaction. These can be shaped by the spectra estimated in SPERoN and synthesized back into a pass-by signal. Psychoacoustic judgements were used to compare the modelled signals with recorded signals. To see how well the modelled signals match the real recorded signals for perception, two listening-tests were performed. The simulated and recorded signals were rated by pleasantness, loudness, roughness and sharpness using semantic differentials. It was found that responses for simulated and recorded signals correlate for all cases, but rankings could not be reproduced exactly. The model can be further improved to be more applicable for listening tests.

Nowadays, society has the need for air transportation all around the world. The yearly increase in the number of passengers forces airports to operate to a maximum of their capacity. This leads to an augmentation of the fleet of each airline and consequently to an increase in aircraft noise emissions. Accordingly, procedures for measuring aircraft noise levels have been developed. There are international standards that specify how transport noise (aircraft, traffic and railroad) must be measured. ISO 1996-2 standard has an appendix called Annex B which specifies the reference position of the microphone to undertake the measurement, and simplified correction factors to use in case that the measurement must be located near a reflecting surface (3 dB) or directly over a reflecting surface (6 dB). A facade behaves like a reflecting surface and the correction factor to apply is relevant to the study of noise because with the reflections produced on the outside of a building, people nearby can be affected. Therefore, numerous studies verifying the correction factors of ISO 1996-2 Annex B have been performed on facades, particularly for traffic noise. Most of the findings from these studies demonstrate that features of the source-receiver geometry change the correction factor. However, this correction factor has not been tested yet for aircraft noise whose source-receiver geometry differs from that of traffic noise. This paper intends to test the correction factor for aircraft noise on facade. It also tries to determine which relationship can be found among the noise level at the reference position and features like the facade noise level, source-receiver geometry and flight type.

The primary objective of this study is to propose a method for assessing population exposure to road traffic noise based on high-resolution population and grid-level noise data. First, after meshing the study region and setting the receivers at the nodes, the noise values of all receivers are calculated by regarding roads as linear sound sources, and these values are rendered as the traffic noise distribution. Next, a population distribution model is trained with point of interest (POI) sample data, population sample data, and the random forests algorithm. Then, the statistics of the POIs in the grids are input to the trained model as the noise distribution; the grid-level population data are obtained and used to depict the population distribution. Then, to facilitate the assessment, the grid-level traffic noise distribution data and population distribution data are combined according to the ID or location of the nodes of grids. Finally, evaluation indexes considering the traffic noise and population distribution are used to assess the population exposure to traffic noise. The proposed method is applied to three types of regions in Guangzhou: a residential area, a commercial area and an industrial area. The noise pollution levels of all study regions are ‘Mild’, but the pollution of road traffic noise is most severe in the residential area with 12.00% of the population and 7.60% of the area affected due to the denser road network and stricter standards. These results indicate that people in residential areas are more sensitive to road traffic noise.

This paper studies urban development trends, both in residential and non-residential areas, and tries to optimize its design in order to obtain increased acoustic comfort especially inside dwellings. Noise pollution is an actual problem in all developed countries and it plays a major role in the decreased general health state of the population, being one of many causes of stress based diseases. In order to improve the comfort of living in noisy areas multiple solutions regarding acoustic treatments and sound insulation are constantly improved and are being used around the globe. The main innovation of this study is the approach regarding the noise problem, instead of studying sound insulation materials and techniques it focuses on general urban planning regarding the shape of buildings, and street orientations, positioning new parks and constructing earth embankments, all of these in order to reduce the noise impact on the citizens outside and inside their homes. There were two sites that were studied in some of the noisiest areas in the city of Cluj-Napoca, one regarding railroad noise pollution and one regarding traffic noise, both in residential areas of the city. Results proved that urban planning must be made with some logical considerations regarding sound propagation and amplification mechanisms in order to improve the comfort and people wellbeing in future developments. Original aspects were studied as presented earlier in the different approach of the problem that focuses on avoiding or diminishing the problem rather than attenuating it.

Annoyance and sleep disturbance caused by transportation noise are frequently associated with heavy vehicles. The ability to accurately predict heavy vehicle noise impact using conventional road traffic noise prediction methods has reduced over the years as the variety of heavy vehicles have increased progressively and the predominant long haul freight vehicle is trending towards larger trucks with a greater number of axles. In this paper, a six-category heavy vehicle source emission model in free-flowing condition has been developed based on the state-wide road setting in New South Wales, Australia. The six-category model allows traffic noise across the road network, carrying a diverse fleet of heavy vehicles, to be predicted with notably higher accuracy and precision in comparison to conventional models that aggregate heavy vehicles into one, or at most, two distinct categories. A comparative analysis is carried out to examine the source emission from various traffic mix scenarios in urban areas and along major freight routes. Current findings also highlight the importance of distinguishing regional characteristics in a harmonised road traffic noise prediction model.

Traffic noise pollution is a widespread public health problem in both developing and developed countries. Quickly and effectively evaluating the quality of an urban acoustic environment is an important challenge for urban planning and management. To solve this problem, this study first classified the urban function area of the study area according to the functional characteristics and environmental quality requirements of the region, and then, the traffic noise propagation model was applied to predict instantaneous sound levels (LA) based on noise attenuation. Finally, a traffic noise evaluation model was proposed to evaluate the quality of the urban acoustic environment. Taking Changchun city as our study area, eighty field samples of equivalent noise levels ( L eq ) were measured every ten minutes at four types of roads, classified as trunk roads, secondary roads, expressways and rural roads, in different urban function areas. An urban noise map was drawn to reflect the degree of traffic noise pollution. By comparing the measured and predicted values of noise levels, the results show that the traffic noise propagation model can be used to predict instantaneous sound levels. The traffic noise evaluation results show that the quality of the acoustic environment in our study area was at a medium level, which means that long-term exposure to it can affect the normal work and life of people. The traffic noise propagation model and proposed evaluation model are feasible methods for evaluating the quality of the acoustic environment and can provide a reference for the management of noise pollution control of urban traffic.

Porous pavements are designed and constructed today to provide one or more of the following functional benefits: lower traffic noise, improved wet-weather driving safety, lower stormwater peak load, and replenishment of groundwater supplies. However, depending on the mix design and material properties of a porous pavement, not all these benefits can be achieved fully by the porous pavement. The factors that affect such functional benefits include the porosity, the properties of binder and aggregates, and the binder content and aggregate gradation of the porous mixture. Currently no agencies have specified any laboratory test procedure for pavement engineers to evaluate the functional characteristics during the mix design phase. Such laboratory procedures are useful in practice for porous pavement design. This study demonstrates that a set of laboratory tests based on currently available equipment and methods, along with related functional assessment analysis, can be performed to meet the purpose. The following laboratory tests on the design mix are proposed in this study: (i) Permeability test. (ii) 3-dimensional scanning of surface texture, (iii) Skid resistance test, and (iv) Sound absorption test. The test data may then be used for drainage capacity analysis, wet-weather skid resistance assessment, and tire-pavement noise analysis. The proposed laboratory test procedures are illustrated using two porous pavement materials. The test results show that practically useful information on functional characteristics of a design porous mix can be obtained using the proposed procedures.

Passive surface wave methods utilizing traffic noise have been studied in recent years to estimate shear wave velocity in urban near-surface explorations. Suitable processing scheme is necessary for the emergence of coherent signal, and even to account for the azimuthal effects in acquired noise data. We propose a new ambient noise data selection technique based on the asymmetry of the cross-correlation functions to refine the quality of data processing in the complex city environment. The asymmetry coefficient is defined by the logarithmic energy ratio of the casual and acausal surface waves to measure the correlation asymmetry, and two kinds of symmetric functions are taken into account to establish the screening conditions. The underlying physics for the symmetries of the correlation functions are demonstrated to prove the feasibility of our algorithm. Two numerical tests suggest that the bidirectional inline sources are adequately highlighted, and the high velocity anomalies caused by the offline sources are eliminated by our method. Furthermore, the significances of the applications of time window and normalization are investigated to improve the reliability of the algorithm. We also apply the method to three-component field data acquired from the city pavement. The comparisons between the results of raw and selected data confirmed that the random noise and the artifacts can be effectively suppressed, and the dispersion energy trends emerge clearly and become more convergent toward the lower frequency. Finally, our method is concluded to be practical for urban bidirectional traffic noise.

Background: Growing evidence supports the concept that traffic noise exposure leads to long-term health complications other than annoyance, including cardiovascular disease. Similar effects may be expected from wind turbine noise exposure, but evidence is sparse. Here, we examined the association between long-term exposure to wind turbine noise and incidence of myocardial infarction (MI). Methods: We used the Danish Nurse Cohort with 28,731 female nurses and obtained data on incidence of MI in the Danish National Patient and Causes of Death Registries until ultimo 2013. Wind turbine noise levels at residential addresses between 1982 and 2013 were estimated using the Nord2000 noise propagation model, as the annual means of a weighted 24-hour average (Lden) at the most exposed façade. Time-varying Cox proportional hazard regression was used to examine the association between the 11-, 5- and 1-year rolling means prior to MI diagnosis of wind turbine noise levels and MI incidence. Results: Of 23,994 nurses free of MI at cohort baseline, 686 developed MI by end of follow-up in 2013. At the cohort baseline (1993 or 1999), 10.4% nurses were exposed to wind turbine noise (≥1 turbine within a 6000-m radius of the residence) and 13.3% in 2013. Mean baseline residential noise levels among exposed nurses were 26.3 dB, higher in those who developed MI (26.6 dB) than among those who didn't develop MI (26.3 dB). We found no association between wind turbine noise and MI incidence: adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) comparing nurses with 11-years mean residential noise levels of 29.9 dB, to non-exposed nurses were 0.89 (0.64–1.25), 1.20 (0.82–1.77), 1.38 (0.95–2.01), and 0.88 (0.53–1.28), respectively. Corresponding HR (95% CI) for the linear association between 11-year mean levels of wind turbine noise (per 10 dB increase) with MI incidence was 0.99 (0.77–1.28). Similar associations were observed when considering the 5- and 1-year running means, and with no evidence of dose-response. Conclusions: The results of this comprehensive cohort study lend little support to a causal association between outdoor long-term wind-turbine noise exposure and MI. However, there were only few cases in the highest exposure groups and our findings need reproduction.

Traffic-related air and noise pollution may increase the risk for cardiovascular disorders, especially among susceptible populations like pregnant women. The objective of this study was to evaluate the association of exposure to traffic-related air pollution and traffic noise with blood pressure in pregnant women. We extracted systolic blood pressure (SBP) and diastolic blood pressure (DBP) at ≥20 weeks gestation, as well as hypertensive disorders of pregnancy from medical records in the HOME Study, a prospective pregnancy and birth cohort from Cincinnati, OH (n = 370). We estimated exposure to elemental carbon attributable to traffic (ECAT),11 ECAT = elemental carbon attributable to traffic. a marker of traffic-related air pollution, at women's residences at ~20 weeks gestation using a validated land use regression model and traffic noise using a publicly available transportation noise model. We used linear mixed models and modified Poisson regression adjusted for covariates to examine associations of ECAT and traffic noise with blood pressure and hypertensive disorders of pregnancy risk, respectively. In adjusted models, we found a 1.6 (95% CI = 0.02, 3.3; p = 0.048) mm Hg increase in SBP associated with an interquartile range increase in ECAT concentration; the association was stronger after adjusting for traffic noise (1.9 mm Hg, 95% = 0.1, 3.7; p = 0.035). ECAT concentrations were not significantly associated with DBP or hypertensive disorders of pregnancy, and traffic noise was not associated with SBP, DBP, or hypertensive disorders of pregnancy. There was no evidence of a joint effect of traffic noise and ECAT on any outcome. In this cohort, higher residential traffic-related air pollution exposure at ~20 weeks gestation was associated with higher SBP in late pregnancy. It is important for future studies of traffic-related air or noise pollution to jointly consider both exposures and neighborhood characteristics given their correlation and potential cumulative impact on cardiovascular health. Keywords: Traffic, Air pollution, Noise, Maternal blood pressure, Hypertension

Research that analyzes the effect of different environmental factors on the impact of COVID-19 focus primarily on meteorological variables such as humidity and temperature or on air pollution variables. However, noise pollution is also a relevant environmental factor that contributes to the worsening of chronic cardiovascular diseases and even diabetes. This study analyzes the role of short-term noise pollution levels on the incidence and severity of cases of COVID-19 in Madrid from February 1 to May 31, 2020. The following variables were used in the study: daily noise levels averaged over 14 days; daily incidence rates, average cumulative incidence over 14 days; hospital admissions, Intensive Care Unit (ICU) admissions and mortality due to COVID-19. We controlled for the effect of the pollutants PM10 and NO2 as well as for variables related to seasonality and autoregressive nature. GLM models with Poisson regressions were carried out using significant variable selection (p, Highlights • Noise levels were related to all COVID-19 ‘s variables considered except mortality. • First association detected was with incidence after with hospital admissions and ICU. • There was no association with deaths due to COVID-19. • Noise is relevant in relation to the incidence and severity of COVID-19.

Background Early life environments may influence children's blood pressure (BP), but evidence on the combined effects of natural and built environment exposures is scarce. The present study investigates the associations of natural and built environment indicators, traffic noise, and air pollution with BP in children living in Alpine valleys. Methods In 2004/2005, 1251 school children (8–12 years old) were sampled for a cross-sectional survey in several Austrian and Italian mountain valleys. Children's mothers completed a questionnaire. The outcomes of interest were systolic and diastolic BP measured with a calibrated oscillometric device. Indicators of land cover assigned to the residential and school coordinates within 100 and 1000 m included normalized difference vegetation index (NDVI), tree canopy cover, and a broader naturalness indicator titled distance to nature (D2N). The presence of a home garden was also measured via self-report. Imperviousness density served as a proxy for the built environment. Residential air pollution (NO2) and noise (Lden) from traffic were calculated using bespoke modeling. NO2, Lden, physical activity, and body mass index (BMI) were treated as mediating pathways. Results Higher NDVI and tree cover levels in residential and school surroundings and home gardens were consistently associated with lower BP. The built environment was associated with higher BP. Counterintuitive inverse associations between NO2 and Lden and BP were also found. Structural equation modeling showed that higher levels of greenspace and presence of a home garden were weakly associated with more outdoor play spaces, and in turn with lower BMI, and ultimately with lower BP. Conclusions Exposure to natural environments may help maintain normal BP in children, while built environment may increase children's BP. Outdoor play and less adiposity in greener areas may mediate some of these associations. Evidence on air pollution and noise remains controversial and difficult to explain.

Noise pollution due to traffic has been recognized as one of the chief sources that negatively affects the quality of life in urban areas across the globe. It is important to monitor and analyze the noise level before purposing remedial measures. So, the main aim of this study is the analysis and evaluation of traffic noise in different zones of Delhi, India. Seven residential, three commercials, four industrial and two silent areas of city Delhi has been selected for this study. The Leq mentoring has been carried out for all selected locations in day and night time and the monitoring results are compared with the prescribed standard of Central Pollution Control Board. Furthermore, the average Leq, Lmin, and Lmax has also been registered for all locations. The variation of noise level clearly indicates that residential area is exposed to the highest noise level i.e. 76.62 dB followed by commercial area (59.36dB), silent area (58.58dB) and Industrial area (44.45dB). This is because of the fact that the residential area is located at the intersection of major roads having high traffic volume most of the time. The Commercial area which has been selected here is the central business district of Delhi and is of historic importance. It’s a famous tourist spot as well as having retail shops, offices and historic structures. All these contribute to high traffic noise. However, the Silent area selected for this study also has similar traffic noise as a commercial area because it has densely populated residential areas nearby. The lowest noise level is observed in the Industrial area because the area has small scale industries that are fully enclosed with high boundary walls which act as a buffer. Also, there is less traffic movement in this area as there is no residential or commercial area nearby and the only traffic is because of the factory workers and loading & unloading.

In this research study an adaptive recurrent artificial nonlinear neural network identification model has been developed and experimentally tested for dynamically predicting the traffic noise level L e q , 1 ′ with a time refinement of 1 minute. The model has been successfully applied in three selected positions, representative of the waterfront in a Mediterranean port city. Several maritime cities are exposed to a wide range of road traffic fluctuations that negatively impact liveability in the area concerned. Large volumes of road traffic periodically access the port, dynamically affecting the acoustic scenario in neighbouring areas, especially in seaside towns during the tourist season. A signalized intersection, a roundabout, and a wide entrance to a vehicular underpass have been analyzed in the course of two characteristic periods, during which traffic ranged widely from normal to peak yearly intensity. Detailed traffic data for 15 road lanes and noise sequence regressors have been considered as input data sources. This exploratory investigation reveals a good predictive performance of the model developed, the prediction error of L e q , 1 ′ falling prevalently within the range ±0.5dB. The experimental profile of L e q , 1 ′ is well reflected by the simulated sequence, and the auto and cross correlation functions confirm how well the identified neural model is able to explain the functional dependence underlying the experimental observations.

The evaluation of the effectiveness of noise barriers have addressed, in some research studies, the intrinsic characteristics of barriers, such as noise absorption or transmission; in other studies, it has been based on the global characteristics of Insertion Loss (IL), which is defined as the difference in the noise level before and after the installation of the barrier. IL is an extrinsic characteristic of noise barriers, depending largely on the site in which the barrier is placed. This research investigated the in situ effectiveness of existing noise barriers by using the indirect IL method established in the international standard ISO 10847:1997. Measurements were performed at thirty sample sites, distributed among the three most frequent types of material found on Spanish roads (earth berms and concrete and metal walls). The results revealed moderate IL values. Results at a distance of 25 m were clearly below the expected effectiveness of a noise barrier. The IL values for the three types of barriers were similar. The best noise reduction effect was in the frequency range of 125–8000 Hz, at which the traffic noise is dominant. In most cases, the dimensions of the barriers did not seem to have been determined taking into account diffraction requirements.

Urban soundscapes are dynamic and complex multivariable environmental systems. Soundscapes can be organized into three main entities containing the multiple variables: Experienced Environment (EE), Acoustic Environment (AE), and Extra-Acoustic Environment (XE). This work applies a multidimensional and synchronic data-collecting methodology at eight urban environments in the city of Cordoba, Argentina. The EE was assessed by means of surveys, the AE by acoustic measurements and audio recordings, and the XE by photos, video, and complementary sources. In total, 39 measurement locations were considered, where data corresponding to 61 AE and 203 EE were collected. Multivariate analysis and GIS techniques were used for data processing. The types of sound sources perceived, and their extents make up part of the collected variables that belong to the EE, i.e. traffic, people, natural sounds, and others. Sources explaining most of the variance were traffic noise and natural sounds. Thus, a Green Soundscape Index (GSI) is defined here as the ratio of the perceived extents of natural sounds to traffic noise. Collected data were divided into three ranges according to GSI value: 1) perceptual predominance of traffic noise, 2) balanced perception, and 3) perceptual predominance of natural sounds. For each group, three additional variables from the EE and three from the AE were applied, which reported significant differences, especially between ranges 1 and 2 with 3. These results confirm the key role of perceiving natural sounds in a town environment and also support the proposal of a GSI as a valuable indicator to classify urban soundscapes. In addition, the collected GSI-related data significantly helps to assess the overall soundscape. It is noted that this proposed simple perceptual index not only allows one to assess and classify urban soundscapes but also contributes greatly toward a technique for separating environmental sound sources.

In Korea, mitigation measures for traffic noise at schools are implemented during urban planning to meet the acceptable level (less than 65 dBA at a building facade) stipulated by the Environmental Impact Assessment (EIA). Meanwhile, traffic noise at schools is managed to satisfy the acceptable level (less than 55 dBA in a classroom with open windows) indicated by the School Health Act (SHA). This variation indicates the possibility to exceed the acceptable SHA level for EIA-approved schools if noise reduction through open windows is less than 10 dBA. Thus, this study carried out onsite measurements for noise reduction through classrooms’ open windows at 19 schools to suggest the appropriate EIA level to meet the acceptable SHA level. The building dispositions were categorized into four types as; (1) Parallel disposition between road and classroom (P type), (2) Perpendicular disposition between road and classroom (V type), (3) Cross-sectional disposition between road and classroom (PV type), and (4) Parallel disposition between road and hallway (H type). The results showed different noise reduction through open windows according to the type of building dispositions in the order of H (16.9 dBA), V (9.2 dBA), PV (8.4 dBA), and P (6.7 dBA) types, attributed to the change in incidence angles between the road and open windows, confirmed by measurements using a speaker. In conclusion, the acceptable noise level on SHA could be exceeded especially for the P, PV, and V types, indicating the need for different noise mitigation measures according to building dispositions.

Background Road-traffic noise can induce stress, which may contribute to mental health disorders. Mental health problems have not received much attention in noise research. People perceive noise differently, which may affect the extent to which noise contributes to poor mental health at the individual level. This paper aims to assess the relationships between outdoor traffic noise and noise annoyance and the use of psychotropic medication. Methods We conducted a survey to assess noise annoyance and psychotropic medication among residents of the Helsinki Capital Region of Finland. We also assessed the associations of annoyance and road-traffic noise with sleep disorders, anxiety and depression. Respondents were randomly sampled from the Finnish Population registry, and data was collected using a self-administered questionnaire. Outdoor traffic noise was modelled using the Nordic prediction model. Associations between annoyance and modelled facade-noise levels with mental health outcome indicators were assessed using a binary logistic regression while controlling for socioeconomic, lifestyle and exposure-related factors. Results A total of 7321 respondents returned completed questionnaires. Among the study respondents, 15%, 7% and 7% used sleep medication, anxiolytic and antidepressant medications, respectively, in the year preceding the study. Noise annoyance was associated with anxiolytic drug use, OR = 1.41 (95% CI: 1.02–1.95), but not with sedative or antidepressant use. There was suggestive association between modelled noise at levels higher than 60 dB and anxiolytic or antidepressant use. In respondents whose bedroom windows faced the street, modelled noise was definitively associated with antidepressant use. Noise sensitivity did not modify the effect of noise but was associated with an increased use of psychotropic medication. Conclusion We observed suggestive associations between high levels of road-traffic noise and psychotropic medication use. Noise sensitivity was associated with psychotropic medication use.

Although traffic noise exposure is a well-known environmental pollutant whose negative health effect has been discussed in different aspects of the human life, only a few animal studies have tackled this issue as a cohort study, which is not feasible to be addressed in human studies. In addition to the deleterious impact of the daytime noise on well-being, chronic nocturnal noise can also disturb sleep and affects physical and mental health, but to date, little research has examined the neurobiological effects of light/dark cycles of traffic noise exposure. We investigated the effects of light/dark cycles and sex on the impact of chronic traffic noise exposure on mouse brain structure-function. The mice were randomly assigned to either one of two stress conditions or a control condition. Animals were exposed to traffic noise on either the light-cycle (LC) or dark-cycle (DC) for 30 days. Traffic noise exposure caused the hypothalamic–pituitary–adrenal (HPA) axis hyperactivity, anxiety-like behavior, impairments in learning and memory, dysfunction in balance and motor coordination, and a reduction in variety of brain measures including a brain volume, medial prefrontal cortex (mPFC) area, cortical thickness, hippocampal volume, amygdala area, and the neural density in mPFC and dentate gyrus. All behavioral and brain measures revealed adverse effects of the chronic noise stress irrespective of the LC/DC exposure or sex. Our findings were a re-emphasis on the significance of noise prevention and mitigation strategies for public health.

BACKGROUND: A growing body of scientific literature indicates that urban green- and bluespace support mental health; however, little research has attempted to address the complexities in likely interrelations among the pathways through which benefits plausibly are realized. OBJECTIVES: The present study examines how different plausible pathways between green/bluespace and mental health can work together. Both objective and perceived measures of green- and bluespace are used in these models. METHODS: We sampled 720 students from the city of Plovdiv, Bulgaria. Residential greenspace was measured in terms of the Normalized Difference Vegetation Index (NDVI), tree cover density, percentage of green areas, and Euclidean distance to the nearest green space. Bluespace was measured in terms of its presence in the neighborhood and the Euclidean distance to the nearest bluespace. Mental health was measured with the 12-item form of the General Health Questionnaire (GHQ-12). The following mediators were considered: perceived neighborhood green/bluespace, restorative quality of the neighborhood, social cohesion, physical activity, noise and air pollution, and environmental annoyance. Structural equation modelling techniques were used to analyze the data. RESULTS: Higher NDVI within a 300 m buffer around the residence was associated with better mental health through higher perceived greenspace; through higher perceived greenspace, leading to increased restorative quality, and subsequently to increased physical activity (i.e., serial mediation); through lower noise exposure, which in turn was associated with lower annoyance; and through higher perceived greenspace, which was associated with lower annoyance. Presence of bluespace within a 300 m buffer did not have a straightforward association with mental health owing to competitive indirect paths: one supporting mental health through higher perceived bluespace, restorative quality, and physical activity; and another engendering mental ill-health through higher noise exposure and annoyance. CONCLUSIONS: We found evidence that having more greenspace near the residence supported mental health through several indirect pathways with serial components. Conversely, bluespace was not clearly associated with mental health.