Traffic-related Noise Research Articles

Health impact assessment of exposure to road traffic noise and air pollution according to pre- and post-densification scenarios in Helsingborg, Sweden

A prevalent solution to accommodate population growth due to urbanization is densification. However, this often pushes new residential housing closer to roads, increasing exposure to both noise and air pollution. The present study’s aim was to estimate the health impacts of road traffic-related noise and air pollution for a low-income area (Drottninghög) in Helsingborg, Sweden, according to pre-densification (2012) and post-densification (2030) scenarios.Road traffic noise was simulated at the façade of residential buildings using the Nordic prediction method, and exposure was assessed using SoundPLAN. Exposure-response functions (ERF) from the WHO were utilized for the following health outcomes associated with noise: annoyance, adverse sleep disturbance, ischemic heart disease (IHD) incidence and IHD mortality. Air pollution (nitrogen dioxide, NO2) was assessed using a Gaussian dispersion model (AERMODE). Health outcomes associated with NO2 included natural cause mortality, pediatric asthma, respiratory hospitalizations and low birth weight (LBW). ERFs were derived from meta-analyses. Health impact assessments were then performed for both scenarios.Densifying Drottninghög according to the municipality’s planned strategy would lead to a 15 % unit increase in the proportion of residents exposed to road traffic noise above the WHO’s health-based guideline value (53 dB(A) Lden). This was estimated to markedly increase the proportion of residents highly annoyed by traffic noise (7.4–13.9 %) as well as those highly sleep disturbed (3.0–4.9 %). IHD incidence and IHD mortality attributed to noise would increase by an estimated 49 % and 44 %, respectively, post-densification. NO2 exposure was estimated to increase slightly (0.7 µg/m3) post-densification, which would contribute to an estimated 4–6 % increase in natural cause mortality, pediatric asthma, respiratory hospitalization and LBW.Urban planning initiatives need to consider these prevalent urban environmental exposures and integrate a public health perspective into densification strategies. Doing so can create synergies in the built environment that promote healthy, sustainable cities.

Comparison of hunting site strategies of the common buzzard Buteo buteo in open landscapes and along expressways.

The expansion of human activities in their many forms increases the frequency, diversity, and scale of human-wildlife interactions. One such negative form is the expansion of road infrastructure, causing road kill and traffic-related noise as well as habitat loss and fragmentation. Even so, habitats around road infrastructure are attractive foraging areas that attract certain bird species. We assessed the impact of road infrastructure on the foraging strategies of the common buzzard Buteo buteo. Birds were observed during two winter seasons in two land-use types, along an expressway and an open agricultural landscape. Individual birds were tracked for a 10-min sequence as a separate sample was analysed. The material, covering 1,220 min along the expressway, and 1,100 min in the agricultural landscape, was collected. Time spent by buzzards on medium-height sites was higher along the expressway than in farmland. Buzzards changed their hunting sites following the mean wind speed. Also, they more often changed their sites along the expressway than in farmland. The land-use types, snow cover, and the mean wind speed mediated the number of attacks on prey. These results illustrate the high plasticity of the buzzards' behaviour, which can adapt their hunting strategies to both foraging locations (expressway and farmland) and weather conditions. Roadsides along expressways are attractive foraging areas for this diurnal raptor, so reducing the risk of vehicle collisions with this and other birds of prey may require targeted planning efforts.

Commuter exposure to ultrafine particles (UFPs), lung deposited surface area (LDSA), and noise in Ho Chi Minh City, Vietnam

IntroductionTransport is a main contributor to air and noise pollution, particularly in urban areas with the high number of motorized vehicles. Promoting active transport (i.e., cycling and walking) and public transport is an instrumental factor in reducing traffic-related air and noise pollution. However, commuters of these transport modes are often exposed to high air and noise pollution than other commuter groups. MethodsThe levels of exposure to UFP, LDSA, and noise during commuting of different transport modes in Ho Chi Minh City (HCMC) were measured and compared. Then, the dose of inhaled pollutants during commuting was calculated for each commuter group by considering the travel time and minute ventilation. ResultsThe level of exposure to air and noise pollution varies across transport modes. Cyclists and motorcyclists were exposed to the highest level of air and noise pollution. Motorcyclists and cyclists were exposed to the highest UFP number concentrations during their trips, 3.6*105 and 3.1*105 particles/cm3, respectively. Car commuters were exposed to the lowest air and noise pollution level, followed by bus commuters. When considering the minute ventilation and travel time, cyclists inhaled significantly higher levels of air pollution than other commuters, followed by pedestrians, motorcyclists, bus commuters, and car users. As a result, the health impacts of exposure to traffic-related air and noise pollution for active commuters could be greater than other commuter groups. ConclusionsPromoting active and public transport is a promising approach to improving air quality and reducing congestion in HCMC. Using these transport modes also has potential positive health effects on commuters through physical activities. However, active commuters are faced with the highest risk of exposure to high air and noise pollution levels. To promote active transport and public transport in HCMC, measures to reduce the level of exposure to air and noise pollution for these commuter groups are needed.

A Comprehensive Evaluation and Mitigation Approaches for Traffic-Related Noise in the Sungai Long Region, Malaysia

A Comprehensive Evaluation and Mitigation Approaches for Traffic-Related Noise in the Sungai Long Region, Malaysia

Transportation Noise Pollution and Cardiovascular Health.

Epidemiological studies have found that transportation noise increases the risk for cardiovascular morbidity and mortality, with solid evidence for ischemic heart disease, heart failure, and stroke. According to the World Health Organization, at least 1.6 million healthy life years are lost annually from traffic-related noise in Western Europe. Traffic noise at night causes fragmentation and shortening of sleep, elevation of stress hormone levels, and increased oxidative stress in the vasculature and the brain. These factors can promote vascular (endothelial) dysfunction, inflammation, and arterial hypertension, thus elevating cardiovascular risk. The present review focusses on the indirect, nonauditory cardiovascular health effects of noise. We provide an updated overview of epidemiological research on the effects of transportation noise on cardiovascular risk factors and disease, and mechanistic insights based on the latest clinical and experimental studies and propose new risk markers to address noise-induced cardiovascular effects in the general population. We will discuss the potential effects of noise on vascular dysfunction, oxidative stress, and inflammation in humans and animals. We will elaborately explain the underlying pathomechanisms by alterations of gene networks, epigenetic pathways, circadian rhythm, signal transduction along the neuronal-cardiovascular axis, and metabolism. We will describe current and future noise mitigation strategies. Finally, we will conduct an overall evaluation of the status of the current evidence of noise as a significant cardiovascular risk factor.

Modeling of Traffic Noise along Urban Arterials in Irbid City of Jordan

Traffic-related noise pollution is a recurring problem in large and medium-sized cities. The objective of this study is to quantify traffic-noise levels along selected urban arterials and model the generated traffic noise based on traffic and pavement characteristics. Urban arterial and collector streets in Irbid city, Jordan, were taken as a case study. The city is considered an example of a medium-sized city. 65 urban arterial and collector sections were selected to achieve the stated objective. For each section, ten noise measurements were taken using a time interval of 2.5 minutes for each observation. The statistical pass-by method was used to measure 650 externalnoise observations. In addition, data on traffic, pavement and section geometric characteristics was obtained through field measurements. The collected traffic characteristics, including traffic flow, percentage of trucks and speed in each direction of travel, were obtained. In addition to the measurement of pavement macrotexture depth, an international roughness index was measured using a smartphone application. Investigation of the collected noise data indicated that urban streets experienced high noise levels, reaching maximum and average values of 82 and 77.2 dB(A), respectively. The results of the analyses showed that an increase in each of the included traffic characteristics resulted in significantly higher noise levels. For example, an increase in speed from 35 to 55 km/h would increase noise by 2.7 dB(A). In addition, the interaction term of roughness index and pavement macrotexture depth was found to increase the generated noise. Finally, the results of the analysis indicated that both multivariate linear -and exponential-regression models are suitable to model the generated traffic noise. Each model explained approximately 54% of the noise variability. Probably, traffic composition and vehicle-power type heterogeneity might reduce the level of explained variability. Keywords: Traffic noise, Urban arterials, Pass-by method, Noise modeling, Jordan.

Impact of landscape attributes on the noise reduction effects of heritage landscapes

Heritage landscapes provide a cost-effective solution for mitigating noise and creating adaptable open spaces in urban ecological construction and planning. In this study, we examined 27 distinct landscapes in a city in northern China to assess their effectiveness in reducing traffic-related noise. The acoustic properties of the landscapes, considering various surfaces, slopes, elevations, structures, and topography, were systematically analysed and compared. The findings indicate that vertically rigid descending landscapes exhibit the highest acoustic performance, followed by vertically flexible dense landscapes without slopes. Additionally, the noise reduction effects of horizontal landscapes with rough rigid surfaces surpass those of landscapes covered by low-growing vegetation and landscapes with sparse high-growing vegetation. The insights derived from this study can enhance our understanding of heritage landscapes, provide valuable information for their protection and micro-updates, and support quantitative research in this field.

Urban vertical air pollution gradient and dynamics investigated with low-cost sensors and large-eddy simulations

A network of five low-cost air pollution sensor (LCS) nodes was deployed vertically on the exterior of the H. C. Ørsted Institute at the University of Copenhagen, Denmark, to investigate the transport of pollution from the road below. All LCS nodes measured PM2.5, NO2, and O3 at 1-min time resolution, and one of them also measured noise. Traffic was monitored with a webcam, where traffic type and levels were derived using a machine-learning algorithm. We investigated how well traffic-related air pollution, noise, and real-time traffic counts serve as proxies for one another. The correlations between NO2, noise, and traffic count exhibited relatively low values when considering all the data. However, these correlations significantly increased under southwesterly wind direction and low wind speed, reaching R2 = 0.40 for NO2 and noise, R2 = 0.51 for NO2 and traffic volume, and R2 = 0.70 for noise and traffic volume. These results indicate a common source, namely traffic, for all three parameters. The five LCS nodes spanning 25 m vertically had extremely low intervariability with minimum R2-values of 0.98 for PM2.5, 0.89 for NO2, and 0.97 for O3. The system could not detect a vertical gradient in pollution levels. Large-eddy simulation model runs using the PALM model system generally supported the lack of gradient observed in measured observations. Under slightly unstable stratification, concentration remained relatively constant with height for southwesterly and southerly winds. Conversely, winds from the north, west, and northwest showed an increase in concentration with height. For other wind directions, the concentration decreased with height by approximately 40 % to 50 %, which is not as strong as for neutral stratification, attributed to enhanced vertical mixing under unstable stratification. Based on the measurements and modeling, we conclude that the vertical concentration profile is very sensitive to stratification, and under these conditions, the concentration outside the window of a fifth-floor office is almost the same as for an office on the ground floor.

Too Loud to Handle? Transportation Noise and Cardiovascular Disease.

The World Health Organization reported that more than 1.6 million healthy life-years are lost yearly from traffic-related noise in western Europe. In addition, the number of studies on health side effects in response to traffic noise is steadily growing, mainly cardiovascular disease, such as acute and chronic ischemic heart disease, heart failure, arrhythmia, and stroke. Pathophysiologically nighttime noise has been shown to cause sleep disturbances, including too short sleep periods and frequent interruption of sleep leading to an increase in the levels of circulating stress hormones and subsequently to a significant increase in the production of reactive oxygen species (oxidative stress) and inflammation in the vasculature and the brain. The consequence is arterial hypertension and vascular (endothelial) dysfunction, which might increase the risk of cardiovascular disease. With the present review, we give an overview of the "so-called" nonauditory cardiovascular health effects of noise, which have been proposed to be responsible for the future development of cardiovascular disease. We present epidemiological evidence but also evidence provided by translational human and experimental noise studies. Finally, we discuss manoeuvres to mitigate noise effectively.

Development of response surface method prediction model for traffic-related roadside noise levels based on traffic characteristics

Recently, several urban areas are trying to mitigate the environmental impacts of traffic, where noise pollution is one of the main consequences. Thus, studying the determinants of traffic-related noise generation and developing a model that predicts the level of noise by controlling the influencing factors are crucial for transportation planning purposes. This research aims at utilizing the response surface method (RSM) to develop a robust statistical prediction model of traffic-related noise levels and optimize different traffic characteristics’ ranges to reduce the expected noise levels. The results indicate that the rate of Leq increase is higher at traffic flow values less than the 1204 veh/h. The interaction effect of flow-speed and flow-heavy vehicle percentage pairs shows that Leq has peak values around 45.8 km/h and 28.71%, respectively, with almost symmetric value distribution about those center points. The main effects study indicates a direct effect of traffic flow, speed, density, and traffic composition on roadside noise levels. The prediction model has good representativeness of observed noise levels by predicted noise levels as the model has a high coefficient of determination (R2 = 95.87% and R2 adj = 92.26%) with a significance level of 0.0036. Then, the research presents a methodology to perform an optimization of the roadside noise level by defining traffic characteristics that can keep the noise level below 65 dB(A) or minimize noise level. Decision-makers could use the proposed method to control the roadside noise level.

Road tunnel noise: monitoring, prediction and evaluation of noise-induced hearing loss.

Incessant increases in vehicles and massive road networks lead to traffic-related problems and noise pollution. Road tunnels are considered a more feasible and effective solution for solving traffic problems. Compared to other traffic noise abatement strategies, road tunnels also offer enormous benefits to urban mass transit systems. However, the road tunnels that are non-complying with the design and safety standards negatively impact commuters' health of being exposed to the high noise level inside the tunnel, particularly for road tunnels above 500 m in length. The study aims to evaluate the applicability of the ASJ RTN-Model 2013 by validating predicted data with the measurement data at the tunnel portal. The study also investigates the acoustic characteristics of noise inside the tunnel by analysing octave frequencies to inspect the correlation of noise spectrum for noise-induced hearing loss (NIHL) and discussed the possible health effect on the pedestrian and vehicle riders passing through the tunnel. The result shows that people are exposed to a high noise level inside the tunnel. The equivalent sound pressure levels at different locations inside the tunnel along the length observed between 78.9 to 86.5 dB(A), which exceeded the CPCB, recommended permissible limits for road traffic noise. The locations L1, L5, L6 and L7 found higher sound pressure levels at 4 kHz and relates to NIHL. The observed average difference between the measurement and predicted LAeq value at the tunnel portal was 2.8 dB(A) which is highly acceptable and confirms the ASJ RTN-2013 prediction model applicability for predicting tunnel portal noise in the Indian road conditions. The study recommends complete restriction of honking inside the tunnel. Considering the commuter's safety perspective, the road tunnels above 500 m must have separate walk sides for pedestrians with a barrier.

Noise pollution and associated health impacts at Ganeshpeth Bus Terminus in Nagpur, India

Abstract Noise pollution, a man-made disaster in the present times, is becoming more severe and pervasive than ever before due to rapid urbanization, affecting quality of life in urban areas in India. Transit areas generate excessive noise which proves disastrous to human health. However, very few studies have mapped noise levels of transit terminals in India. The objectives of this study are (i) assessment of noise levels in Ganeshpeth Bus Terminus, the major interstate bus terminus in Nagpur and generation of noise contour map in ArcGIS and (ii) a qualitative assessment of the impact of traffic-related noise on the health of the people working in the terminus with prolonged exposure to noisy environment, by conducting a health perception survey based on a questionnaire comprising indicators of health parameters. This is a first-of-its-kind study on noise mapping at an interstate bus terminus in India. The results indicate that the noise levels all over the bus terminus site are much higher than the prescribed standards and the source of noise is not only the plying of vehicles but also the misuse of the public address system. Solutions have been suggested to achieve a drastic reduction in noise levels through simple planning-oriented measures.

Social Inequities in Exposure to Traffic-Related Air and Noise Pollution at Public Schools in Texas.

Although children are particularly vulnerable to the adverse impacts of vehicular pollution and spend significant portions of their time at school, previous studies have not examined or compared school-level social inequities in exposure to both traffic-related air and noise pollution in the same study area. We addressed this gap through a case study in Texas-the second-largest US state based on total population and number of children. Vehicular pollution exposure was measured using: (1) outdoor concentrations of nitrogen dioxide (NO2), a widely used proxy for traffic-related air pollution; and (2) road noise estimates from the US Department of Transportation's National Transportation Noise Mapping Tool. These variables were linked to data on locations and sociodemographic characteristics of children enrolled in Texas public schools. We found children attending schools with the highest exposure to both NO2 and road noise (top 25%) were significantly more likely to be Black, Hispanic, and eligible for free/reduced lunches (socioeconomically deprived). Results from multivariable generalized estimating equations that control for spatial clustering and other relevant factors revealed that schools with greater NO2 exposure were significantly more likely to serve racial/ethnic minority and younger students, while schools with greater exposure to road noise were significantly more likely to serve socioeconomically deprived and older students. These findings underscore the urgent need to reduce both air pollution and noise exposure at school locations, especially in schools attended by higher proportions of socially disadvantaged children that are often additionally burdened with other challenges.

Air pollution and traffic noise interact to affect cognitive health in older Mexican Americans

BackgroundBoth air pollution and noise exposures have separately been shown to affect cognitive impairment. Here, we examine how air pollution and noise exposures interact to influence the development of incident dementia or cognitive impairment without dementia (CIND). MethodsWe used 1,612 Mexican American participants from the Sacramento Area Latino Study on Aging conducted from 1998 to 2007. Air pollution (nitrogen dioxides, particulate matter, ozone) and noise exposure levels were modeled with a land-use regression and via the SoundPLAN software package implemented with the Traffic Noise Model applied to the greater Sacramento area, respectively. Using Cox proportional hazard models, we estimated the hazard of incident dementia or CIND from air pollution exposure at the residence up to 5-years prior to diagnosis for the members of each risk set at event time. Further, we investigated whether noise exposure modified the association between air pollution exposure and dementia or CIND. ResultsIn total, 104 incident dementia and 159 incident dementia/CIND cases were identified during the 10 years of follow-up. For each ∼2 µg/m3 increase in time-varying 1- and 5-year average PM2.5 exposure, the hazard of dementia increased 33% (HR = 1.33, 95%CI: 1.00, 1.76). The hazard ratios for NO2-related dementia/CIND and PM2.5-related dementia were stronger in high-noise (≥65 dB) exposed than low-noise (<65 dB) exposed participants. ConclusionOur study indicates that PM2.5 and NO2 air pollution adversely affect cognition in elderly Mexican Americans. Our findings also suggest that air pollutants may interact with traffic-related noise exposure to affect cognitive function in vulnerable populations.

Cross-sectional associations of different types of nature exposure with psychotropic, antihypertensive and asthma medication

BackgroundExposure to natural environments is thought to be beneficial for human health, but the evidence is inconsistent.ObjectiveTo examine whether exposure to green and blue spaces in urban environments is associated...

Mitigation of traffic-related noise – An overview of the focus research area within the BMDV Network of Experts

Increasing traffic flows and a densification of traffic networks lead to an increase in traffic-related noise. The consequences for people exposed to (traffic) noise can be concentration disorders, cardiovascular diseases and various other pathologies. In order to find interdepartmental solutions for problems that affect all modes of transport, the German Federal Ministry for Digital and Transport (BMDV) has set up the BMDV Network of Experts. In the subject area “Possibilities for reducing traffic-related sound emissions and noise”, different authorities have joined their expertise to develop new approaches for the mitigation of traffic-related noise. The present work gives an overview of the activities in this focus area. It summarises the promising results of the first research phase and presents the projects of the current second research phase, which started in 2020.

Selected Indicators of Al-Najaf Road Network: Public Transportation Noise and Pollution

It is urgently necessary to improve the state of transportation and related infrastructure, especially given that the most important indicators of urban development gauge a city's progress. One of the most influential of these indicators is what is known as "smart transport, " which refers to transportation that utilizes modern communication and information technology technologies to address various challenges in various transportation sectors. The holy city of Najaf smart transportation strategy seeks to reduce dangerous levels of traffic-related noise and air pollution while enhancing various aspects of mobility and traffic flow indicators. This study aims to evaluate the performance of the existing traffic network and public transport in Najaf City and its interference with noise and air pollution at selected points for data gathering by using field measurements using cameras, noise meters, and pollution measurement devices. The study states that the public transport sector in Al-Najaf city is significantly poor as private cars are dominant by about 65% of traffic mix with values of pollution and noise above the standards. One of the most effective solutions to traffic problems is the implementation of intelligent transportation systems. Part of these strategies is establishing a tram network and raising road classes’ strategies by proposing some geometric design editing, U-turns reducing, and raised ramps additions.

Co-exposure to urban particulate matter and aircraft noise adversely impacts the cerebro-pulmonary-cardiovascular axis in mice

Worldwide, up to 8.8 million excess deaths/year have been attributed to air pollution, mainly due to the exposure to fine particulate matter (PM). Traffic-related noise is an additional contributor to global mortality and morbidity. Both health risk factors substantially contribute to cardiovascular, metabolic and neuropsychiatric sequelae. Studies on the combined exposure are rare and urgently needed because of frequent co-occurrence of both risk factors in urban and industrial settings. To study the synergistic effects of PM and noise, we used an exposure system equipped with aerosol generator and loud-speakers, where C57BL/6 mice were acutely exposed for 3d to either ambient PM (NIST particles) and/or noise (aircraft landing and take-off events). The combination of both stressors caused endothelial dysfunction, increased blood pressure, oxidative stress and inflammation. An additive impairment of endothelial function was observed in isolated aortic rings and even more pronounced in cerebral and retinal arterioles. The increase in oxidative stress and inflammation markers together with RNA sequencing data indicate that noise particularly affects the brain and PM the lungs. The combination of both stressors has additive adverse effects on the cardiovascular system that are based on PM-induced systemic inflammation and noise-triggered stress hormone signaling. We demonstrate an additive upregulation of ACE-2 in the lung, suggesting that there may be an increased vulnerability to COVID-19 infection. The data warrant further mechanistic studies to characterize the propagation of primary target tissue damage (lung, brain) to remote organs such as aorta and heart by combined noise and PM exposure.

Estimating traffic noise over a large urban area: An evaluation of methods

Unlike air pollution, traffic-related noise remains unregulated and has been under-studied despite evidence of its deleterious health impacts. To characterize population exposure to traffic noise, both acoustic-based numerical models and data-driven statistical approaches can generate estimates over large urban areas. The aim of this work is to formally compare the performances of the most common traffic noise models by evaluating their estimates for different categories of roads and validating them against a unique dataset of measured noise in Long Beach, California. Specifically, a statistical land use regression model, an extreme gradient boosting machine learning model (XGB), and three numerical/acoustic traffic noise models: the US Noise Model (FHWA-TNM2.5), a commercial noise model (CadnaA), and an open-source European model (Harmonoise) were optimized and compared. The results demonstrate that XGB and CadnaA were the most effective models for estimating traffic noise, and they are particularly adept at differentiating noise levels on different categories of road.

Association of residential road proximity with cognitive decline and dementia: The Atherosclerosis Risk in Communities (ARIC) Study

BACKGROUND AND AIM: Increasing evidence links higher air pollution exposures to increased risk of cognitive impairment, and there is growing interest in the role of noise in cognitive aging. Although risk factor associations with incident dementia are often strongest when midlife values of risk factors are considered, few studies have considered associations between midlife exposures to traffic-related air pollution or road noise and late life cognition. Our aim was to determine if midlife residential proximity to major roads, a proxy for traffic-related air pollution exposure and road noise, is associated with increased risk of incident dementia in the Atherosclerosis Risk in Communities (ARIC) study. METHODS: ARIC participants were enrolled from 4 US sites in 1987-1989 at ages 45 to 65. We considered data from 12,135 participants of ARIC Visit 2 (1990-1992, study baseline). We calculated midlife residential Euclidean distance to a major (A1, A2, or A3) road based on geocoded residential addresses at Visit 2. We ascertained dementia status through 2019 via in-person study visits with neurocognitive assessment, telephone cognitive interview, informant interview, and access to hospitalization and death records. We estimated the association between midlife residential road proximity and incident dementia using adjusted Weibull models. RESULTS: At study baseline, the mean age of participants was 57 years, 22% were black, 56% were female. 48% lived within 200m and 36% lived within 200 to 500m of a major road. 20% developed dementia during follow-up. While residing closer to major roads in midlife was associated with increased risk of incident dementia in unadjusted models, this association did not persist in adjusted analyses. CONCLUSIONS: Residence near a major road in midlife, a proxy for higher exposure to traffic-related air pollution and noise, does not appear to increase risk of dementia. KEYWORDS: dementia, air pollution, roadway, roads, particulate matter, cognition, aging, epidemiology