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Curve squeal is a highly disturbing tonal noise produced by railway vehicles on tight curves, primarily attributed to lateral sliding at the wheel–rail interface. An essential step to estimate curve squeal noise levels is to determine the nonlinear self-sustained vibrations, for which time integration is a commonly used method. However, although it is known that the initial conditions affect the solutions obtained with time integration, their impact on the limit cycles is often overlooked. This study investigates this aspect for a curve squeal model based on falling friction and a modal reduction of the wheel and provides some insights on the mode competition phenomena and the nature of the final limit cycles obtained. The paper first details the curve squeal model, stability analysis, as well as the initial condition derivation, and then discusses the time integration and limit cycle results in both time and frequency domains. The results reveal two primary families of limit cycles that can be obtained for both types of initial conditions. The cases where stationary vibrations result in a quasi-periodic regime converge to a unique limit cycle which displays three fundamental frequencies corresponding to specific wheel modes, plus harmonic interactions among them. [ABSTRACT FROM AUTHOR]

Rapid urbanization has led to unplanned settlements near railway lines, exposing residents to continuous noise pollution with potential adverse effects on health. This study focuses on the environmental monitoring and assessment of railway noise pollution in urban areas and its impact on human health and daily activities. Noise levels were quantified across different residential zones using precise sound level meters, and a detailed human perception survey was conducted to assess the relationship between noise exposure, annoyance, and health disturbances. By employing structural equation modelling (SEM), the study integrates environmental monitoring data with epidemiological and health data to assess the risk of noise pollution to individuals residing near railway lines. The results indicate that railway noise frequently exceeds regulatory limits, with passenger trains contributing more significantly to pollution than freight trains. The findings also reveal that noise exposure is a significant predictor of annoyance and health effects, with proximity to the railway line being a critical factor. The study emphasizes the need for improved noise monitoring systems and risk assessment strategies in transportation planning to mitigate health risks. These insights contribute to the development of sustainable noise management practices and the design of more efficient monitoring systems, enhancing the understanding of pollution risks at both individual and population levels. [ABSTRACT FROM AUTHOR]

Abstract This study investigates the impact of the noise radiated from airplanes, urban rail transit, high-speed railways, and urban roads on residents near an airport. The results showed that all respondents near the airport were highly annoyed with airplane noise, and some remain annoyed with the noise from the urban rail transit and high-speed railway connecting to the airport. The most detrimental aspect of transportation noise was sleeping disturbance. Transportation noise from 19:00 to 24:00 primarily caused the annoyance of surrounding residents. Airplane noise is the largest source of sound pollution in residences in the region adjacent to the elevated urban rail transit and airport. The insertion loss of vertical sound barrier with a height of 2.4 m at the points 25 m away from the track centerline is 6.9–8.6 dB, but the sound pressure level below 40 Hz is amplified owing to the structure-borne noise radiating from the barrier itself. The presence of sound barriers can reduce the high annoyance level from 24 to 8.2%.

This study investigates the impact of the noise radiated from airplanes, urban rail transit, high-speed railways, and urban roads on residents near an airport. The results showed that all respondents near the airport were highly annoyed with airplane noise, and some remain annoyed with the noise from the urban rail transit and high-speed railway connecting to the airport. The most detrimental aspect of transportation noise was sleeping disturbance. Transportation noise from 19:00 to 24:00 primarily caused the annoyance of surrounding residents. Airplane noise is the largest source of sound pollution in residences in the region adjacent to the elevated urban rail transit and airport. The insertion loss of vertical sound barrier with a height of 2.4 m at the points 25 m away from the track centerline is 6.9–8.6 dB, but the sound pressure level below 40 Hz is amplified owing to the structure-borne noise radiating from the barrier itself. The presence of sound barriers can reduce the high annoyance level from 24 to 8.2%. [ABSTRACT FROM AUTHOR]

In this article, we consider the numerical prediction of the noise emission from a wheelset in laboratory conditions. We focus on the fluid–structure interaction leading to sound emission in the fluid domain by analyzing three different methods to account for acoustic sources. These are a discretized baffled piston using the discrete calculation method (DCM), a closed cylindrical volume using the boundary element method (BEM) and radiating elastic disks in a cubic enclosure solved with the finite element method (FEM). We provide the validation of the baffled piston and the BEM using measurements of the noise emission of a railway wheel by considering ground reflections in the numerical models. Selected space-resolved waveforms are compared with experimental results as well as with a fluid–structure interaction finite element model. The computational advantage of a discretized disk mounted on a baffle and BEM compared to FEM is highlighted, and the baffled pistons limitations caused by a lack of edge radiation effects are investigated. [ABSTRACT FROM AUTHOR]

Abstract Background Long-term exposure to transportation noise is related to cardio-metabolic diseases, with more recent evidence also showing associations with diabetes mellitus (DM) incidence. This study aimed to evaluate the association between transportation noise and DM mortality within the Swiss National Cohort. Methods During 15 years of follow-up (2001–2015; 4.14 million adults), over 72,000 DM deaths were accrued. Source-specific noise was calculated at residential locations, considering moving history. Multi-exposure, time-varying Cox regression was used to derive hazard ratios (HR, and 95%-confidence intervals). Models included road traffic, railway and aircraft noise, air pollution, and individual and area-level covariates including socio-economic position. Analyses included exposure-response modelling, effect modification, and a subset analysis around airports. The main findings were integrated into meta-analyses with published studies on mortality and incidence (separately and combined). Results HRs were 1.06 (1.05, 1.07), 1.02 (1.01, 1.03) and 1.01 (0.99, 1.02) per 10 dB day evening-night level (Lden) road traffic, railway and aircraft noise, respectively (adjusted model, including NO2). Splines suggested a threshold for road traffic noise (~ 46 dB Lden, well below the 53 dB Lden WHO guideline level), but not railway noise. Substituting for PM2.5, or including deaths with type 1 DM hardly changed the associations. HRs were higher for males compared to females, and in younger compared to older adults. Focusing only on type 1 DM showed an independent association with road traffic noise. Meta-analysis was only possible for road traffic noise in relation to mortality (1.08 [0.99, 1.18] per 10 dB, n = 4), with the point estimate broadly similar to that for incidence (1.07 [1.05, 1.09] per 10 dB, n = 10). Combining incidence and mortality studies indicated positive associations for each source, strongest for road traffic noise (1.07 [1.05, 1.08], 1.02 [1.01, 1.03], and 1.02 [1.00, 1.03] per 10 dB road traffic [n = 14], railway [n = 5] and aircraft noise [n = 5], respectively). Conclusions This study provides new evidence that transportation noise is associated with diabetes mortality. With the growing evidence and large disease burden, DM should be viewed as an important outcome in the noise and health discussion.

Abstract In this article, we consider the numerical prediction of the noise emission from a wheelset in laboratory conditions. We focus on the fluid–structure interaction leading to sound emission in the fluid domain by analyzing three different methods to account for acoustic sources. These are a discretized baffled piston using the discrete calculation method (DCM), a closed cylindrical volume using the boundary element method (BEM) and radiating elastic disks in a cubic enclosure solved with the finite element method (FEM). We provide the validation of the baffled piston and the BEM using measurements of the noise emission of a railway wheel by considering ground reflections in the numerical models. Selected space-resolved waveforms are compared with experimental results as well as with a fluid–structure interaction finite element model. The computational advantage of a discretized disk mounted on a baffle and BEM compared to FEM is highlighted, and the baffled pistons limitations caused by a lack of edge radiation effects are investigated.

Curve squeal is a highly disturbing tonal noise produced by railway vehicles on tight curves, primarily attributed to lateral sliding at the wheel–rail interface. An essential step to estimate curve squeal noise levels is to determine the nonlinear self-sustained vibrations, for which time integration is a commonly used method. However, although it is known that the initial conditions affect the solutions obtained with time integration, their impact on the limit cycles is often overlooked. This study investigates this aspect for a curve squeal model based on falling friction and a modal reduction of the wheel and provides some insights on the mode competition phenomena and the nature of the final limit cycles obtained. The paper first details the curve squeal model, stability analysis, as well as the initial condition derivation, and then discusses the time integration and limit cycle results in both time and frequency domains. The results reveal two primary families of limit cycles that can be obtained for both types of initial conditions. The cases where stationary vibrations result in a quasi-periodic regime converge to a unique limit cycle which displays three fundamental frequencies corresponding to specific wheel modes, plus harmonic interactions among them.

Background: Long-term exposure to transportation noise is related to cardio-metabolic diseases, with more recent evidence also showing associations with diabetes mellitus (DM) incidence. This study aimed to evaluate the association between transportation noise and DM mortality within the Swiss National Cohort. Methods: During 15 years of follow-up (2001–2015; 4.14 million adults), over 72,000 DM deaths were accrued. Source-specific noise was calculated at residential locations, considering moving history. Multi-exposure, time-varying Cox regression was used to derive hazard ratios (HR, and 95%-confidence intervals). Models included road traffic, railway and aircraft noise, air pollution, and individual and area-level covariates including socio-economic position. Analyses included exposure-response modelling, effect modification, and a subset analysis around airports. The main findings were integrated into meta-analyses with published studies on mortality and incidence (separately and combined). Results: HRs were 1.06 (1.05, 1.07), 1.02 (1.01, 1.03) and 1.01 (0.99, 1.02) per 10 dB day evening-night level (Lden) road traffic, railway and aircraft noise, respectively (adjusted model, including NO2). Splines suggested a threshold for road traffic noise (~ 46 dB Lden, well below the 53 dB Lden WHO guideline level), but not railway noise. Substituting for PM2.5, or including deaths with type 1 DM hardly changed the associations. HRs were higher for males compared to females, and in younger compared to older adults. Focusing only on type 1 DM showed an independent association with road traffic noise. Meta-analysis was only possible for road traffic noise in relation to mortality (1.08 [0.99, 1.18] per 10 dB, n = 4), with the point estimate broadly similar to that for incidence (1.07 [1.05, 1.09] per 10 dB, n = 10). Combining incidence and mortality studies indicated positive associations for each source, strongest for road traffic noise (1.07 [1.05, 1.08], 1.02 [1.01, 1.03], and 1.02 [1.00, 1.03] per 10 dB road traffic [n = 14], railway [n = 5] and aircraft noise [n = 5], respectively). Conclusions: This study provides new evidence that transportation noise is associated with diabetes mortality. With the growing evidence and large disease burden, DM should be viewed as an important outcome in the noise and health discussion. [ABSTRACT FROM AUTHOR]

Railway noise, stemming from various sources such as wheel/rail interactions, locomotives, and track machinery, affects both human health and the environment. This study explores the application of machine learning (ML) models to quantify tram noise at sharp curves, considering variables such as weather conditions, train speed, crowd levels, and running directions. Data collection is carried out on a tram line in Birmingham, using an iPhone 11 to record acoustic data at a sample rate of 48 kHz. The noise is categorized into impact noise, rolling noise, flanging noise, and squeal noise based on frequency and power spectrum characteristics. Random Forests (RF) and Extreme Gradient Boosting (XGBoost) are employed to predict the root mean square (R.M.S) values of each type of noise. Results indicate that XGBoost outperformed RF with an R2 up to 0.96 during k-fold cross-validation. This model provides a robust tool for railway operators to optimize noise control measures and contributes to improved compliance with environmental regulations and a better quality of life for communities near rail tracks.

The growth in the utilization and development of rail transport within urban networks is crucial for transitioning towards a more sustainable form of mobility. However, challenges related to discomfort and noise pollution arising from rail traffic must be addressed and mitigated to foster a harmonious coexistence between residents and trains. This study focuses on analyzing an experimental campaign conducted on the surface metropolitan network of Porto to study and identify the frequency content and pressure levels associated with light rail traffic. The presented experimental campaign holds significant relevance as it comprises various and distinct circulation conditions within the railway network, enabling a comprehensive characterization of railway noise. The collected data indicates a noticeable increase in sound pressure levels as the speed of circulation rises, particularly emphasizing the 1/3 octave band centered around 1000 Hz. The choice of tracks with components having a limited capacity for absorbing acoustic energy leads to a significant rise in noise levels compared to track solutions with elements exhibiting excellent acoustic energy absorption. Furthermore, the study highlights a substantial increase in noise levels (10 dBA) associated with small radius curves, even at low speeds. These findings underscore the importance of considering the track characteristics and geometric features in noise assessment within rail networks. Therefore, the insights gained from this experimental campaign contribute significantly to the understanding and comprehensive characterization of railway noise under diverse circulation conditions within the railway network. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Engineering & Management Sciences (2498-700X) / Műszaki és Menedzsment Tudományi Közlemények is the property of University of Debrecen and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The proportion of high speed railway vehicles in the rolling stock of national carriers providing public transport services is constantly increasing. Currently, Alstom vehicles run at the highest speed on railway lines in Poland. The paper attempts to identify the acoustic signature of high speed railway vehicles. There are many works and studies aimed at identifying or defining the acoustic signature of high speed railway vehicles. However, the authors of these works carried out their research in a rather narrow scope, i.e. the measurement cross-section had only 1 or 2 measure-ment points with one microphone at each point. As part of the conducted experimental research, the location of testing grounds was determined, the measurement apparatus was selected and the methodology for carrying out measurements including the assessment of noise emission on curve and straight line were specified for electric multiple units. The object of the tests were railway vehicles of Alstom company, type ETR610, series ED250, the so-called Pendolino, moving on a selected measuring route without stops at a speed of 200 km/h. Measurements were carried out on the railway line no. 4 Grodzisk Mazowiecki – Zawiercie, section Grodzisk Mazowiecki - Idzikowice at kilometre 18+600 (curve) and 21+300 (straight section). When measuring the acoustic signals with a microphone array (4x2), 8 meas-urement microphones operating in the audible range were used. The microphones were placed at a distance of 5 m, 10 m, 20 m and 40 m from the track centre, at a height of 4 m (from the rail head) and at the rail head (approx. 0.8 m from the ground surface). In addition, an acoustic camera with 112 directional microphones was used to locate the main noise sources, which was located at a distance of approximately 20 m from the track centreline. The identification of the main noise sources for high speed railway vehicles, basig on actual acoustic measurements, made it possible to isolate the dominant noise sources, as well as to find out the amplitude-frequency characteristics in the range from 20 Hz to 20 kHz, divided into one third octave bands.

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Background: Noise pollution from transportation is one of the leading contributors to the environmental disease burden in Europe. We provide a novel assessment of spatial variations of these health impacts within a country, using England as an example. Methods: We estimated the burden of annoyance (highly annoyed), sleep disturbance (highly sleep disturbed), ischemic heart disease (IHD), stroke, and diabetes attributable to long-term transportation noise exposures in England for the adult population in 2018 down to local authority level (average adult population: 136,000). To derive estimates, we combined literature-informed exposure-response relationships, with population data on noise exposures, disease, and mortalities. Long-term average noise exposures from road, rail and aircraft were sourced from strategic noise mapping, with a lower exposure threshold of 50 dB (decibels) Lden and Lnight. Results: 40 %, 4.5 % and 4.8 % of adults in England were exposed to road, rail, and aircraft noise exceeding 50 dB Lden. We estimated close to a hundred thousand (∼97,000) disability adjusted life years (DALY) lost due to road-traffic, ∼13,000 from railway, and ∼ 17,000 from aircraft noise. This excludes some noise-outcome pairs as there were too few studies available to provide robust exposure–response estimates. Annoyance and sleep disturbance accounted for the majority of the DALYs, followed by strokes, IHD, and diabetes. London, the South East, and North West regions had the greatest number of road-traffic DALYs lost, while 63 % of all aircraft noise DALYs were found in London. The strategic noise mapping did not include all roads, which may still have significant traffic flows. In sensitivity analyses using modelled noise from all roads in London, the DALYs were 1.1x to 2.2x higher. Conclusion: Transportation noise exposures contribute to a significant and unequal environmental disease burden in England. Omitting minor roads from the noise exposure modelling leads to underestimation of the disease burden.

Background: Environmental noise is an important environmental exposure that can affect health. An association between transportation noise and breast cancer incidence has been suggested, although current evidence is limited. We investigated the pooled association between long-term exposure to transportation noise and breast cancer incidence. Methods: Pooled data from eight Nordic cohorts provided a study population of 111,492 women. Road, railway, and aircraft noise were modelled at residential addresses. Breast cancer incidence (all, estrogen receptor (ER) positive, and ER negative) was derived from cancer registries. Hazard ratios (HR) were estimated using Cox Proportional Hazards Models, adjusting main models for sociodemographic and lifestyle variables together with long-term exposure to air pollution. Results: A total of 93,859 women were included in the analyses, of whom 5,875 developed breast cancer. The median (5th–95th percentile) 5-year residential road traffic noise was 54.8 (40.0–67.8) dB Lden, and among those exposed, the median railway noise was 51.0 (41.2–65.8) dB Lden. We observed a pooled HR for breast cancer (95 % confidence interval (CI)) of 1.03 (0.99–1.06) per 10 dB increase in 5-year mean exposure to road traffic noise, and 1.03 (95 % CI: 0.96–1.11) for railway noise, after adjustment for lifestyle and sociodemographic covariates. HRs remained unchanged in analyses with further adjustment for PM2.5 and attenuated when adjusted for NO2 (HRs from 1.02 to 1.01), in analyses using the same sample. For aircraft noise, no association was observed. The associations did not vary by ER status for any noise source. In analyses using

Urban environment noise is a complex mixture of transportation, industrial, household, and recreational noise, which is identified as an emerging environmental threat. Present study monitors and evaluates a noise pollution hotspot: a railway level crossing, where several activities related to transportation noise were involved. Train honking, train movement, road vehicles, and pedestrians contribute to the noise level at a railway level crossing. Train horns are generally performed as train approach railway level crossings and they are mandatorily used to alert road users. However, the train horns are regarded as nuisance to the nearby residents. A detailed evaluation of train horn effectiveness is very much essential in the current contemporary environment. Thus, the main objective of this study is to measure noise levels emanating from train horns at a level crossing with due consideration to train types and climatic conditions. A comprehensive noise monitoring survey was conducted at an access-controlled level crossing. Furthermore, an artificial neural network (ANN)-based railway noise prediction model was developed to forecast maximum ( L max ) and equivalent (Leq) noise levels. Results revealed that train horn produced impulsive sound signals which fall under high frequency one-third octave bands causing severe irritation to trackside inhabitants. The proposed ANN models produced accurate results for L max and Leq noise levels and this model is identified as a vital tool for railway noise abatement. The results from this study are helpful to the urban planning and development authorities to implement strategic laws and policies to eradicate the urban environment noise. [ABSTRACT FROM AUTHOR]

[Display omitted] • Effects of railway noises on sleep indicators and mental health were investigated. • Field study data was used to construct a health risk prediction model. • Railway noise reduced the sleep quality of nearby residents. • A Cox risk prediction model was developed to help managers and residents improve mental health. Noise is an important environmental risk factor for physical and mental health. Furthermore, long-term noise exposure is burdensome for the mind and body and has become a serious problem. Rail transportation is one of the main methods used to transport goods in China; however, the noise and vibrations generated by freight trains have serious impacts on residents in nearby regions. To further investigate the relationship between railway noise and road noise exposure and changes in sleep duration and mental health scores, a field study in Harbin, China, was conducted and a health risk prediction model was constructed. The results showed that for every 1 dB increase in the Equivalent continuous A-weighted sound pressure level (LAeq), the percentage of deep sleep among residents living near the railway decreased by 0.2 %. Although residents near the railway reported similar sleep evaluations compared to those living farther away, they exhibited poorer mental health. Cox risk modeling indicates that the risk of mental health problems is approximately three times higher for those living near the railway. These findings potentially provide benefits in developing strategies to reduce the risk of mental illness for people residing near railways. [ABSTRACT FROM AUTHOR]

The growth in the utilization and development of rail transport within urban networks is crucial for transitioning towards a more sustainable form of mobility. However, challenges related to discomfort and noise pollution arising from rail traffic must be addressed and mitigated to foster a harmonious coexistence between residents and trains. This study focuses on analyzing an experimental campaign conducted on the surface metropolitan network of Porto to study and identify the frequency content and pressure levels associated with light rail traffic. The presented experimental campaign holds significant relevance as it comprises various and distinct circulation conditions within the railway network, enabling a comprehensive characterization of railway noise. The collected data indicates a noticeable increase in sound pressure levels as the speed of circulation rises, particularly emphasizing the 1/3 octave band centered around 1000 Hz. The choice of tracks with components having a limited capacity for absorbing acoustic energy leads to a significant rise in noise levels compared to track solutions with elements exhibiting excellent acoustic energy absorption. Furthermore, the study highlights a substantial increase in noise levels (10 dBA) associated with small radius curves, even at low speeds. These findings underscore the importance of considering the track characteristics and geometric features in noise assessment within rail networks. Therefore, the insights gained from this experimental campaign contribute significantly to the understanding and comprehensive characterization of railway noise under diverse circulation conditions within the railway network.

Aims: To examine the longitudinal association between transportation noise exposure (road traffic, aircraft, and railway noise) and T2D in a meta‐analysis. Materials and Methods: We systematically searched PubMed, Embase, Scopus, Cochrane, and Web of Science published up to February 2022. The GRADE approach was used to evaluate the study quality, and the pooled effect estimate was calculated by the fixed‐effects model or the random‐effects model. Results: We included 10 prospective studies with a total of 4,994,171 participants and 417,332 T2D cases in the meta‐analysis. According to the Navigation guide, 8 studies out of 10 were rated as having a probably high or high risk of bias. For road noise, the pooled relative risk (RR) per 10 dB higher Lden for developing T2D was 1.06 (95% CI:1.03, 1.09) with high heterogeneity (I2 = 90.1%, p < 0.001). Similar associations were also observed in aircraft and railway noise: the pooled RR were separately were: 1.01 (1.00, 1.01) and 1.02 (1.01, 1.03) separately. A 'dose‐response' analysis found a similar linear association between road noise exposure and the risk of T2D. Conclusions: An overall 6% increase in the risk of T2D per 10 dB increase in road exposure was observed. Further studies are needed to confirm our findings, especially for aircraft and railway noise, and to identify the mechanisms involved. [ABSTRACT FROM AUTHOR]

We analyze the impact of sound barriers on residential satisfaction and well-being manifested in housing prices in Singapore. Using the difference-in-difference approach, we demonstrate a significant price effect of sound barriers in high-rise residential environments. There was a 0.6% price increase for public housing units located within 300 m from a railway track after public announcement of sound barriers and a 1.2% further increase after barrier installation. Price effects of sound barriers are heterogeneous by the noise level prior to installation as well as the degree of noise mitigation by barriers. In contrast to the result for public housing, no significant price change was observed for private housing units that have better building design to be shielded from noise even before sound barrier installation. Among public housing, higher-floor units experienced more substantial price increases compared with lower-floor units exposed to less noise prior to barrier installation. Finally, the units that are very close to the railway did not enjoy price premiums brought by sound barriers potentially because noise did not fall below the threshold level of annoyance even after barrier installation. [ABSTRACT FROM AUTHOR]

• Rail traffic is increasing following policy recommendations for sustainability. • People living close to rail tracks are exposed to both vibration and noise. • We show strong dose–response relationships for modelled vibration and annoyance. • The associations are strongest for freight trains. • Important to consider railway noise in the investigation of vibration annoyance. Rail traffic is increasing following policy recommendations for a sustainable transportation model. However, the health effects of rail traffic vibration on residents living close to railways remain underexplored. We aimed to investigate the relationships between rail traffic vibration and vibration annoyance from different types of trains and to explore the influence of railway noise on these relationships. The study population (N = 7280) was randomly selected from adults living within 1 km of a trafficked railway in Sweden. Survey data were combined with modelled rail traffic vibration and noise. A cross-sectional design and logistic regression analysis were used. Results support a dose–response relationship between vibration and annoyance (stronger for freight trains and weaker for passenger trains). In the adjusted analysis, we observe a robust association between vibration and annoyance from all types of trains, accounting for socioeconomic factors. Furthermore, railway noise appears to modulate the vibration annoyance response. [ABSTRACT FROM AUTHOR]

In 2018, the World Health Organization (WHO) stated that transport noise is the second biggest environmental problem affecting people's health, after air pollution. The Australian Environmental Health Standing Committee (enHealth) also provides suggested health-based limits for transport noise exposure. To better understand the impact of transport noise in Australia, a strategic national transport noise model was developed, representative of the year 2018. The transport noise model presented included parameters for terrain, buildings, and noise barriers, with results verified against measured data. The model calculated the road, rail, and aircraft noise levels for the day, evening, and night-time periods, across all façades of all storeys for over 15 million buildings across Australia. The State of Victoria was chosen as a case study to document noise exposure levels to the community. Australian Census of Population and Housing data and planning zones allowed a population within each dwelling to be calculated and paired to the modelled noise levels. Based on noise levels at the most exposed façade, it is estimated that 48% of the Victorian population are exposed to road traffic noise levels that exceed the 2018 WHO recommendations. Additionally, 10% are estimated to be exposed to aircraft noise levels, and 11% are estimated to be exposed to rail noise levels, that exceed the 2018 WHO recommendations. These percentages are commensurate with higher affected European Member states based on 2017 noise mapping completed as part of the European Noise Directive. When compared against environmental noise exposure recommendations from enHealth (2018), it is estimated that 11% of the Victorian population are exposed to combined road, rail, and aircraft noise levels above the recommended day/evening 60 dB LAeq 16 h health-based limit, and 10% above the health-based night-time limit of 55 dB LAeq 8 h. This national transport noise model provides a base for further research into the impacts of transport noise on the community, particularly regarding health and property values. The model can also support government planning, complaints handling, and asset management in the planning of future noise abatement in Australia. [ABSTRACT FROM AUTHOR]

The goal of this study is to investigate the psychophysiological effects of traffic sounds in urban green spaces. In a laboratory experiment, psychological and physiological responses to four traffic sounds were measured, including road, conventional train, high-speed train, and tram. The findings demonstrated that traffic sounds had significant detrimental psychological and physiological effects. In terms of psychological responses, the peak sound level outperformed the equivalent sound level in determining the psychological impact of traffic sounds. The physiological effects of traffic sounds were shown to be significantly influenced by sound type and sound level. The physiological response to the high-speed train sound differed significantly from the other three traffic sounds. The physiological effects of road traffic sounds were found to be unrelated to the sound level. On the contrary, as for the railway sounds, the change in sound level was observed to have a significant impact on the participants' physiological indicators. [ABSTRACT FROM AUTHOR]

Bridge noise may increase when a train with local wears on wheel treads runs at higher speed. In this study we developed the estimation method for bridge noise at a high-speed section based on permanent accelerometers at a low-speed section. We proposed combining outputs of three accelerometers to measure precisely the influence of the wear of each wheel on rail vibration at the low-speed section, since the influence of the wear is attenuated depending on distance between a position of an accelerometer and that of where the local wear contacts rail. Composite measured data at the low-speed section showed that rail vibration affected by the local wear can be measured independent of distance between them. We also proposed an estimation method that converts the rail vibration at the low-speed section into that at the high-speed section to predict the bridge noises during train running at the high-speed section. In the estimation, the vibration properties of a wheel, a track and a contact spring at each section are used, and it is assumed that a wheel roughness is greater than a rail roughness at the spatial frequencies where the effect due to the local wear appears. The impulse excitation tests were carried out to obtain these vibration properties and transfer functions in vibration from the rail to the bridge at the high-speed section. The transfer functions are used to estimate bridge vibration using the rail vibration induced by one wheel. The bridge noise generated by one wheel is also estimated from the bridge vibration by taking account of the radiation area of the viaduct. Summing the vibrations and noise generated by all wheels in one train results in the overall bridge vibration and noise. The estimated results at the high-speed section show a good agreement with the measured one at the frequencies where the local wear has a stronger effect.

In this paper, an attempt is undertaken to identify the acoustic signature of railway vehicles travelling at 200 km/h. In the framework of conducted experimental research, test fields were determined, measurement apparatus was selected and a methodology for making measurements was specified, including the assessment of noise emission on curved and straight track for electric multiple units of Alstom type ETR610-series ED250, the so-called Pendolino. The measurements were made with the use of an acoustic camera and a 4 × 2 microphone array, including four equipped measurement points and two microphones located at the level of the head of the rail and at a height of 4 m above this level. As a result of the conducted experimental research, the dominant noise sources were identified and amplitude–frequency characteristics for these sources were determined by dividing the spectrum into one-third octave bands in the range from 20 Hz to 20 kHz. The paper also considers issues related to the verification of selected models of noise assessment in terms of their most accurate reflection of the phenomenon of propagation in close surroundings. On the basis of conducted experimental studies, the behaviour of selected models describing the change of sound level with frequency division into one-third octave bands as a function of variable distance of observer from the railway line on which high-speed railway vehicles are operated was verified. In addition, the author's propagation model is presented together with a database built within the scope of the study, containing the actual waveforms in the time and frequency domain. [ABSTRACT FROM AUTHOR]

Rail transport is the most sustainable transportation mode, with the lowest energy consumption and carbon footprint. However, the noise induced by railway traffic in urban regions is a significant drawback and several reports point out the risks and the amount of people suffering from direct exposure to railway noise. One of the most used mitigation measures for railway noise is the implementation of noise barriers. Although they offer a significant reduction in noise levels, their height makes people feel enclosed. Therefore, in the case of railway infrastructure, the solution to the problem may lie in the use of barriers with a lower height placed close to the railway track. As the noise-forming mechanisms are mainly located at the track level, placing the barrier in a position close to the track allows mitigating rail noise without causing the problems identified above for the population in the vicinity. The purpose of this paper is to illustrate the development of a barrier solution to be used in a railway context through numerical modelling with the Boundary Element Method (BEM). The solutions developed were placed close to the track and have a low height. The geometry was defined so as to direct the energy back to the track to take advantage of the acoustic properties of the ballast. The addition of a porous granular material on the inner face of the barrier allows the control of reflections between the vehicle body and the barrier, increasing its acoustic efficiency. Finally, considering the most efficient solution, the insertion loss in a network of receivers located 10 m away from the track is analysed in order to study the noise reduction levels in a place where human receivers are usually located. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to clarify the damping mechanism of the wheel that we have developed. In high-speed railway vehicles, noise associated with speed increase is a problem. We have developed a new wheel that can damp the rolling noise radiated from the wheel. This noise damped wheel has a special device attached to the inner circumference of the rim, which consists of steel sandwiched with vibration absorbing rubber. The noise damping effect was confirmed by the wheel rolling test, but the mechanism was unclear. Therefore, we elucidated the vibration damping mechanism using FEM. Using frequency response analysis, the equivalent radiated power (ERP) was calculated based on the response speed and element area when a load was repeatedly applied at a specified frequency. By calculating the modal ERP for a specific frequency, the natural vibration of the wheel, which contributes significantly to that frequency, was clarified. From this result, it became clear that the developed wheel disperses the natural vibration modes. It was also found that the vibration is reduced by damping of the rubber that acts on the dispersed natural vibration. Based on these findings, we concluded that increasing the Young's modulus of the rubber would improve the damping performance.

Background: Transportation noise has been linked with cardiometabolic outcomes, yet whether it is a risk factor for atrial fibrillation (AF) remains inconclusive. We aimed to assess whether transportation noise was associated with AF in a large, pooled Nordic cohort., Methods: We pooled data from 11 Nordic cohorts, totaling 161,115 participants. Based on address history from five years before baseline until end of follow-up, road, railway, and aircraft noise was estimated at a residential level. Incident AF was ascertained via linkage to nationwide patient registries. Cox proportional hazards models were utilized to estimate associations between running 5-year time-weighted mean transportation noise (L den ) and AF after adjusting for sociodemographics, lifestyle, and air pollution., Findings: We identified 18,939 incident AF cases over a median follow-up of 19.6 years. Road traffic noise was associated with AF, with a hazard ratio (HR) and 95% confidence interval (CI) of 1.02 (1.00-1.04) per 10-dB of 5-year mean time-weighted exposure, which changed to 1.03 (1.01-1.06) when implementing a 53-dB cut-off. In effect modification analyses, the association for road traffic noise and AF appeared strongest in women and overweight and obese participants. Compared to exposures ≤40 dB, aircraft noise of 40.1-50 and > 50 dB were associated with HRs of 1.04 (0.93-1.16) and 1.12 (0.98-1.27), respectively. Railway noise was not associated with AF. We found a HR of 1.19 (1.02-1.40) among people exposed to noise from road (≥45 dB), railway (>40 dB), and aircraft (>40 dB) combined., Interpretation: Road traffic noise, and possibly aircraft noise, may be associated with elevated risk of AF., Funding: NordForsk., Competing Interests: All other authors declare no competing interests., (© 2024 The Author(s).)

Rail transport is the most sustainable transportation mode, with the lowest energy consumption and carbon footprint. However, the noise induced by railway traffic in urban regions is a significant drawback and several reports point out the risks and the amount of people suffering from direct exposure to railway noise. One of the most used mitigation measures for railway noise is the implementation of noise barriers. Although they offer a significant reduction in noise levels, their height makes people feel enclosed. Therefore, in the case of railway infrastructure, the solution to the problem may lie in the use of barriers with a lower height placed close to the railway track. As the noise-forming mechanisms are mainly located at the track level, placing the barrier in a position close to the track allows mitigating rail noise without causing the problems identified above for the population in the vicinity. The purpose of this paper is to illustrate the development of a barrier solution to be used in a railway context through numerical modelling with the Boundary Element Method (BEM). The solutions developed were placed close to the track and have a low height. The geometry was defined so as to direct the energy back to the track to take advantage of the acoustic properties of the ballast. The addition of a porous granular material on the inner face of the barrier allows the control of reflections between the vehicle body and the barrier, increasing its acoustic efficiency. Finally, considering the most efficient solution, the insertion loss in a network of receivers located 10 m away from the track is analysed in order to study the noise reduction levels in a place where human receivers are usually located.

Wheel squeal noise is a common problem that occurs in railway systems especially on curved tracks. These tonal noises are usually found at high frequency, typically over 1 kHz. The cause of the squeal noise remains unclear and could be different under varied conditions. Several mechanisms that could cause wheel squeal, including falling friction and mode coupling, have been proposed in literature. Most existing lab experimental investigations were focused on the squeal noise caused by falling friction with vertical contacts. As a result, the squeal noise generated by mode coupling could be missed due to the absence of a non-vertical contact angle. In this work, a two-wheel test rig has been designed with curved wheel profiles to achieve adjustable contact angles with lateral components. Experimental and numerical modal analysis of the two-disk system was conducted to determine the dynamic characteristics for exploration of mode coupling effects. Using a set of benchmark parameters predicted to be the cause of significant mode-coupled instability, squeal noise was found at frequencies higher than the existing falling friction experimental tests as reported in the literature. The frequency and amplitude measured in the experiments agreed with the predictions of the analytical mode coupling model. Further experiments varying control parameters, contact angle, angle of attack and direction of rotation were performed, confirming that the new squeal noise was caused by mode coupling. • The first experimental verification of mode coupling wheel squeal mechanism using two-disk testrig. • Experimental generated squeal noise level and frequency agreed well with the analytical model prediction. • Additional experiment with reversed rotation confirmed the identified squeal noise was caused by mode coupling. • Further parametric experiments varying contact angle and angle of attack were conducted, and the results were compared with the analytical model prediction and literature. [ABSTRACT FROM AUTHOR]

The combined health impact of concurrent railway noise and railway vibration exposure is not yet well understood. This systematic review gives an overview of epidemiological studies on health effects from railway vibration, aiming to quantify this association with exposure-effect curves. Moreover, the combined health effects of vibration and concurrent noise were investigated. We converted the vibration metric to an equivalent noise level and calculated an overall noise level by energetically summing the equivalent and railway noise level. The combined health effect was determined by using published evidence-based exposure-effect formulas. Studies included in this systematic review predominately investigated annoyance and self-reported sleep disturbances; no studies on manifest diseases were identified. For the combined effects of vibration and noise on "total" annoyance, the results based on the pooled analysis of CargoVibes project are recommended as conservative approach. Converting railway vibration into equivalent noise levels in dB may offer a pragmatic approach to assess the combined health effects of railway noise and railway vibration exposure. Future studies should include cardiovascular and mental diseases in addition to vibration-induced annoyance and sleep disturbances. Furthermore, future studies should include in-depth investigations of the interaction between railway noise and railway vibration to allow for a more accurate assessment of the railway-induced burden of disease. [ABSTRACT FROM AUTHOR]

Environmental noise is of increasing concern for public health. Quantification of associated health impacts is important for regulation and preventive strategies. To estimate the burden of disease (BoD) due to road traffic and railway noise in four Nordic countries and their capitals, in terms of DALYs (Disability-Adjusted Life Years), using comparable input data across countries. Road traffic and railway noise exposure was obtained from the noise mapping conducted according to the Environmental Noise Directive (END) as well as nationwide noise exposure assessments for Denmark and Norway. Noise annoyance, sleep disturbance and ischaemic heart disease were included as the main health outcomes, using exposure-response functions from the WHO, 2018 systematic reviews. Additional analyses included stroke and type 2 diabetes. Country-specific DALY rates from the Global Burden of Disease (GBD) study were used as health input data. Comparable exposure data were not available on a national level for the Nordic countries, only for capital cities. The DALY rates for the capitals ranged from 329 to 485 DALYs/100,000 for road traffic noise and 44 to 146 DALY/100,000 for railway noise. Moreover, the DALY estimates for road traffic noise increased with up to 17% upon inclusion of stroke and diabetes. DALY estimates based on nationwide noise data were 51 and 133% higher than the END-based estimates, for Norway and Denmark, respectively. Further harmonization of noise exposure data is required for between-country comparisons. Moreover, nationwide noise models indicate that DALY estimates based on END considerably underestimate national BoD due to transportation noise. The health-related burden of traffic noise was comparable to that of air pollution, an established risk factor for disease in the GBD framework. Inclusion of environmental noise as a risk factor in the GBD is strongly encouraged. • Transportation noise contributes with a considerable burden in the Nordic capitals. • END based BoD assessment underestimate the disease burden at the country level. • BoD due to traffic noise was of similar size as reported for PM 2.5 air pollution. • Fair comparison of BoD across countries requires further noise data harmonization. [ABSTRACT FROM AUTHOR]

• Estimation of psychoacoustic and noise indices from L Aeq of transportation noise. • Cross-validation of these psychoacoustic and noise index relationships proposed. • This enables psychoacoustic and noise indices to be estimated from noise map L den. • Use of these index relationships appears to be beneficial for annoyance prediction. • Relevance of various indices can therefore be investigated in field studies. Few research works tackled the testing of noise annoyance models proposed in the literature by considering a new set of survey data. This lack contributes to limit the effect of endeavors in noise annoyance prediction. This lack is observed for both annoyance models built from field data and laboratory data. Different reasons might explain this. In the case of annoyance models based on psychoacoustic indices accounting for annoying auditory sensations, their relevance was highlighted in laboratory conditions as they might increase the part of explained variance of annoyance. But the use of these indices in field studies leads to issues. Actually, audio recordings are needed for their calculation, making too tedious their use in large-scale studies. This work proposed a methodology, and its testing, to estimate various psychoacoustic and noise indices from the A-weighted equivalent sound pressure level, L Aeq , of different transportation noise sources. The transportation noise sources were urban and suburban road traffic noise, urban railway noise, and aircraft noise in cities close to French international airports. A database of index values has been built from various recordings of these transportation noise sources. From the database, relationships between the various indices and L Aeq of the transportation noise sources were built, and satisfactorily tested by cross-validation. These relationships might be of interest for field studies dealing with transportation noise assessment. In the current study, the relationships were used to estimate variables of noise annoyance models based on different psychoacoustic and noise indices. The proposed relationships enabled the assessment of the prediction quality of these models also based on individual noise sensitivity. The comparison of their prediction quality with the one of noise annoyance models solely based on the day-evening-night level, L den , and of a model based on both noise sensitivity and the day-night level, L dn , highlighted an improvement of the correlation coefficients between the predicted and the field measured annoyance ratings with a ratio of 2 for the best enhancement. Such a ratio was observed as the correlation coefficient obtained for models solely based on L den were weak. The results stated the interest of the proposed index relationships to be used in the investigation of improving noise annoyance models in future annoyance field studies. [ABSTRACT FROM AUTHOR]

Studies have indicated that transportation noise is associated with higher cardiovascular mortality, whereas evidence of noise as a risk factor for respiratory and cancer mortality is scarce and inconclusive. Also, knowledge on effects of low-level noise on mortality is very limited. We aimed to investigate associations between road and railway noise and natural-cause and cause-specific mortality in the Danish population. We estimated address-specific road and railway noise at the most (LdenMax) and least (LdenMin) exposed façades for all residential addresses in Denmark from 1990 to 2017 using high-quality exposure models. Using these data, we calculated 10-year time-weighted mean noise exposure for 2.6 million Danes aged >50 years, of whom 600,492 died from natural causes during a mean follow-up of 11.7 years. We analyzed data using Cox proportional hazards models with adjustment for individual and area-level sociodemographic variables and air pollution (PM 2.5 and NO 2). We found that a 10-year mean exposure to road LdenMax and road LdenMin per 10 dB were associated with hazard ratios (95% confidence intervals) of, respectively, 1.09 (1.09; 1.10) and 1.10 (1.10; 1.11) for natural-cause mortality, 1.09 (1.08; 1.10) and 1.09 (1.08; 1.10) for cardiovascular mortality, 1.13 (1.12; 1.14) and 1.17 (1.16; 1.19) for respiratory mortality and 1.03 (1.02; 1.03) and 1.06 (1.05; 1.07) for cancer mortality. For LdenMax, the associations followed linear exposure-response relationships from 35 dB to 60–<65 dB, after which the function levelled off. For LdenMin, exposure-response relationships were linear from 35 dB and up, with some levelling off at high noise levels for natural-cause and cardiovascular mortality. Railway noise did not seem associated with higher mortality in an exposure-response dependent manner. In conclusion, road traffic noise was associated with higher mortality and the increase in risk started well below the current World Health Organization guideline limit for road traffic noise of 53 dB. [Display omitted] • Road noise was associated with higher cardiovascular, respiratory and cancer mortality. • Results were robust to adjustment for air pollution. • Increase in mortality risk started below current guideline limits for road noise. • Railway noise was not associated with mortality. [ABSTRACT FROM AUTHOR]