Railway Noise Research Articles

Residential exposure to transportation noise and risk of incident atrial fibrillation: a pooled study of 11 prospective Nordic cohorts

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. 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 (Lden) and AF after adjusting for sociodemographics, lifestyle, and air pollution. 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 ≤40dB, aircraft noise of 40.1-50 and>50dB 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 (≥45dB), railway (>40dB), and aircraft (>40dB) combined. Road traffic noise, and possibly aircraft noise, may be associated with elevated risk of AF. NordForsk.

Railway-induced vibration combined with railway noise - a systematic review with exposure-effect curves

The combined health impact of concurrent railway noise and railway vibration exposure is not yet well understood. This systematic review aimed to investigate the combined effects of vibration and concurrent noise. 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. Our results based on epidemiological studies are corroborated by findings of laboratory studies. 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.

Evaluation of railway noise calculation models using CNOSSOS-EU considering the effect of rail roughness

Railway noise assessment is an important tool in decision-making for urban planning, investment in transportation infrastructure and implementation of noise reduction strategies. Currently, the procedure is based on CNOSSOS-EU (Common Noise Assessment Methods in Europe), which was developed in accordance with European Directive 2002/49/EC. This method takes into account a variety of factors impacting rail noise levels, such as vehicle characteristics and track features. The purpose of this study was to investigate the influence of rail roughness on generated railway noise and to evaluate the accuracy of calculation models using CNOSSOS-EU. The study involved in-situ railway noise measurements at three different locations near the city of Zagreb, Croatia, and measuring rail roughness at each location. In order to eliminate the influence of other factors, the rail track structures at the measurement locations were similar, and an identical train configuration was used for the study. Finally, a comparison was made between calculation models based on default roughness values and models including values obtained from in-situ measurements. This approach enabled an assessment of the variations in CNOSSOS-EU calculation models taking into account actual in-situ rail roughness measurements.

Enhancing railway noise reduction through advanced multilayer acoustic absorbent systems with tunable resonators

Railway noise poses a significant environmental challenge, prompting the need for effective mitigation strategies. In response, noise barriers are often employed to reduce noise near railways. This research focuses on the use of porous materials, more specifically porous concrete, for acoustic absorption, particularly in the context of railway noise reduction. A novel approach is proposed, wherein porous multilayer metamaterial systems are developed, with each layer's macroscopic parameters strategically optimized to enhance the overall sound absorption curve. Additionally, to broaden the frequency range of noise attenuation, tunable resonators are seamlessly integrated into the multilayer system. The analytical framework for analyzing both the multilayer system and resonators involves employing equivalent fluid models and the analytical transfer matrix method. Linear regressions were employed to establish relationships between porosity, density, and other macroscopic parameters, enabling the derivation of the sound absorption curve solely from these parameters. Through systematic optimization and integration of resonators, it is expected that, the proposed approach demonstrates significant advancements in railway noise reduction efficacy across a wide frequency range. This research aims to contribute to the development of more efficient and versatile acoustic absorbent systems for mitigating railway noise pollution.

Improving knowledge of the acoustic factors involved in railway noise annoyance: first results of a pilot field survey of sixty-two local residents

Railway transportation contributes to the objectives of decarbonization but also generates negative externalities, including noise. Energy noise indicators used to characterize population exposure do not adequately reflect the repetitive nature of railway noise peaks. The GENIFER pilot study aims to test a protocol designed to characterize railway noise events according to the instantaneous perceived annoyance when the train is passing, in order to improve understanding of the influence of acoustic factors on annoyance. The first phase of the survey was carried out in 2023 among 62 residents of a pilot site. An electronic device was used to collect around 5,000 ratings, ranging from 1 to 10, assessing the instantaneous annoyance induced by train noise at passing trains. The site instrumentation included sixteen sound level meters and two video recording systems, enabling annoyance ratings to be associated with the acoustic characteristics of railway noise events. A questionnaire aimed at identifying co-determinants of long-term annoyance was also administered to participants. Feedback on the field implementation of this survey and initial results concerning acoustic measurements, instantaneous annoyance ratings and questionnaire responses will be presented.

Effect of the railway wheel design on rolling noise

Railway noise has become a relevant problem, especially along the urban environments. In this sense, the pollution noise coming from the rolling noise can affect the health of people in the surrounding area. For this reason, the present work focuses in reducing the total rolling noise radiated by the wheel, rail and sleeper through a study of the influence of the relevant geometric parameters involved. A comprehensive vibroacustic model of the wheel and track is considered, taking into account their dynamic interaction. The influence of the wheel geometry on the radiated sound has been evaluated by means of statistical techniques, quantifying the importance of each design parameter.

Annoyance assessment of the combined effect of railway noise and vibration including physiological measurements

The prediction of annoyance due to railway transportation in residential areas is crucial to correctly dimension noise and vibration reduction solutions. In situ annoyance assessment for multiple exposition scenarios requires to convince many residents to take annoyance tests combined with noise and vibration measurements inside their homes. Such approach is not adapted to large-scale experiments. Therefore, the VibAcouPhysio project aims at studying annoyance due to railway noise and vibration in laboratory conditions. A vibrating platform combined with a high-quality sound reproduction system has been designed for this project to reproduce the noise and vibrations of a train pass-by. Annoyance is estimated by multiple means including questionnaires, cognitive tasks performance assessment and various physiological measurements. Twenty participants were exposed to various train pass-by signals as if they were seating at a table inside their housing. The results show a significant correlation between physiological metrics, the annoyance evaluated in the questionnaires and the physical indicators derived from the noise and vibration signals. The main purpose of the VibAcouPhysio project is to rank various physical indicators describing noise and vibration signals according to their correlation to the perceived or measured annoyance.

Enhanced railway sound event detection using YAMNet and classification criteria

The segmentation-by-classification method has become a popular way to detect sound events. It uses neural networks, trained to detect sound sources on short signals (one tenth of a second to a second), or long-term signals divided into a succession of short segments. In this paper, we focus on detecting train pass-bys from long term signals, where it is assumed that railway noise is higher than ambient noise. Using the neural network YAMNet, we show that a processing stage is necessary to improve the segmentation of such events and reduce the high false positive rate. The applied criteria are related to the nature of a train pass-by, lasting several seconds and with broad frequency band. Around 90% of events are detected with proper boundaries. However, we observe that YAMNet is not designed to distinguish railway vehicles from other vehicles. False positive rate remains high whenever other vehicles travel near the measurement location. Additional AI models are proposed to perform this specific distinction. Their efficiency depends on train type, as recent passenger train noise resembles roadway noise. Otherwise, false positive rate decreases below 10%, and the railway noise contribution estimate aligns with the reference level, within a 0.5 dB(A) margin on average.

Results of a pilot study using experience sampling method to assess railway noise annoyance

This article aims to report on the development of a method to study the acoustic factors driving the short-term annoyance experienced by neighbors of high-speed train lines (> 250 km/h). In fact, current indicators (e.g., LDEN) only partially explain annoyance caused by high-speed trains noise. They could potentially be improved by considering some event-related aspects (e.g., the suddenness, spectral content, temporal fluctuations), whose role remains not fully understood. The development of a protocol dedicated to these issues is an essential prerequisite. A review of the different methods used to study transportation noise annoyance highlights the benefits of the experience sampling method (ESM), not yet used for railway noise assessment. This method allows participants to report their annoyance right after a train pass-by with a remote device while noise exposure is simultaneously recorded. We report on the results of a pilot study aiming to test an experimental protocol by proposing an adaptation of the experience sampling method to study annoyance caused by the passage of high-speed trains. Residents were recruited to take part in the study and received two protocols in two different periods. The most efficient ESM parameters were determined, and further possibilities offered by this new methodology are discussed.

Transportation noise and cardiovascular health: an Umbrella+ review

A significant number of studies have shown an association between transportation noise and cardiovascular diseases. With this Umbrella+ review, we aimed to provide a comprehensive overview of the literature on the relation between transportation noise and various cardiovascular health outcomes such as ischaemic heart disease, stroke, heart failure, blood pressure and hypertension, as well as cardiovascular mortality. Following the Umbrella+ approach, we first identified the newest review of high quality and then original high-quality studies published thereafter. Further, by including the latest studies we performed a meta-analysis to derive up-to-date exposure-response functions for each noise source (road traffic, railway and aircraft) separately. We found that compared to road traffic noise, less research was available for railway and aircraft noise. Regarding road traffic noise, we identified a significantly increased risk for multiple cardiovascular health outcomes. For example, the pooled effect estimate for cardiovascular mortality was 1.05 (95% CI: 1.02-1.07) per 10dB(A) increase in noise, for the incidence of ischaemic heart disease it was 1.04 (95% CI: 1.02-1.06) and for stroke incidence 1.05 (95% CI: 1.01-1.08) per 10dB(A) increase in noise. This work will be used to quantify the burden of disease from transportation noise for the general population in Europe.

Sources for railway community noise modeling

For rail traffic, the wheel-rail interaction is one of the most important sources of noise, and is included in different ways in the noise calculation methods being used in Sweden today. However, if the rolling stock exhibit other noise sources it is not clear how they are handled by the different calculation methods. Recent measurements in Sweden of the newly refurbished 'X2' passenger trains indicate that cooling fan exhausts mounted high up on the driving unit radiate noise at levels corresponding to the wheel-rail noise at speeds of 200 km/h. The NMT96 calculation method currently used in Sweden represents the whole train as one line source per octave band, each placed at different heights. The newer Nord 2000 method, applies three sources at low heights for rolling noise and allows additional sources but without defining how to accommodate them. The Cnossos-EU method puts all potential exhaust and fan noise at the higher of two sources, at 4 m above the rail. None of the models define how to apply a source to just the locomotive as sound power is given per meter train or per rolling axis. The impact on noise exposure and mitigation is discussed in this paper.

Noise reducing elements filled with laminated safety glass (LSG) for use along railway lines

The main purpose of noise barriers is to shield the environment from unwanted sound. Along railway lines, noise barriers must also meet strict requirements for structural integrity, usability and fatigue safety. Furthermore, noise barriers should satisfy aesthetic criteria. Transparent noise barriers have less impact on the environment and are more widely accepted by the public. In Germany, PMMA (acrylic glass) is currently the only transparent material approved for railway noise reducing elements. Laminated safety glass (LSG) could be a viable alternative due to its high rigidity and transparency, comparatively low dirt accumulation and high chemical and physical resistance. However, it still needs to be demonstrated that LSG meets the strict requirements for use along railway lines. LSG is a type of laminated glass that has a splitter-binding intermediate layer of plastics. The multi-layered structure presents challenges regarding the proof of usability. MFPA Leipzig GmbH was commissioned by the German Centre for Rail Traffic Research at the Federal Railway Authority to develop and evaluate possible methods to prove the usability of LSG for noise barriers along railway lines. The paper presents the structure of the project, the main findings until now and the open challenges to be addressed.

Measures to abate railway noise

An important environmental issue in densely populated areas, such as Germany or France, is the problem of noise. Traffic noise from cars, railway vehicles and airports located in close proximity to the city is not only annoying for residents; it also leads to serious health issues and has an enormous negative economic impact. Unlike road traffic noise, which occurs virtually everywhere, rail traffic noise is much more localized to individual transport corridors. However, depending on the type of train and the volume of trains, high levels of noise can be generated, especially along freight corridors on which most of the rail traffic is at night. One example is the Middle Rhine Valley, which is part of the European freight corridor between Rotterdam and Genoa. In many places along this corridor, the noise levels are essentially higher than those considered desirable to maintain good health. The noise caused by rail traffic is therefore the ecological Achilles heel of the railway. However, there are measures for the reduction of noise emitted by rail traffic. In a recent research project, the German Environment Agency evaluated technical, operational and legal measures to abate the railway noise.

Advancements in railway noise simulation: assessment of tools for virtual validation

In pursuit of more efficient and cost-effective measurement campaigns, the railway industry is embracing the prospect of virtual validation based on simulations. The primary obstacle lies in the need for noise simulation tools capable of accurately replicating complex sources, installation effects, noise propagation, ground reflection and, for some cases, the diffraction in the different train surfaces. This paper presents insights derived from European project Shift2Rail S2R-CFM-CCA-01-2019 Energy and Noise & Vibration WP6, concentrating on the validation and enhancement of two exterior noise simulation tools, tailored for railway applications. The paper covers four reference cases, simulating exterior noise at standstill with diverse noise sources and varying source locations and noise emission (i.e. electrical noise, cooling, etc.). A correlation with previously conducted measurements at typical receiver locations (7.5 meters from the track centerline) is carried out. The measurements were conducted in a "controlled" configuration, isolating as much as possible the analyzed noise source and gathering all the needed information about the ground and train geometry. The evaluation between measurements and simulations is done against a global and a 1/3rd octave band criteria with successful results. Finally, key features essential for achieving more accurate simulations are listed.

A bottom-up numerical model for wheel-rail contact to predict rail-way noise emission

Pass-by noise emission models are often based on measurement databases, yielding engineering models that are fast enough to calculate noise maps or to do predictions based on existing infrastructure. However, these cannot predict the effect of innovative components, either in the track or in the rolling stock. Changing properties of a single component, e.g. damping of rail pads or the profile of a wheel, leads to a chain of coupled effects including the dynamics of the individual component, the contact force, the vibrational velocity, and finally the emitted noise. These intricate interactions can only be captured by detailed numerical models. We present a step-by-step implementation that allows to predict the effect of changes on the component level on the pass-by noise emission. The model includes the finite element calculation of the mobility of track and wheel separately, and uses these to derive the contact force from the combined roughness and train speed. Next, the vibration velocities of rails, sleepers, and wheels are used as input for a boundary element calculation of the noise emission. Pass-by measurement results validate the models, and show good agreement if wheel-rail contact noise is dominant and secondary sources can be ignored.

Railway noise monitoring - a tool to analyse in detail the evolution of noise over time during a rolling stock renewal period

As part of the commissioning of a rail freight project, a noise monitoring system was set up to track the increase in rail freight traffic and to monitor noise over time. Noise monitoring is done by continuous measurement stations, an analysis of the classic noise exposure indexes LAeq,6-22h and LAeq,22-6h is realized, completed by an analysis of several event acoustic indexes, with a distinction between the different traffic types (Freight, regional trains). In addition, the European Regulation EU 2019/774 on the application of the technical specification for interoperability relating to the subsystem 'rolling stock - noise' to the existing freight wagons, obliges the circulation of less noisy freight trains on certain itineraries called "Quieter routes" from 8/12/2024. The projected benefit will not be limited to the nearby residents of these routes but will, by indirect consequence, enable a gradual acoustic gain on all the French rail freight routes, due to the retrofit or renewal of the existing rolling stock. The goal of the noise monitoring system is also to quantify the acoustic gains from the indirect effects of this new regulation.

Research on the effects of railway noise and biaxial vibration on calculation disturbances

This study conducted an evaluation experiment on simultaneous exposure to noise and two-axis vibration stimuli from railways, using noise stimuli from railways and two-axis vibration stimuli in the horizontal-vertical direction, and verified differences in evaluation of interference due to differences in noise and the direction of vibration. The experiment was conducted in a laboratory with a vibration exciter placed in a simple anechoic chamber, with the participation of 20 students. The stimuli presented utilized vibrations recorded indoors and sounds recorded outdoors. Both vertical and horizontal vibrations were presented in four levels, and the sound stimuli were presented at three levels: 50, 60, and 70 dB. The evaluation of annoyance and interference showed that under conditions of noise levels of 50 dB and 60 dB, discomfort and interference increased as the vertical vibration level increased with horizontal vibration levels (X: 2-6), confirming the combined effect of vertical vibration and noise. Even under conditions of a noise level of 70 dB, except for vibration conditions X: 2, Z: 2, and X: 6, Z: 6, the combined effect of vertical vibration and noise was confirmed.

A time-domain approach to predict sound radiation from track vibrations

With the intended shift of transport from road to railway, noise exposure due to railway noise will increase. Auralisation of the noise is a key tool for assessing noise perception beyond equivalent sound pressure levels. Researching the connection between, for example, track design parameters and perceived sound quality holds potential for perception-centered track design. A computationally efficient model is required to render the sound field generated by the track vibration. In this paper, using simulated time-domain surface velocities of a rail and sleepers as input, such a model is presented. The sound pressure signal in a position on the side of the track is efficiently predicted by convolving these velocities with precalculated acoustic transfer functions. For a typical ballasted track, the necessary spatial discretisation of the evaluated velocities is determined in a convergence study. Further, the required length of the finite section of the track to be included in the prediction is specified. Finally, pass-by signals generated by track vibration are demonstrated.

Railway psychoacoustic annoyance - an indicator for planning infrastructure projects

The joint project "Real-time Calculation, Auralization and Visualization of Sound Propagation and Noise Protection Measures for Infrastructure Projects" (EAV-Infra), funded by the German Federal Ministry for Economic Affairs, investigates the potentials of digital infrastructure planning based on Building Information Modeling (BIM) in combination with state-of-the art Auralization and Visualization technology as well as Psychoacoustic Modelling. Currently, log-scaled sound pressure levels, which are only informative to experts, are used to communicate the topic of noise exposure to the public. Auralization, in combination with a hearing-oriented noise index, will constitute a more intuitive and understandable evaluation basis for residents. One focal point of EAV-Infra is the development of a linearly-scaled metric for railway noise, which correlates better with human perception than the LAeq. Binaural recordings of a wide spectrum of different railway pass-by scenarios were presented in listening experiments to obtain semantic-differential information about the sounds as well as global and continuous annoyance ratings for individual passings. Currently, a railway psychoacoustic annoyance metric is being developed by comparing two fitting methods: a classical model based on common psychoacoustic quantities, as well as an AI model with a Mel-log-spectrogram-CRNN architecture. The approach and first results will be discussed in this contribution.

Towards the development of measurement and analysis method for aerodynamic noise emission from high speed train: the UIC Aeronoise Project

The increase of railway lines operating at speeds above 250 km/h has shifted the attention towards environmental noise emissions by aerodynamic noise, dominant at these speeds. Adding complexity to the issue, while railway noise emissions at conventional speeds are concentrated in the lower parts of the train, aerodynamic noise emissions are distributed along the train at different heights and depending on the train design. Assessment of aerodynamic noise emissions of high speed train has been endeavored using microphone arrays, implementing different variants of the wave beamforming algorithm. This method involves a quite complex post-processing, and also numerical quantification of results is not immediate. UIC AERONOISE project has aimed at developing a simplified pass-by test methodology capable of quantifying aerodynamic noise emissions from high speed , using exclusively a limited number of standard instrumentation microphones. This methodology has been validated theoretically and is currently undergoing experimental tests. Fundamental points in this methodology are explained in this contribution, together with results achieved so far.