ASSESSMENT OF RAIL TRANSPORT NOISE PERCEIVED BY TRACKSIDE DWELLERS

Abstract

Unplanned urbanization has led to the settlement of migrants from rural areas close to railway lines, exposing them to the continuous noise levels from the moving trains. These high, intense noise levels annoy and adversely affect the health of individuals living near railway lines. Every ambient noise study employs the source-path-receiver structure to explore the overall behavior of sound. Therefore, noise control techniques are necessary to modify the noise source mechanism, transmission path characteristics, and receiver perception. Among these techniques, eliminating railway noise at the source is the most effective method for mitigating noise. This study evaluated different train types, including various speeds and lengths, to determine their correlation with noise levels. Results showed that train speed had the strongest correlation with noise levels, the driving factor for maximum noise levels. When the train speed increases by 10 km/h, noise levels rise by 2.8 to 3 dBA. In the case of freight trains, the train length is a key parameter in the emission of railway noise when compared to passenger trains. The study also identified the type of trains with the highest noise levels, and a detailed examination of the mechanism responsible for this phenomenon was carried out. Multiple linear regression models for maximum and equivalent noise levels were developed for passenger and freight trains. In addition to source parameters, the current study 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 blown as trains approach railway level crossings and are mandatorily used to alert road users. However, the train horns are considered a nuisance to the nearby residents. A comprehensive noise monitoring survey was conducted at an access-controlled level crossing. Further, an Artificial Neural Network (ANN) based railway noise prediction model was developed to forecast maximum (Lmax) and equivalent (Leq) noise levels. Results revealed that train horns produced impulsive sound signals that fall under high-frequency one-third octave bands, causing severe irritation to trackside inhabitants. Noise levels are affected by changes in distance, intervening barriers, and atmospheric conditions along the transmission path between the source and the receiver. This study explored the variance of railway noise in an urban setting over various measuring distances, including 25, 50, 100, and 200 m, with variables such as air temperature, humidity, and wind conditions. Results showed that the effect of the wind was more significant for larger distances between the source and the receiver. For every 1 m/s increase in wind speed within a distance of 50 m, the average sound attenuation induced by the upwind phenomena was 0.2 dBA. The impact of air temperature changes on received xx sound level from a moving source was insignificant within the range of temperatures considered in the study. The effect of humidity was observed to be less at shorter distances but at larger distances, increasingly attenuates noise levels. Along the transmission path, the presence of a wall between the source and receiver can act as a noise barrier resulting in a reduction in intensity of noise. In urban areas, railway boundary walls are constructed to prevent encroachments of railway lands and to avoid pedestrians trespassing the railway tracks. This study aims to evaluate the effectiveness of such a boundary wall in reducing noise and proposes an improved alternative through Computational Fluid Dynamics (CFD) simulations. Various noise barriers with different geometry, shape, and surface materials were simulated and verified through field study measurements. Noise attenuation was evaluated by measuring railway noise spectra at different positions, including 0.5 m in front and behind the barrier and at the facade of the residential area. Results showed that as barrier height increased, insertion loss also increased, with a maximum attenuation of 17 dBA achieved with a rectangular barrier of height 6 m. The most effective noise barrier for reducing railway noise was a T-shaped barrier with a height of 6 m and a projection length of 2 m, with an insertion loss of 22 dBA. This study recommends constructing the barrier with soft materials on its surface to reflect and absorb sound waves effectively. In the last phase of this study, the impact of railway noise on the residents living along the railway line at several distances was assessed by measuring the noise inside houses. Additionally, a human perception survey was conducted to investigate the relationship between noise levels and annoyance during daily activities such as working, resting, conversing, eating, talking on the phone, and reading. Structural Equation Models (SEM) were employed to analyze the complex relationships between annoyance, disturbance, and health effects. The outcomes of this study reveal that both passenger and freight trains exceeded the permissible noise limits, with an excess of 36.8% and 15% during daytime and 75.15% and 41.8% during nighttime, respectively. The primary factors contributing to annoyance were identified as the source type and location of noise exposure. The annoyance levels associated with the time of noise exposure negatively impacted disturbances to daily activities and subsequent health effects. This phenomenon suggests a psychological adaptation known as habituation, where residents along railway lines gradually become accustomed to the noise over time. Furthermore, the cumulative impact of disturbances to daily activities can indirectly influence long-term health. Proximity to the railway line amplifies the relationship between annoyance and health effects.