Estimating the harmful effects of environmental transport noise: An EU study

Crowdsourced cycling data applications to estimate noise pollution exposure during urban cycling

This research demonstrates a methodology to integrate freely available datasets to understand the relationship between road traffic noise and cycling experiences in a medium sized city. An illustrative example of the methodology was drawn from data for Dublin, Ireland. We aggregate local environmental data with 81,403 Strava cycle trips, contextualised by feedback from 335 cyclists to estimate exposure levels and infer impacts on experiences and behaviours. Results demonstrate that cyclists recognise that they are subjected to increased noise levels and experience negative psychophysical consequences as a result, but they tend to downplay the impact of noise as merely a minor annoyance. Noise also impacts behaviour, most noticeably through temporal and spatial detours. Geospatial mapping was used to visualise the relationship between noise pollution and cycling activity. Estimating traffic noise levels across two cycle routes, direct vs popular detour, revealed a +10 dB(A) increase in exposure for a saving of approximately 4 min on the direct route compared to the detour. Spatial inequities in exposure levels may have serious health consequences for cyclists in a city such as Dublin. The methodology is demonstrated as suitable for policy level interventions and planning purposes.

Spatial assessment of the attributable burden of disease due to transportation noise in England

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.

Contribution of outdoor noise-induced health risk in schools located in urbanized arid country

Ambient noise pollution is deemed as one of the major growing public health issues, especially in developing countries. Therefore, it is crucial to assess the impact of noise pollution on public health. The aim of this study is to investigate the health risk of noise exposure levels in three schools: Kaab Bin Zeyd of Basic Education (school A), Hail Al-Awamour Girls school (school B), and Al-Fikr School (school C) in Muscat, Oman. The study employed a survey of 300 students, dose-response models, and regression models to quantify health risk and to determine the relationship between noise levels and perceived noise annoyance sources. The study found average noise levels (L_Aeq) of school A (70.03±8.21 dBA), school B (69.54±7.75 dBA), and school C (55.95± 5.67 dBA) to be higher than WHO's outdoor schools environment standard of 55 dBA and European (EN16798-1) classroom's critical limits of 30-34 dBA. Most of the students from schools A (30.9%), B (33.3%), and C (63%) have reported noise produced from traffic as extremely annoyed compared to aircraft of 15.4%, 11.5%, and 27.2%, respectively. Regression analysis shows that perceived traffic noise was strongly correlated with L_Aeq in school A (R² =0.481), B (R² =0.121), and C (R² = 0.132) when compared with other subjective noise types. The health risk assessment results show that the percentage of highly annoyed (%HA) was higher in school A (15.2%) and school B (14.95%) than in school C (8.18%). The estimated highly sleep disturbed (%HSD) based on mean noise levels were almost the same in schools A (15.62%) and B (15.19%) but far higher compared to school C (6.01%). However, there was an association between the mean noise exposure levels and the risk of developing ischemic heart diseases (IHD) in school A (RR= 1.172, 95% CI: 1.020-1.334), school B (RR=1.167, 95% CI: 1.020-1.325), and school C (RR=1.051, 95% CI: 1.006-1.095). Moreover, attributable risk percentage (AR%) for school A (AR% =14.675, 95% CI: 2.028-25.037), school B (AR% =14.310, 95% CI: 1.960-24.528), and school C (AR% = 4.852, 95% CI:0.596-8.742) have shown that a substantial portion of the population could be prevented from developing IHD. It is expected that findings of the study can be applied in other arid regions with sprawl urbanized built environments.

The influence of the brake pad construction on noise formation, people's health and reduction measures

The brake system is one of the most important systems on the vehicle, especially from the aspect of traffic safety. The use of the braking system comes with many undesirable effects, such as brake wear and noise emission. The noise that originates from brakes is related to the wear of brake elements, the applied materials for manufacture, to the elements which are connected to each other, and all of this represents a very challengeable problem in the automotive industry. In this paper are presented the dominant parameters that influence noise formation, where the main focus was placed on brake pads, as well as how the noise influences people's health. After that, further, in the paper, it was analyzed the influence of the brake pads' construction on the noise formation, and at the end are given the measures for noise reduction. The conclusions of the paper show that the construction of brake pads significantly influences noise emission, noise negatively influences on the people health, and because of the negative influence on the people health, some solutions show that it is necessary to include insulators in the construction of brake pads, and if the space in which people reside is observed, it is necessary during construction to use materials which will prevent noise conduction, into the space in which people reside.

Automated identification and assessment of environmental noise sources

Noise pollution is one of the major health risks in urban life. The approach to measurement and identification of noise sources needs to be improved and enhanced to reduce high costs. Long measurement times and the need for expensive equipment and trained personnel must be automated. Simplifying the identification of main noise sources and excluding residual and background noise allows more effective measures. By spatially filtering the acoustic scene and combining unsupervised learning with psychoacoustic features, this paper presents a prototype system capable of automated calculation of the contribution of individual noise sources to the total noise level. Pilot measurements were performed at three different locations in the city of Ljubljana, Slovenia. Equivalent sound pressure levels obtained with the device were compared to the results obtained by manually marking individual parts of each of the three measurements. The proposed approach correctly identified the main noise sources in the vicinity of the measurement points.

Improving strategic noise mapping of railway noise in Europe: Refining CNOSSOS-EU calculations using TWINS

The Environmental Noise Directive (2002/49/EC) requires all European Union Member States to produce strategic noise maps using a common assessment methodology: CNOSSOS-EU. The reliability of CNOSSOS-EU railway noise evaluation is dependent on the input vehicle and track transfer functions. The CNOSSOS-EU default database contains the currently available choices for these transfer functions. However, these available transfer functions are limited and of insufficient quality, resulting in large errors in noise level calculations. An approach is presented, introducing an established analytical railway rolling noise calculation technique (TWINS), to extract more reliable and specific transfer functions. A case study consisting of railway rolling noise mitigation measures is defined and used as the basis for extracting and testing these transfer functions. The extracted transfer functions reduce the average deviation between CNOSSOS-EU and reference calculations using TWINS from 6.1 dB(A) to 0.8 dB(A) in absolute sound power levels, and from 1.2 db(A) to 0.3 dB(A) in estimates of noise reduction potential for the defined mitigation measures. Application of this approach shows potential to improve the quality and depth of the existing CNOSSOS-EU default database. This may lead to more reliable estimations of railway noise in the strategic noise maps and the subsequent assessment of its harmful effects.