Longitudinal annoyance responses to a road traffic noise management strategy that reduced heavy vehicles at night

Analysis of single vehicle noise emissions in the frequency domain for two different motorizations

Environmental noise, primarily attributed to the road transportation system, poses a significant challenge in Europe, impacting the quality of life for millions. Therefore, a thorough characterization of noise emissions from road transportation sources is needed to stem this problem. This investigation aims to fill a gap in the literature regarding single-vehicle noise emissions in the frequency domain. The emphasis is on motorization (i.e., fuel type), with particular attention to Low-Frequency components, due to their potential impact on human health and ecosystems. Two probe vehicles, a diesel and a Liquefied Petroleum Gas-powered, were employed to collect data for noise emission curves in the frequency domain (from 63 to 8000 Hz) and compare them with those furnished in the CNOSSOS-EU, Harmonoise, and REMEL models. Moreover, data in terms of exhaust noise emissions (at the tailpipe) were also gathered and analyzed in the frequency domain. The analysis highlighted motorization's influence on noise emissions, revealing differences in frequency component contributions to the overall sound power level at different speeds. Low-frequency components were found to be predominant for both vehicles, especially at lower speeds, where the engine noise contribution dominates. This finds its endorsement in the frequency analysis on the noise emission curves provided in the examined models. The evaluation of the exhaust noise emissions revealed resonance phenomena at 63 Hz and showcased the dominance of low-frequency components in the exhaust spectrum (despite the penalization introduced by the A-weighting procedure), opening avenues for understanding and lowering noise emissions during vehicle idling and low-speed operations.

Did Noise Pollution Really Improve during COVID-19? Evidence from Taiwan

Background and objectives: The impacts of COVID-19 are like two sides of one coin. During 2020, there were many research papers that proved our environmental and climate conditions were improving due to lockdown or large-scale restriction regulations. In contrast, the economic conditions deteriorated due to disruption in industry business activities and most people stayed at home and worked from home, which probably reduced the noise pollution. Methods: To assess whether there were differences in noise pollution before and during COVID-19. In this paper, we use various statistical methods following odds ratios, Wilcoxon and Fisher’s tests and Bayesian Markov chain Monte Carlo (MCMC) with various comparisons of prior selection. The outcome of interest for a parameter in Bayesian inference is complete posterior distribution. Roughly, the mean of the posterior will be clear with point approximation. That being said, the median is an available choice. Findings: To make the Bayesian MCMC work, we ran the sampling from the conditional posterior distributions. It is straightforward to draw random samples from these distributions if they have regular shapes using MCMC. The case of over-standard noise per time frame, number of noise petition cases, number of industry petition cases, number of motorcycles, number of cars and density of vehicles are significant at α=5%. In line with this, we prove that there were differences of noise pollution before and during COVID-19 in Taiwan. Meanwhile, the decreased noise pollution in Taiwan can improve quality of life.

WHO Environmental Noise Guidelines for the European Region: A Systematic Review of Transport Noise Interventions and Their Impacts on Health

This paper describes a systematic review (1980-2014) of evidence on effects of transport noise interventions on human health. The sources are road traffic, railways, and air traffic. Health outcomes include sleep disturbance, annoyance, cognitive impairment of children and cardiovascular diseases. A conceptual framework to classify noise interventions and health effects was developed. Evidence was thinly spread across source types, outcomes, and intervention types. Further, diverse intervention study designs, methods of analyses, exposure levels, and changes in exposure do not allow a meta-analysis of the association between changes in noise level and health outcomes, and risk of bias in most studies was high. However, 43 individual transport noise intervention studies were examined (33 road traffic; 7 air traffic; 3 rail) as to whether the intervention was associated with a change in health outcome. Results showed that many of the interventions were associated with changes in health outcomes irrespective of the source type, the outcome or intervention type (source, path or infrastructure). For road traffic sources and the annoyance outcome, the expected effect-size can be estimated from an appropriate exposure-response function, though the change in annoyance in most studies was larger than could be expected based on noise level change.

Quantification of the exposure and effects of road traffic noise in a dense Asian city: a comparison with western cities

BACKGROUND

Particularly in Asia, dense, traffic-intense, and usually high-rise cities are increasingly the norm. Is existing knowledge on exposure to road traffic noise, and on people's response to such exposure, garnered primarily from western cities, equally applicable in these?

METHODS

Hong Kong has high population and traffic density and a high-rise building form. Road traffic noise exposure was estimated, and residents' responses to traffic noise measured, for a sample of 10,077 dwellings. Noise level estimates were based on three-dimensional modelling. Best international survey practice measured self-reported annoyance and sleep-disturbance. Benchmark estimates of exposure, and of annoyance and self-reported sleep disturbance, are provided. We compare Hong Kong exposure with those of European cities, and the exposure-response relationship for annoyance in Hong Kong to those reported from elsewhere - based on the tolerance limits of previous syntheses. Exposure-response for self-reported sleep disturbance is also compared.

RESULTS

The distribution of exposures of dwellings in high-rise, high-density, Hong Kong is different from those reported from Europe, but not at the higher noise levels. The exposure-annoyance relationship for road traffic noise was from the same population of exposure-response relationships, being well within the tolerance limits, of studies used to generate the synthesized Miedema and Oudshoorn curves. The exposure-response curve for self-reported sleep disturbance was parallel to that of Miedema and Vos but slightly lower.

CONCLUSIONS

The proportion of the Hong Kong population exposed to high levels (>70 dB) is similar to that found in Europe. However, a much higher proportion, compared to European cities, is exposed to Lden levels of 60-64 dB, and a much lower proportion to lower levels (<55 dB). There is no evidence that the exposure-response relationships for annoyance and self-reported sleep disturbance in Hong Kong are different from relationships synthesized from earlier studies - despite the western bias and temperate-climate bias in the studies available in the syntheses. This is an important finding for urban planning and traffic noise management of the growing mega-cities in the world whose built forms can be expected to reflect that of Hong Kong more than of cities in the west.