Exposure to traffic noise is associated with stress and sleep disturbances. The World Health Organization (WHO) recently concluded that road traffic noise increases the risk for ischemic heart disease and potentially other cardiometabolic diseases, including stroke, obesity, and diabetes. The WHO report focused on whole-day noise exposure, but new epidemiological and translational field noise studies indicate that nighttime noise, in particular,is an important risk factor for cardiovascular disease (CVD) through increased levels of stress hormones and vascular oxidative stress, leading to endothelial dysfunction and subsequent development of various CVDs. Novel experimental studies found noise to be associated with oxidative stress–induced vascular and brain damage, mediated by activation of the NADPH oxidase, uncoupling of endothelial and neuronal nitric oxide synthase, and vascular/brain infiltration with inflammatory cells. Noise-induced pathophysiology was more pronounced in response to nighttime as compared with daytime noise. This review focuses on the consequences of nighttime noise.

The aim of the present study is to establish exposure-response relationships reflecting the percentage highly annoyed (%HA) as functions of road traffic, railway, and aircraft noise exposure, measured as day-evening-night level (Lden), as well as to elucidate the degree to which the acoustic indicator Intermittency Ratio (IR), which reflects the "eventfulness" of a noise situation, predicts noise annoyance. We conducted a mixed-mode representative population survey in a stratified random sample of 5592 residents exposed to transportation noise all over Switzerland. Source-specific noise exposure was calculated for each floor and each façade based on comprehensive traffic data. Noise annoyance was measured using the ICBEN 11-point scale. The survey was carried out in 4 waves at different times of the year. We hypothesized that in addition to Lden, the effects of noise on annoyance can be better explained when also considering the intensity of short-term variations of noise level over time. We therefore incorporated the acoustic indicator IR in the statistical models. For all noise sources, results revealed significant associations between Lden and %HA after controlling for confounders and independent predictors such as IR (measured over 24 h), exposure to other transportation noise sources, sex and age, language, home ownership, education level, living duration, temperature, and access to a quiet side of the dwelling. Aircraft noise annoyance scored markedly higher than annoyance to railway and road traffic noise at the same Lden level. Railway noise elicited higher percentages of highly annoyed persons than road traffic noise. Results furthermore suggest that for road traffic noise, IR has an additional effect on %HA and can explain shifts of the exposure-response curve of up to about 6 dB between low IR and high IR exposure situations, possibly due to the effect of different durations of noise-free intervals between events. For railway and aircraft noise annoyance, the predictive value of IR was limited.

The number of operations of Unmanned Aerial Vehicles (UAV), commonly referred to as “drones”, has strongly increased in the past and is likely to further grow in the future. Therefore, drones are becoming a growing new source of environmental noise pollution, and annoyance reactions to drone noise are likely to occur in an increasing share of the population. To date, research on drone noise emission characteristics, and in particular also on health impacts, seems scarce, but systematic overviews on these topics are missing. The objective of this study was to establish a systematic literature review on drone noise emissions and noise effects on humans. The paper presents the methodology of the systematic reviews performed separately for noise emission and noise effects, assembles current literature, gives an overview on the state of knowledge, and identifies research gaps. Current literature suggests that drone noise is substantially more annoying than road traffic or aircraft noise due to special acoustic characteristics such as pure tones and high-frequency broadband noise. A range of open questions remains to be tackled by future studies.

Most environmental epidemiology studies model health effects of noise by regressing on acoustic exposure metrics that are based on the concept of average energetic dose over longer time periods (i.e. the L_eq and related measures). Regarding noise effects on health and wellbeing, average measures often cannot satisfactorily predict annoyance and somatic health effects of noise, particularly sleep disturbances. It has been hypothesized that effects of noise can be better explained when also considering the variation of the level over time and the frequency distribution of event-related acoustic measures, such as for example, the maximum sound pressure level. However, it is unclear how this is best parametrized in a metric that is not correlated with the L_eq, but takes into account the frequency distribution of events and their emergence from background. In this paper, a calculation method is presented that produces a metric which reflects the intermittency of road, rail and aircraft noise exposure situations. The metric termed intermittency ratio (IR) expresses the proportion of the acoustical energy contribution in the total energetic dose that is created by individual noise events above a certain threshold. To calculate the metric, it is shown how to estimate the distribution of maximum pass-by levels from information on geometry (distance and angle), traffic flow (number and speed) and single-event pass-by levels per vehicle category. On the basis of noise maps that simultaneously visualize L_eq, as well as IR, the differences of both metrics are discussed.