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.

Epidemiological studies have inconsistently linked transportation noise and air pollution (AP) with diabetes risk. Most studies have considered single noise sources and/or AP, but none has investigated their mutually independent contributions to diabetes risk. We investigated 2631 participants of the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA), without diabetes in 2002 and without change of residence between 2002 and 2011. Using questionnaire and biomarker data, incident diabetes cases were identified in 2011. Noise and AP exposures in 2001 were assigned to participants’ residences (annual average road, railway or aircraft noise level during day-evening-night (Lden), total night number of noise events, intermittency ratio (temporal variation as proportion of event-based noise level over total noise level) and nitrogen dioxide (NO₂) levels. We applied mixed Poisson regression to estimate the relative risk (RR) of diabetes and their 95% confidence intervals (CI) in mutually-adjusted models. Diabetes incidence was 4.2%. Median [interquartile range (IQR)] road, railway, aircraft noise and NO₂ were 54 (10) dB, 32 (11) dB, 30 (12) dB and 21 (15) μg/m³, respectively. Lden road and aircraft were associated with incident diabetes (respective RR: 1.35; 95% CI: 1.02–1.78 and 1.86; 95% CI: 0.96–3.59 per IQR) independently of Lden railway and NO₂ (which were not associated with diabetes risk) in mutually adjusted models. We observed stronger effects of Lden road among participants reporting poor sleep quality or sleeping with open windows. Transportation noise may be more relevant than AP in the development of diabetes, potentially acting through noise-induced sleep disturbances.

The contribution of different transportation noise sources to metabolic disorders such as obesity remains understudied. We evaluated the associations of long-term exposure to road, railway and aircraft noise with measures of obesity and its subphenotypes using cross-sectional and longitudinal designs. We assessed 3796 participants from the population-based Swiss Cohort Study on Air Pollution and Lung and Heart Diseases (SAPALDIA), who attended the visits in 2001 (SAP2) and 2010/2011 (SAP3) and who were aged 29-72 at SAP2. At SAP2 we measured body mass index (BMI, kg/m2). At SAP3 we measured BMI, waist circumference (centimetres) and Kyle body Fat Index (%) and derived overweight, central and general obesity. Longitudinally for BMI, we derived change in BMI, incidence of overweight and obesity and a 3-category outcome combining the latter two. We assigned source-specific 5-year mean noise levels before visits and during follow-up at the most exposed dwelling façade (Lden, dB), using Swiss noise models for 2001 and 2011 and participants' residential history. Models were adjusted for relevant confounders, including traffic-related air pollution. Exposure to road traffic noise was significantly associated with all adiposity subphenotypes, cross-sectionally (at SAP3) [e.g. beta (95% CI) per 10 dB, BMI: 0.39 (0.18; 0.59); waist circumference: 0.93 (0.37; 1.50)], and with increased risk of obesity, longitudinally (e.g. RR = 1.25, 95% CI: 1.04; 1.51, per 10 dB in 5-year mean). Railway noise was significantly related to increased risk of overweight. In cross-sectional analyses, we further identified a stronger association between road traffic noise and BMI among participants with cardiovascular disease and an association between railway noise and BMI among participants reporting bad sleep. Associations were independent of the other noise sources, air pollution and robust to all adjustment sets. No associations were observed for aircraft noise. Long-term exposure to transportation noise, particularly road traffic noise, may increase the risk of obesity and could constitute a pathway towards cardiometabolic and other diseases.