A theoretical model for the oblique incidence sound absorption coefficient of thin woven fabrics backed by an air cavity is presented where the fabric is acoustically described by its specific ...airflow resistance and its surface mass density. The theoretical model is illustrated by an equivalent electrical circuit and validated in the case of normal sound incidence by experimental results obtained from impedance tube measurements on three fabric types. The influence of the surface mass density on the absorption coefficient is discussed and recommendations for practical applications are derived. Further, a simple formula to predict the specific airflow resistance of woven fabrics based on geometrical parameters is deduced. The normal incidence absorption coefficient and geometrical parameters of a set of 24 fabrics with a large range of interyarn porosities and specific airflow resistances were measured and used to validate the proposed geometry-based model to predict the absorption coefficient. Measured and estimated absorption coefficients show excellent agreement, with mean value and standard deviation of the differences of 0.03 ± 0.10. The model is therefore suitable for the design of new fabrics with an intended absorption coefficient.
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NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
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.
•Noise annoyance is associated with Lden of road, rail, and aircraft noise exposure.•The degree of intermittency of noise can explain differences in annoyance reactions.•Aircraft noise is more annoying than railway noise and road traffic noise.•We found no empirical basis for a “railway bonus” for noise regulation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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.
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.
•Long-term exposure to road traffic noise over time may increase the risk of obesity.•Cross-sectionally, it also relates to higher BMI, waist circumference and body fat.•Cross-sectionally, it also relates to general and central obesity and overweight.•Long-term exposure to railway noise might also relate to risk of overweight.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•We studied transportation noise exposure and annoyance with incidence of depression.•Annoyance associated with depression risk, independent of noise exposure.•Annoyance mediated the indirect effects ...of road traffic and aircraft noise.•In non-movers, there were cumulative noise exposure effects, with additive tendency.•Physical activity and daytime sleepiness moderated the annoyance effect.
Prospective evidence on the risk of depression in relation to transportation noise exposure and noise annoyance is limited and mixed. We aimed to investigate the associations of long-term exposure to source-specific transportation noise and noise annoyance with incidence of depression in the SAPALDIA (Swiss cohort study on air pollution and lung and heart diseases in adults) cohort.
We investigated 4,581 SAPALDIA participants without depression in the year 2001/2002. Corresponding one-year mean road, railway and aircraft day-evening-night noise (Lden) was calculated at the most exposed façade of the participants’ residential floors, and transportation noise annoyance was assessed on an 11-point scale. Incident cases of depression were identified in 2010/2011, and comprised participants reporting physician diagnosis, intake of antidepressant medication or having a short form-36 mental health score < 50. We used robust Poisson regressions to estimate the mutually adjusted relative risks (RR) and 95% confidence intervals (CI) of depression, independent of traffic-related air pollution and other potential confounders.
Incidence of depression was 11 cases per 1,000 person-years. In single exposure models, we observed positive but in part, statistically non-significant associations (per 10 dB) of road traffic Lden RR: 1.06 (0.93, 1.22) and aircraft Lden RR: 1.19 (0.93, 1.53), and (per 1-point difference) of noise annoyance RR: 1.05 (1.02, 1.08) with depression risk. In multi-exposure model, noise annoyance effect remained unchanged, with weaker effects of road traffic Lden (RR: 1.02 (0.89, 1.17) and aircraft Lden (RR: 1.17 (0.90, 1.50). However, there were statistically significant indirect effects of road traffic Lden (β: 0.02 (0.01, 0.03) and aircraft Lden β: 0.01 (0.002, 0.02) via noise annoyance. There were no associations with railway Lden in the single and multi-exposure models (RRboth models: 0.88 (0.75, 1.03). We made similar findings among 2,885 non-movers, where the effect modification and cumulative risks were more distinct. Noise annoyance effect in non-movers was stronger among the insufficiently active (RR: 1.09; 95%CI: 1.02, 1.17; pinteraction = 0.07) and those with daytime sleepiness RR: 1.07 (1.02, 1.12); pinteraction = 0.008. Cumulative risks of Lden in non-movers showed additive tendencies for the linear cumulative risk (RRper 10dB of combined sources: 1.31 (0.90, 1.91) and the categorical cumulative risk (RRtriple- vs. zero-source ≥45 dB: 2.29 (1.02, 5.14), and remained stable to noise annoyance.
Transportation noise level and noise annoyance may jointly and independently influence the risk of depression. Combined long-term exposures to noise level seems to be most detrimental, largely acting via annoyance. The moderation of noise annoyance effect by daytime sleepiness and physical activity further contribute to clarifying the involved mechanisms. More evidence is needed to confirm these findings for effective public health control of depression and noise exposure burden.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Transportation noise leads to sleep disturbance and to psychological and physiological sustained stress reactions, which could impact respiratory health. However, epidemiologic evidence on ...associations of objective transportation noise exposure and also perceived noise annoyance with respiratory morbidity is limited. We investigated independent associations of transportation noise exposure and noise annoyance with prevalent respiratory symptoms and incident asthma in adults.
Using 17,138 observations (from 7049 participants) from three SAPALDIA (Swiss Cohort Study on Lung and Heart Diseases in Adults) surveys, we assessed associations of transportation noise exposure and noise annoyance with prevalent respiratory symptoms, and with incident asthma (in 10,657 nested observations from 6377 participants). Annual day-evening-night transportation noise comprising road, railway and aircraft Lden (Transportation Lden) was calculated for the most exposed façade of participants' residence using Swiss noise models. Transportation noise annoyance was assessed using an 11-point scale, and participants reported respiratory symptoms and doctor-diagnosed asthma at each survey. We estimated associations with transportation Lden (as well as source-specific Lden) and noise annoyance, independent of air pollution and other potential confounders, using mutually-adjusted mixed logistic and Poisson models and applying random intercepts at the level of the participants.
Prevalent respiratory symptoms ranged from 5% (nocturnal dyspnoea) to 23% (regular cough/phlegm). Transportation noise annoyance, but not Lden, was independently associated with respiratory symptoms and current asthma in all participants, with odds ratios (OR) and 95% confidence intervals (CI) ranging between 1.03 (95%CI: 1.01, 1.06) and 1.07 (95% CI: 1.04, 1.11) per 1-point difference in noise annoyance. Both noise annoyance and Lden showed independent associations with asthma symptoms among asthmatics, especially in those reporting adult-onset asthma ORLden: 1.90 (95% CI: 1.25, 2.89) per 10 dB; p-value of interaction (adult-onset vs. childhood-onset): 0.03; ORnoise annoyance: 1.06 (95%CI: 0.97, 1.16) per 1-point difference; p-value of interaction: 0.06. No associations were found with incident asthma.
Transportation noise level and annoyance contributed to symptom exacerbation in adult asthma. This suggests both psychological and physiological noise reactions on the respiratory system, and could be relevant for asthma care. More studies are needed to better understand the effects of objective and perceived noise in asthma aetiology and overall respiratory health.
•We studied association of noise level and annoyance with adult respiratory morbidity.•Noise annoyance was associated with respiratory symptoms and current asthma.•Noise level was only associated with respiratory symptoms in asthmatic participants.•Noise level and annoyance were not associated with the development of asthma.•The results highlight the potential importance of perceived noise and noise annoyance on respiratory health.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Epidemiological research on transportation noise uses different exposure assessment strategies based on façade point estimates or regulatory noise maps. The degree of exposure measurement error and ...subsequent potentially biased risk estimates related to exposure definition is unclear. We aimed to evaluate associations between transportation noise exposure and myocardial infarction (MI) mortality considering: assumptions about residential floor, façade point selection (loudest, quietest, nearest), façade point vs. noise map estimates, and influence of averaging exposure at coarser spatial scales (e.g. in ecological health studies).
Lden from the façade points were assigned to >4 million eligible adults in the Swiss National Cohort for the best match residential floor (reference), middle floor, and first floor. For selected floors, the loudest and quietest exposed façades per dwelling, plus the nearest façade point to the residential geocode, were extracted. Exposure was also assigned from 10 × 10 m noise maps, using “buffers” from 50 to 500 m derived from the maps, and by aggregating the maps to larger areas. Associations between road traffic and railway noise and MI mortality were evaluated by multi-pollutant Cox regression models, adjusted for aircraft noise, NO2 and socio-demographic confounders, following individuals from 2000 to 2008. Bias was calculated to express differences compared to the reference.
Hazard ratios (HRs) for the best match residential floor were 1.05 (1.02–1.07) and 1.03 (1.01–1.05) per IQR (11.3 and 15.0 dB) for road traffic and railway noise, respectively. In most situations, comparing the alternative exposure definitions to this reference resulted in attenuated HRs. For example, assuming everyone resided on the middle or everyone on first floor introduced little bias (%Bias in excess risk: −1.9 to 4.4 road traffic and −4.4 to 10.7 railway noise). Using the noise grids generated a bias of approximately −26% for both sources. Averaging the maps at a coarser spatial scale led to bias from −19.4 to −105.1% for road traffic and 17.6 to −34.3% for railway noise and inflated the confidence intervals such that some HRs were no longer statistically significant.
Changes in spatial scale introduced more bias than changes in residential floor. Use of noise maps to represent residential exposure may underestimate noise-induced health effects, in particular for small-scale heterogeneously distributed road traffic noise in urban settings.
•Source-propagation models at façades are the gold standard for noise exposure.•Influence of assigning exposure in different ways was evaluated.•Exposure definition on health effects was more critical for road vs. rail noise.•Exposure at larger scales introduced more bias and attenuated health estimates.•Façade estimates or fine scale noise maps are recommended.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Epidemiological evidence indicates an association between transportation noise exposure and a higher risk of developing type 2 diabetes. Sleep disturbances are thought to be one of the mechanisms as ...it is well established that a few nights of short or poor sleep impair glucose tolerance and insulin sensitivity in healthy good sleepers.
The present study aimed to determine the extent to which exposure to nocturnal transportation noise affects glucose metabolism, and whether it is related to noise-induced sleep alterations.
Twenty-one young healthy volunteers (nine women) participated in a six-day laboratory study starting with a noise-free baseline night, then four nights sleeping with randomly-presented transportation noise scenarios (three road and one railway noise scenario) with identical average sound level of 45dB but differing in eventfulness and ending with a noise-free recovery night. Sleep was measured by polysomnography. Glucose tolerance and insulin sensitivity were measured after the baseline, the last noise night and the recovery nights with an oral glucose tolerance test using Matsuda and Stumvoll insulin sensitivity indexes. Eleven participants were assigned a less eventful noise scenario during the last noise night (LE-group), while the other ten had a more eventful noise scenario (ME-group). Baseline metabolic and sleep variables between the two intervention groups were compared using a non-parametric Mann-Whitney U test while mixed models were used for repeated measure analysis.
All participants had increased glucoseAUC (mean±SE, 14±2%, p<0.0001) and insulinAUC (55±10%, p<0.0001) after the last noise night compared to the baseline night. 2h-glucose level tended to increase only in the ME-group between baseline (5.1±0.22mmol·L−1) and the last noise night (6.1±0.39mmol·L−1, condition: p=0.001, interaction: p=0.08). Insulin sensitivity assessed with Matsuda and Stumvoll indexes respectively decreased by 7±8% (p=0.001) and 9±2% (p<0.0001) after four nights with transportation noise. Only participants in the LE-group showed beneficial effects of the noise-free recovery night on glucose regulation (relative change to baseline: glucoseAUC: 1±2%, p=1.0 for LE-group and 18±4%, p<0.0001 for ME-group; Stumvoll index: 3.2±2.6%, p=1.0 for LE-group and 11±2.5%, p=0.002 for ME-group). Sleep was mildly impaired with increased sleep latency of 8±2min (<0.0001) and more cortical arousals per hour of sleep (1.8±0.6arousals/h, p=0.01) during the last noise night compared to baseline. No significant associations between sleep measures and glucose tolerance and insulin sensitivity were found.
In line with epidemiological findings, sleeping four nights with transportation noise impaired glucose tolerance and insulin sensitivity. Based on the presented sound exposure, the eventfulness of the noise scenarios seems to play an important role for noise-induced alterations in glucose regulation. However, we could not confirm our hypothesis that transportation noise impairs glucose regulation via deterioration in sleep quality and quantity. Therefore, other factors, such as stress-related pathways, may need to be considered as potential triggers for noise-evoked glucose intolerance in future research.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
While the technique of auralization has been in use for quite some time in architectural acoustics, the application to environmental noise has been discovered only recently. With road traffic noise ...being the dominant noise source in most countries, particular interest lies in the synthesis of realistic pass-by sounds. This article describes an auralizator for pass-bys of accelerating passenger cars. The key element is a synthesizer that simulates the acoustical emission of different vehicles, driving on different surfaces, under different operating conditions. Audio signals for the emitted tire noise, as well as the propulsion noise are generated using spectral modeling synthesis, which gives complete control of the signal characteristics. The sound of propulsion is synthesized as a function of instantaneous engine speed, engine load and emission angle, whereas the sound of tires is created in dependence of vehicle speed and emission angle. The sound propagation is simulated by applying a series of time-variant digital filters. To obtain the corresponding steering parameters of the synthesizer, controlled experiments were carried out. The tire noise parameters were determined from coast-by measurements of passenger cars with idling engines. To obtain the propulsion noise parameters, measurements at different engine speeds, engine loads and emission angles were performed using a chassis dynamometer. The article shows how, from the measured data, the synthesizer parameters are calculated using audio signal processing.
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