Intermittency ratio: A metric reflecting short-term temporal variations of transportation noise exposure

Long-term exposure to transportation noise and diabetes mellitus mortality: a national cohort study and updated meta-analysis

BACKGROUND

Long-term exposure to transportation noise is related to cardio-metabolic diseases, with more recent evidence also showing associations with diabetes mellitus (DM) incidence. This study aimed to evaluate the association between transportation noise and DM mortality within the Swiss National Cohort.

METHODS

During 15 years of follow-up (2001-2015; 4.14 million adults), over 72,000 DM deaths were accrued. Source-specific noise was calculated at residential locations, considering moving history. Multi-exposure, time-varying Cox regression was used to derive hazard ratios (HR, and 95%-confidence intervals). Models included road traffic, railway and aircraft noise, air pollution, and individual and area-level covariates including socio-economic position. Analyses included exposure-response modelling, effect modification, and a subset analysis around airports. The main findings were integrated into meta-analyses with published studies on mortality and incidence (separately and combined).

RESULTS

HRs were 1.06 (1.05, 1.07), 1.02 (1.01, 1.03) and 1.01 (0.99, 1.02) per 10 dB day evening-night level (Lden) road traffic, railway and aircraft noise, respectively (adjusted model, including NO2). Splines suggested a threshold for road traffic noise (~ 46 dB Lden, well below the 53 dB Lden WHO guideline level), but not railway noise. Substituting for PM2.5, or including deaths with type 1 DM hardly changed the associations. HRs were higher for males compared to females, and in younger compared to older adults. Focusing only on type 1 DM showed an independent association with road traffic noise. Meta-analysis was only possible for road traffic noise in relation to mortality (1.08 [0.99, 1.18] per 10 dB, n = 4), with the point estimate broadly similar to that for incidence (1.07 [1.05, 1.09] per 10 dB, n = 10). Combining incidence and mortality studies indicated positive associations for each source, strongest for road traffic noise (1.07 [1.05, 1.08], 1.02 [1.01, 1.03], and 1.02 [1.00, 1.03] per 10 dB road traffic [n = 14], railway [n = 5] and aircraft noise [n = 5], respectively).

CONCLUSIONS

This study provides new evidence that transportation noise is associated with diabetes mortality. With the growing evidence and large disease burden, DM should be viewed as an important outcome in the noise and health discussion.

Managing Circadian Disruption due to Hospitalization: A Pilot Randomized Controlled Trial of the CircadianCare Inpatient Management System

The objective of the present study was to test the effects of an inpatient management system (CircadianCare) aimed at limiting the negative impact of hospitalization on sleep by enhancing circadian rhythmicity. Fifty inpatients were randomized to either CircadianCare (n = 25; 18 males, 62.4 ± 1.9 years) or standard of care (n = 25; 14 males, 64.5 ± 2.3 years). On admission, all underwent a full sleep-wake evaluation; they then completed daily sleep diaries and wore an actigraph for the whole length of hospitalization. On days 1 (T0), 7 (T1), and 14 (T2, if still hospitalized), salivary melatonin for dim light melatonin onset (DLMO) and 24-h skin temperature were recorded. In addition, environmental noise, temperature, and illuminance were monitored. Patients in the CircadianCare arm followed 1 of 3 schedules for light/dark, meal, and physical activity timings, based on their diurnal preference/habits. They wore short-wavelength-enriched light-emitting glasses for 45 min after awakening and short-wavelength light filter shades from 18:00 h until sleep onset. While the first, primary registered outcome (reduced sleep-onset latency on actigraphy or diary) was not met, based on sleep diaries, there was a trend (0.05 < p < 0.1) toward an advance in bedtime for CircadianCare compared to standard of care patients between T0 and T1. Similarly, DLMO time significantly advanced in the small group of patients for whom it could be computed on both occasions, with untreated ones starting from earlier baseline values. Patients sleeping near the window had significantly higher sleep efficiency, regardless of treatment arm. As noise fluctuation increased, so did the number of night awakenings, regardless of treatment arm. In conclusion, the CircadianCare management system showed positive results in terms of advancing sleep timing and the circadian rhythm of melatonin. Furthermore, our study identified a combination of environmental noise and lighting indices, which could be easily modulated to prevent hospitalization-related insomnia.

Advanced Noise Indicator Mapping Relying on a City Microphone Network

In this work, a methodology is presented for city-wide road traffic noise indicator mapping. The need for direct access to traffic data is bypassed by relying on street categorization and a city microphone network. The starting point for the deterministic modeling is a previously developed but simplified dynamic traffic model, the latter necessary to predict statistical and dynamic noise indicators and to estimate the number of noise events. The sound propagation module combines aspects of the CNOSSOS and QSIDE models. In the next step, a machine learning technique-an artificial neural network in this work-is used to weigh the outcomes of the deterministic predictions of various traffic parameter scenarios (linked to street categories) to approach the measured indicators from the microphone network. Application to the city of Barcelona showed that the differences between predictions and measurements typically lie within 2-3 dB, which should be positioned relative to the 3 dB variation in street-side measurements when microphone positioning relative to the façade is not fixed. The number of events is predicted with 30% accuracy. Indicators can be predicted as averages over day, evening and night periods, but also at an hourly scale; shorter time periods do not seem to negatively affect modeling accuracy. The current methodology opens the way to include a broad set of noise indicators in city-wide environmental noise impact assessment.

Suicide and Transportation Noise: A Prospective Cohort Study from Switzerland

BACKGROUND

Although plausible from a pathophysiological point of view, robust evidence for effects of transportation noise on mental health remains scarce. Meanwhile, psychiatric diseases are among the most prevalent noncommunicable diseases worldwide, and suicide as a mortality outcome highly connected to mental disorders presents a pressing public health issue. The aim of this study was to investigate the association between source-specific transportation noise, particulate matter (PM) air pollution, residential greenness, and suicide by means of a nationwide cohort study.

METHODS

Road traffic, railway and aircraft noise exposure as well as exposure to air pollution [PM with aerodynamic diameter ≤2.5μm (PM2.5)] and greenness [normalized difference vegetation index (NDVI)] were linked to 5.1 million adults (age 15 y and older) in the Swiss National Cohort, accounting for their address history. Mean noise exposure in 5-y periods was calculated. Individuals were followed for up to 15 y (2001-2015). Time-varying Cox regression models were applied to deaths by suicide (excluding assisted suicide). Models included all three noise sources, PM2.5, and NDVI plus individual and spatial covariates, including socioeconomic status. Effect modification by sex, age, socioeconomic indicators, and degree of urbanization was explored.

RESULTS

During the follow-up, there were 11,265 suicide deaths (10.4% poisoning, 33.3% hanging, 28.7% firearms, 14.7% falls). Road traffic and railway noise were associated with total suicides [hazard ratios: 1.040; 95% confidence interval (CI): 1.015, 1.065; and 1.022 (95% CI: 1.004, 1.041) per 10 dB day-evening-night level (Lden)], whereas for aircraft noise, a risk increase starting from 50 dB was masked by an inverse association in the very low exposure range (30-40 dB). Associations were stronger for females than males. The results were robust to adjustment for residential greenness and air pollution.

CONCLUSION

In this longitudinal, nationwide cohort study, we report a robust association between exposure to road traffic and railway noise and risk of death by suicide after adjusting for exposure to air pollution and greenness. These findings add to the growing body of evidence that mental health disorders may be related to chronic transportation noise exposure. https://doi.org/10.1289/EHP11587.

Spatial modelling and inequalities of environmental noise in Accra, Ghana

Noise pollution is a growing environmental health concern in rapidly urbanizing sub-Saharan African (SSA) cities. However, limited city-wide data constitutes a major barrier to investigating health impacts as well as implementing environmental policy in this growing population. As such, in this first of its kind study in West Africa, we measured, modelled and predicted environmental noise across the Greater Accra Metropolitan Area (GAMA) in Ghana, and evaluated inequalities in exposures by socioeconomic factors. Specifically, we measured environmental noise at 146 locations with weekly (n = 136 locations) and yearlong monitoring (n = 10 locations). We combined these data with geospatial and meteorological predictor variables to develop high-resolution land use regression (LUR) models to predict annual average noise levels (LAeq24hr, Lden, Lday, Lnight). The final LUR models were selected with a forward stepwise procedure and performance was evaluated with cross-validation. We spatially joined model predictions with national census data to estimate population levels of, and potential socioeconomic inequalities in, noise levels at the census enumeration-area level. Variables representing road-traffic and vegetation explained the most variation in noise levels at each site. Predicted day-evening-night (Lden) noise levels were highest in the city-center (Accra Metropolis) (median: 64.0 dBA) and near major roads (median: 68.5 dBA). In the Accra Metropolis, almost the entire population lived in areas where predicted Lden and night-time noise (Lnight) surpassed World Health Organization guidelines for road-traffic noise (Lden <53; and Lnight <45). The poorest areas in Accra also had significantly higher median Lden and Lnight compared with the wealthiest ones, with a difference of ∼5 dBA. The models can support environmental epidemiological studies, burden of disease assessments, and policies and interventions that address underlying causes of noise exposure inequalities within Accra.

Vehicular traffic noise modelling of urban area-a contouring and artificial neural network based approach

Road traffic vehicular noise is one of the main sources of environmental pollution in urban areas of India. Also, steadily increasing urbanization, industrialization, infrastructures around city condition causes health risks among the urban populations. In this study, we have explored noise descriptors (L₁₀, L₉₀, L_dn, LNI, TNI, NC), contour plotting and find the suitability of artificial neural networks (ANN) for the prediction of traffic noise all around the Dhanbad township in 15 monitoring stations. In order to develop the prediction model, measuring noise levels of five different hours, speed of vehicles, and traffic volume in every monitoring point have been studied and analyzed. Traffic volume, percent of heavy vehicles, speed, traffic flow, road gradient, pavement, road side carriageway distance factors were taken as input parameter, whereas L_Aeq as output parameter for formation of neural network architecture. As traffic flow is heterogenous which mainly contains 59%, two wheelers and different vehicle specifications with varying speeds also affect driving and honking behavior which constantly changing noise characteristics. From radial noise diagrams shown that average noise levels of all the stations beyond permissible limit and the highest noise levels were found at the speed of 50-55 km/h in both peak and non-peak hours. Noise descriptors clearly indicate high annoyance level in the study area. Artificial neural network with 7-7-5 formation has been developed and found as optimum due to its sum of square and overall relative error 0.858 and .029 in training and 0.458 and 0.862 in testing phase respectively. Comparative analysis between observed and predicted noise level shows very less deviation up to ± 0.6 dB(A) and the R² linear values are more than 0.9 in all five noise hours indicating the accuracy of model. Also, it can be concluded that ANN approach is much superior in prediction of traffic noise level to any other statistical method.

Exposure to road traffic noise and cognitive development in schoolchildren in Barcelona, Spain: A population-based cohort study

BACKGROUND

Road traffic noise is a prevalent and known health hazard. However, little is known yet about its effect on children's cognition. We aimed to study the association between exposure to road traffic noise and the development of working memory and attention in primary school children, considering school-outdoor and school-indoor annual average noise levels and noise fluctuation characteristics, as well as home-outdoor noise exposure.

METHODS AND FINDINGS

We followed up a population-based sample of 2,680 children aged 7 to 10 years from 38 schools in Barcelona (Catalonia, Spain) between January 2012 to March 2013. Children underwent computerised cognitive tests 4 times (n = 10,112), for working memory (2-back task, detectability), complex working memory (3-back task, detectability), and inattentiveness (Attention Network Task, hit reaction time standard error, in milliseconds). Road traffic noise was measured indoors and outdoors at schools, at the start of the school year, using standard protocols to obtain A-weighted equivalent sound pressure levels, i.e., annual average levels scaled to human hearing, for the daytime (daytime LAeq, in dB). We also derived fluctuation indicators out of the measurements (noise intermittency ratio, %; and number of noise events) and obtained individual estimated indoor noise levels (LAeq) correcting for classroom orientation and classroom change between years. Home-outdoor noise exposure at home (Lden, i.e., EU indicator for the 24-hour annual average levels) was estimated using Barcelona's noise map for year 2012, according to the European Noise Directive (2002). We used linear mixed models to evaluate the association between exposure to noise and cognitive development adjusting for age, sex, maternal education, socioeconomical vulnerability index at home, indoor or outdoor traffic-related air pollution (TRAP) for corresponding school models or outdoor nitrogen dioxide (NO2) for home models. Child and school were included as nested random effects. The median age (percentile 25, percentile 75) of children in visit 1 was 8.5 (7.8; 9.3) years, 49.9% were girls, and 50% of the schools were public. School-outdoor exposure to road traffic noise was associated with a slower development in working memory (2-back and 3-back) and greater inattentiveness over 1 year in children, both for the average noise level (e.g., ‒4.83 points [95% CI: ‒7.21, ‒2.45], p-value < 0.001, in 2-back detectability per 5 dB in street levels) and noise fluctuation (e.g., ‒4.38 [‒7.08, ‒1.67], p-value = 0.002, per 50 noise events at street level). Individual exposure to the road traffic average noise level in classrooms was only associated with inattentiveness (2.49 ms [0, 4.81], p-value = 0.050, per 5 dB), whereas indoor noise fluctuation was consistently associated with all outcomes. Home-outdoor noise exposure was not associated with the outcomes. Study limitations include a potential lack of generalizability (58% of mothers with university degree in our study versus 50% in the region) and the lack of past noise exposure assessment.

CONCLUSIONS

We observed that exposure to road traffic noise at school, but not at home, was associated with slower development of working memory, complex working memory, and attention in schoolchildren over 1 year. Associations with noise fluctuation indicators were more evident than with average noise levels in classrooms.

The Evaluation of Conventional, Electric and Hybrid Electric Passenger Car Pass-By Noise Annoyance Using Psychoacoustical Properties

Road traffic noise is one of the most prominent sources of urban noise pollution. Recently, as a result of the electrification of vehicles, lower noise levels are expected in urban areas at speeds below 50 km/h. The commonly used physical descriptor, the A-weighted sound pressure level, does not sufficiently characterize the perceived annoyance of either combustion engine or electric passenger car pass-by noises. Psychoacoustical descriptors are advantageous for characterization purposes. The objective of this study was to evaluate the perceived annoyance caused by the noise from internal combustion engine, electric, and hybrid passenger cars using psychoacoustical properties. To achieve this objective, the following steps were conducted. First, the binaurally recorded sounds of 40 cars from different brands with different motorization were presented to the subjects who indicated the intensity of their perceived annoyance on a quasi-continuous scale. Second, the signal and psychoacoustical properties of the recorded sounds were analyzed. Third, a new annoyance index was developed, based on annoyance judgments and signal and psychoacoustical properties, to characterize the annoyance caused by pass-by noises. One of the novel aspects of this study is the consideration of not only the pass-by sounds of the internal combustion engine passenger cars, but also the pass-by sounds of hybrid and electric passenger cars. An acceleration from idle to a target speed of 50 km/h was selected as a traffic pass-by situation, which differs from those considered in previous studies. The results of the study show that psychoacoustical properties, such as loudness, tonality, roughness, and fluctuation strength, are very useful to characterize the annoyance perception, which is caused by single passenger car pass-by sounds in the above mentioned traffic situation. The developed index, which is a weighted combination of chosen psychoacoustical properties, can be very useful for traffic planning and traffic noise prevention measures.

Long-term exposure to transportation noise and risk for atrial fibrillation: A Danish nationwide cohort study

BACKGROUND

Epidemiological studies have linked transportation noise and cardiovascular diseases, however, atrial fibrillation (AF) has received limited attention. We aimed to investigate the association between transportation noise and AF risk.

METHODS

Over the period 1990-2017 we estimated road and railway noise (L_den) at the most and least exposed façades for all residential addresses across Denmark. We estimated time-weighted mean noise exposure for 3.6 million individuals age ≥35 years. Of these, 269,756 incident cases of AF were identified with a mean follow-up of 13.0 years. Analyses were conducted using Cox proportional hazards models with adjustment for individual and area-level sociodemographic covariates and long-term residential air pollution.

RESULTS

A 10 dB higher 10-year mean road traffic noise at the most and least exposed façades were associated with incidence rate ratios (IRR) and 95% confidence intervals (CI) for AF of 1.006 (1.001-1.011) and 1.013 (1.007-1.019), respectively. After further adjustment for PM_2.5, the IRRs (CIs) were 1.000 (0.995-1.005) and 1.007 (1.000-1.013), respectively. For railway noise, the IRRs per 10 dB increase in 10-year mean exposure were 1.017 (1.007-1.026) and 1.035 (1.021-1.050) for the most and least exposed façades, respectively, and were slightly attenuated when adjusted for PM_2.5. Aircraft noise between 55 and 60 dB and ≥60 dB were associated with IRRs of 1.055 (0.996-1.116) and 1.036 (0.931-1.154), respectively, when compared to <45 dB.

CONCLUSION

Transportation noise seems to be associated with a small increase in AF risk, especially for exposure at the least exposed façade.

The association of road traffic noise with problem behaviour in adolescents: A cohort study

The findings of environmental noise exposure and behavioural disorders in children and adolescents are inconclusive, and longitudinal studies are scarce. We studied the response of behaviour and behavioural change within one year in a cohort of 886 adolescents in Switzerland aged 10-17 years in response to road traffic noise exposure. Participants filled in a comprehensive questionnaire at baseline and follow-up. It included the Strengths and Difficulties Questionnaire (SDQ), which measures self-rated positive and negative behaviours in five scales. We modelled road traffic noise for participants' most exposed facade at home and school addresses in various metrics (L_den, L_night, L_day, Intermittency Ratio and Number of events). We addressed missing data with multiple imputation and performed mixed linear cross-sectional analyses and longitudinal change score analyses. In cross-sectional analyses, peer relationship problems increased by 0.15 units (95%CI: 0.02, 0.27; scale range: 0-10) per 10 dB road traffic noise increase. In longitudinal analyses, increases in SDQ scales between baseline and follow-up were not related to noise exposure. This study suggests subtle associations between road traffic noise exposure and behaviour problems in adolescents, but longer follow-up times may be needed to observe longitudinal changes.

Assessment of Road Noise Pollution in Urban Residential Areas—A Case Study in Piteşti, Romania

The paper addresses the problem of urban road noise, in the context of the European legislative requirements regarding noise pollution. The second noise mapping in Pitesti city, revealed that despite the proposed action plan after the first noise mapping, the noise pollution increased instead of decreasing. Considering that the proposed measures were insufficient to control road noise in the conditions of the estimated increase in road traffic, the authors developed complex research to identify how the road noise level is determined by the way of regulation of road traffic at intersections of the residential zone. Thus, noise and traffic measurements are made at the main road intersections in the central part of the city, determining the most relevant noise indicators for the specifics of urban traffic and residential areas. The results obtained lead to the conclusion that roundabouts bring a reduction in noise pollution compared to traffic light intersections only if the speed of vehicles in the roundabout is predictable: on preselected lanes and with speed timing.

Road traffic noise impacts sleep continuity in suburban residents: Exposure-response quantification of noise-induced awakenings from vehicle pass-bys at night

Nocturnal traffic noise has been associated with adverse health outcomes in exposed residents. Precise quantification of traffic noise effects on sleep is thus of great importance. Here we establish an exposure-response relationship for the awakening probability due to intermittent road traffic noise in suburban residents. We conducted a field study in residential areas where road traffic was the dominant noise source, and noise events were attributable to separate vehicle pass-bys. Forty healthy participants underwent polysomnography for five consecutive nights at their homes. A total of 11,003 road traffic noises derived from simultaneous acoustic measurements at the sleepers' ears were included in an event-related analysis of awakenings. Logistic regression analysis revealed that the awakening probability due to road traffic noise increased with the maximum sound pressure level (SPL) and the maximum slope of the increasing SPL of a vehicle pass-by, as well as the age of the exposed individual. Compared to sleep stage 2, the awakening probability was higher in rapid eye movement sleep (REMS) and lower in slow wave sleep (SWS). The protective effect of both stage 2 and SWS against awakenings decreased with age, whereas no age-dependent change was observed for REMS. When adjusting for other contributing factors, the probability of a noise-induced awakening ranged from 0% at a maximum SPL of 27.1 dB(A) to 2.0% at 70 dB(A). Road traffic noise at night - even in suburban areas with moderate traffic density - negatively impacts residents' sleep continuity. Exposure-response quantification for traffic noise-induced awakenings may serve as a basis for noise protection efforts by regulators and policy makers.

Does the Macro-Temporal Pattern of Road Traffic Noise Affect Noise Annoyance and Cognitive Performance?

Noise annoyance is usually estimated based on time-averaged noise metrics. However, such metrics ignore other potentially important acoustic characteristics, in particular the macro-temporal pattern of sounds as constituted by quiet periods (noise breaks). Little is known to date about its effect on noise annoyance and cognitive performance, e.g., during work. This study investigated how the macro-temporal pattern of road traffic noise affects short-term noise annoyance and cognitive performance in an attention-based task. In two laboratory experiments, participants worked on the Stroop task, in which performance relies predominantly on attentional functions, while being exposed to different road traffic noise scenarios. These were systematically varied in macro-temporal pattern regarding break duration and distribution (regular, irregular), and played back with moderate L_Aeq of 42–45 dB(A). Noise annoyance ratings were collected after each scenario. Annoyance was found to vary with the macro-temporal pattern: It decreased with increasing total duration of quiet periods. Further, shorter but more regular breaks were somewhat less annoying than longer but irregular breaks. Since Stroop task performance did not systematically vary with different noise scenarios, differences in annoyance are not moderated by experiencing worsened performance but can be attributed to differences in the macro-temporal pattern of road traffic noise.

Effects of COVID-19 lockdown in Milan urban and Rome suburban acoustic environments: Anomalous noise events and intermittency ratio

The COVID-19 pandemic affected the acoustic environment worldwide, entailing relevant reductions of equivalent noise levels (L_Aeq) during this exceptional period. In the context of the LIFE+ DYNAMAP project, two wireless acoustic sensor networks were deployed in Milan and Rome. Taking advantage of the built-in identification of anomalous noise events (ANE) in the sensors, this work analyses the effects of the COVID-19 lockdown in both urban and suburban acoustic environments from January to June 2020, considering the distribution of ANEs and the intermittency ratio (IR) as an indicator of the impact of noise on population. The results show statistically significant increments of ANEs in Rome during the lockdown, mainly on weekends, and especially at night, despite the significant decrease in salient events. Differently, ANEs decrease during the lockdown in Milan, mostly at daytime, as a result of population confinement. Although the IR increases in several urban locations, most sensed locations show a relevant decrease in IR during the confinement, which represents a noteworthy reduction of the negative impact of noise in the population of both cities. During the post-lockdown period, all the scores start to return to those observed in the pre-lockdown, but still remaining higher than in 2019.

Natural and built environments and blood pressure of Alpine schoolchildren

BACKGROUND

Early life environments may influence children's blood pressure (BP), but evidence on the combined effects of natural and built environment exposures is scarce. The present study investigates the associations of natural and built environment indicators, traffic noise, and air pollution with BP in children living in Alpine valleys.

METHODS

In 2004/2005, 1251 school children (8-12 years old) were sampled for a cross-sectional survey in several Austrian and Italian mountain valleys. Children's mothers completed a questionnaire. The outcomes of interest were systolic and diastolic BP measured with a calibrated oscillometric device. Indicators of land cover assigned to the residential and school coordinates within 100 and 1000 m included normalized difference vegetation index (NDVI), tree canopy cover, and a broader naturalness indicator titled distance to nature (D2N). The presence of a home garden was also measured via self-report. Imperviousness density served as a proxy for the built environment. Residential air pollution (NO₂) and noise (L_den) from traffic were calculated using bespoke modeling. NO₂, L_den, physical activity, and body mass index (BMI) were treated as mediating pathways.

RESULTS

Higher NDVI and tree cover levels in residential and school surroundings and home gardens were consistently associated with lower BP. The built environment was associated with higher BP. Counterintuitive inverse associations between NO₂ and L_den and BP were also found. Structural equation modeling showed that higher levels of greenspace and presence of a home garden were weakly associated with more outdoor play spaces, and in turn with lower BMI, and ultimately with lower BP.

CONCLUSIONS

Exposure to natural environments may help maintain normal BP in children, while built environment may increase children's BP. Outdoor play and less adiposity in greener areas may mediate some of these associations. Evidence on air pollution and noise remains controversial and difficult to explain.

WASN-Based Spectro-Temporal Analysis and Clustering of Road Traffic Noise in Urban and Suburban Areas

Environmental noise has become one of the principal health risks for urban dwellers and road traffic noise (RTN) is considered to be the main source of these adverse effects. To address this problem, strategic noise maps and corresponding action plans have been developed throughout Europe in recent years in response to the European Noise Directive 2002/49/EC (END), especially in populated cities. Recently, wireless acoustic sensor networks (WASNs) have started to serve as an alternative to static noise maps to monitor urban areas by gathering environmental noise data in real time. Several studies have analysed and categorized the different acoustic environments described in the END (e.g., traffic, industrial, leisure, etc.). However, most of them have only considered the dynamic evolution of the A-weighted equivalent noise levels LAeq over different periods of time. In order to focus on the analysis of RTN solely, this paper introduces a clustering methodology to analyse and group spectro-temporal profiles of RTN collected simultaneously across an area of interest. The experiments were conducted on two acoustic databases collected during a weekday and a weekend day through WASNs deployed in the pilot areas of the LIFE+ DYNAMAP project. The results obtained show that the clustering of RTN, based on its spectro-temporal patterns, yields different solutions on weekdays and at weekends in both environments, being larger than those found in the suburban environment and lower than the number of clusters in the urban scenario.

Transportation noise exposure and cardiovascular mortality: 15-years of follow-up in a nationwide prospective cohort in Switzerland

BACKGROUND

Death from cardiovascular diseases (CVD) has been associated with transportation noise. This nationwide cohort, with state-of-the-art exposure assessment, evaluates these associations by noise source.

METHODS

Road traffic, railway and aircraft noise for 2001 and 2011 were linked to 4.1 million adults in the Swiss National Cohort, accounting for address history. Mean noise exposure in 5-year periods was calculated. Time-varying Cox regression models, with age as timescale, were applied to all and cause-specific cardiovascular causes of death. Models included all three noise sources plus PM_2.5, adjusted for individual and spatial covariates. Nighttime noise events for all sources combined (expressed as intermittency ratio or number of events) were considered in sensitivity analyses. Absolute excess risk was calculated by multiplying deaths/100,000 person-years by the excess risk (hazard ratio-1) within each age/sex group.

RESULTS

During a 15-year follow-up, there were 277,506 CVD and 34,200 myocardial infarction (MI) deaths. Associations (hazard ratio; 95%-CIs) for road traffic, railway and aircraft noise and CVD mortality were 1.029 (1.024-1.034), 1.013 (1.010-1.017), and 1.003 (0.996-1.010) per 10 dB L_den, respectively. Associations for MI mortality were a respective 1.043 (1.029-1.058), 1.020 (1.010-1.030) and 1.040 (1.020-1.060) per 10 dB L_den. Blood pressure-related, ischemic heart disease, and all stroke mortality were significantly associated with road traffic and railway noise, while ischemic stroke mortality was associated with aircraft noise. Associations were mostly linear, often starting below 40 dB L_den for road traffic and railway noise. Higher levels of noise intermittency were also independently associated with each outcome. While the absolute number of deaths attributed to noise increased with age, the hazard ratios declined with age. Relative and absolute risk was higher in males compared to females.

CONCLUSION

Independent of air pollution, transportation noise exposure is associated with all and cause-specific CVD mortality, with effects starting below current guideline limits.

Calculation of the physiologically developed nighttime noise index from existing noise indices

Background:

The effects of noise on sleep and health have been evaluated in earlier studies using noise indices chosen on the basis of practical considerations and not on the physiologic mechanisms of sleep disturbance due to noise exposure. We investigated the neurophysiologic mechanisms of sleep and found that the arithmetic mean of the sound levels above a threshold () may be used effectively to evaluate the effects of nighttime noise exposure. However, the efficacy of using has only been confirmed in a specific setting; therefore, the reliability of in other situations should be investigated by applying it in epidemiologic studies. In this study, we aimed to obtain an alternative equation for calculating from existing noise indices, given that detailed information on fluctuations in sound levels, needed to calculate according to the definition, is not readily available.

Materials and Methods:

We examined statistical relationships among noise indices namely , the number of noise events above 60 and 70 dB (N₆₀ and N₇₀), and the night equivalent sound level (L_night). The study area was around the Kadena military airfield, where the sound levels were recorded at noise monitoring stations.

Results:

showed a very strong correlation with N₆₀ and N₇₀ but not with L_night. Among regression equations, an equation representing N₆₀ and the interaction between N₆₀ and L_night, which is equivalent to the product of N₆₀ and a linear expression of L_night, showed the highest prediction capability.

Conclusion:

We obtained a regression equation to calculate from N₆₀ and L_night. Although this alternative equation for is only applicable for military aircraft noise, it will aid the re-analysis of existing epidemiologic studies as well as further investigations on the relationship between noise exposure and health effects.

Optimized Sensors Network and Dynamical Maps for Monitoring Traffic Noise in a Large Urban Zone

We review a Dynamap European Life project whose main scope was the design, commissioning, and actual implementation of “real-time” acoustic maps in a district of the city of Milan (District 9, or Z9, composed of about 2000 road stretches), by employing a small number of noise monitoring stations within the urban zone. Dynamap is based on the idea of finding suitable sets of roads displaying similar daily traffic noise behavior, so that one can group them together into single dynamical noise maps. The Dynamap sensor network has been built upon twenty-four monitoring stations, which have been permanently installed in appropriate locations within the pilot zone Z9, by associating four sensors to each one of the six group of roads considered. In order to decide which road stretches belong to a group, a non-acoustic parameter is used, which is obtained from a traffic flow model of the city, developed and tested over the years by the “Enviroment, Mobility and Territory Agency” of Milan (EMTA). The fundamental predictive equation of Dynamap, for the local equivalent noise level at a given site, can be built by using real-time data provided by the monitoring sensors. In addition, the corresponding contributions of six static traffic noise maps, associated with the six group of roads, are required. The static noise maps can be calculated from the Cadna noise model, based on EMTA road traffic data referred to the ‘rush-hour’ (8:00–9:00 a.m.), when the road traffic flow is maximum and the model most accurate. A further analysis of road traffic noise measurements, performed over the whole city of Milan, has provided a more accurate description of road traffic noise behavior by using a clustering approach. It is found that essentially just two mean cluster hourly noise profiles are sufficient to represent the noise profile at any site location within the zone. In order words, one can use the 24 monitoring stations data to estimate the local noise variations at a single site in real time. The different steps in the construction of the network are described in detail, and several validation tests are presented in support of the Dynamap performance, leading to an overall error of about 3 dB. The present work ends with a discussion of how to improve the design of the network further, based on the calculation of the cross-correlations between monitoring stations’ noise data.

Methods for Noise Event Detection and Assessment of the Sonic Environment by the Harmonica Index

Noise annoyance depends not only on sound energy, but also on other features, such as those in its spectrum (e.g., low frequency and/or tonal components), and, over time, amplitude fluctuations, such as those observed in road, rail, or aircraft noise passages. The larger these fluctuations, the more annoying a sound is generally perceived. Many algorithms have been implemented to quantify these fluctuations and identify noise events, either by looking at transients in the sound level time history, such as exceedances above a fixed or time adaptive threshold, or focusing on the hearing perception process of such events. In this paper, four criteria to detect sound were applied to the acoustic monitoring data collected in two urban areas, namely Andorra la Vella, Principality of Andorra, and Milan, Italy. At each site, the 1 s A-weighted short LAeq,1s time history, 10 min long, was available for each hour from 8:00 a.m. to 7:00 p.m. The resulting 92-time histories cover a reasonable range of urban environmental noise time patterns. The considered criteria to detect noise events are based on: (i) noise levels exceeding by +3 dB the continuous equivalent level LAeqT referred to the measurement time (T), criteria used in the definition of the Intermittency Ratio (IR) to detect noise events; (ii) noise levels exceeding by +3 dB the running continuous equivalent noise level; (iii) noise levels exceeding by +10 dB the 50th noise level percentile; (iv) progressive positive increments of noise levels greater than 10 dB from the event start time. Algorithms (iii) and (iv) appear suitable for notice-event detection; that is, those that (for their features) are clearly perceived and potentially annoy exposed people. The noise events detected by the above four algorithms were also evaluated by the available anomalous noise event detection (ANED) procedure to classify them as produced by road traffic noise or something else. Moreover, the assessment of the sonic environment by the Harmonica index was correlated with the single event level (SEL) of each event detected by the four algorithms. The threshold value of 8 for the Harmonica index, separating the “noisy” from the “very noisy” environments, corresponds to lower SEL levels for notice-events as identified by (iii) and (iv) algorithms (about 88–89 dB(A)) against those identified by (i) and (ii) criteria (92 dB(A)).

The influence of a signal's time structure on the perceived noise annoyance of road traffic noise

PURPOSE

Road traffic noise is the most common source of noise in modern cities. The noise indicators used to manage noise do not take into account its temporal structure. However, in cities the traffic flow varies during the day, peaking due to congestion and more fluent periods. In this research we sought to analyze how people (giving answers on a numerical ICBEN scale) perceive noise stimuli with the same L_AeqT values but different time structures (more/less noise events, different amplitude envelopes).

METHODS

31 people with normal hearing took part in an experiment conducted in an anechoic chamber. Participants listened to 18 different noise recordings and rated each of them using the numerical ICBEN scale regarding noise annoyance.

RESULTS

The results showed that only sound level was a statistically significant factor. However, based on people's remarks about noise, we can also say that the more intermittent the noise is, the more negative feelings it evokes in people.

CONCLUSIONS

Time structure does not have a significant influence on people's judgments about noise annoyance. However, people tend to have a preference for a steady noise rather than an intermittent one.

A community noise survey in Southwest Detroit and the value of supplemental metrics for truck noise

Noise exposure can affect sleep, health and cognitive performance, and it disproportionately affects communities of color. This study has the objective of evaluating both conventional and supplemental noise metrics in a community noise survey examining Southwest Detroit, Michigan, a densely populated and industrialized area with extensive truck traffic on residential streets. Sound pressure level (SPL) monitors were deployed at 21 residential sites within 900 m of a major interstate highway. With assistance from youth volunteers, continuous SPL measurements were obtained for 1.5-7 days at each site, and short-term vehicle counts on local roads were recorded. We calculated conventional noise metrics, including the day-evening-night average sound level L_DEN and the 90th percentile 1-hr maximum L₁₀(h), and evaluated the effect of distance from highways, traffic volume, time-of-day, and other factors. Supplemental metrics potentially appropriate for intermittent traffic noise were calculated, including fraction of time over specific SPL thresholds using a new metric called F_DEN, which is the fraction of time over 60, 65 and 70 dB during night, evening and daytime periods, respectively, and a peak noise metric called L_2P(h), which utilizes the 98th percentile SPL within time blocks to increase robustness. The conventional metrics indicated five sites that exceeded 70 dB, and the highest noise levels were found within ~50 m of truck routes, arterials and freeway ramps. The estimated impact of truck traffic ranged up to 17 dB for hourly averages and to 33 dB for 1-s peaks. The conventional metrics did not always capture short-term noise exposures, which may be especially important to annoyance and sleep issues. In addition to showing widespread exposure to traffic noise in the study community that warrants consideration of noise abatement strategies, the study demonstrates the benefits of supplemental noise metrics and community engagement in noise assessment.

Space-time characterization of community noise and sound sources in Accra, Ghana

Urban noise pollution is an emerging public health concern in growing cities in sub-Saharan Africa (SSA), but the sound environment in SSA cities is understudied. We leveraged a large-scale measurement campaign to characterize the spatial and temporal patterns of measured sound levels and sound sources in Accra, Ghana. We measured sound levels and recorded audio clips at 146 representative locations, involving 7-days (136 locations) and 1-year measurements between 2019 and 2020. We calculated metrics of noise levels and intermittency and analyzed audio recordings using a pre-trained neural network to identify sources. Commercial, business, and industrial areas and areas near major roads had the highest median daily sound levels (LAeq_24hr: 69 dBA and 72 dBA) and the lowest percentage of intermittent sound; the vice-versa was found for peri urban areas. Road-transport sounds dominated the overall sound environment but mixtures of other sound sources, including animals, human speech, and outdoor music, dominated in various locations and at different times. Environmental noise levels in Accra exceeded both international and national health-based guidelines. Detailed information on the acoustical environmental quality (including sound levels and types) in Accra may guide environmental policy formulation and evaluation to improve the health of urban residents.

The impact of nocturnal road traffic noise, bedroom window orientation, and work-related stress on subjective sleep quality: results of a cross-sectional study among working women

Objective

To examine the effect of work-related stress and road noise exposure on self-rated sleep and potential additive interaction effects.

Methods

Sleep and predictor variables were surveyed within two subsamples with 2191 and 1764 working women in a cross-sectional study. Sleep was assessed using a single question on general sleep quality and four questions on specific sleep problems and subsequently dichotomized (poor sleep vs. no poor sleep). Work-related stress was operationalized by job strain and effort-reward imbalance. Nocturnal exposure to road traffic noise was assessed as (a) the orientation of the bedroom window to a quiet façade vs. a low-, medium- or high-trafficked street and (b) energy-equivalent sound pressure levels for night-time modelled at the most exposed façade (L_night). We distinguished between low (< 45 dB(A)), medium (45–50 dB(A)) and high exposure (> 50 dB(A)).

Results

Poor sleep was associated with job strain and effort-reward imbalance. The prevalence of poor sleep did not increase with increasing L_night, but bedroom window orientation showed a non-significant trend. A quiet façade had a protective effect on sleep in each L_night category. We found a non-significant trend for an additive interaction between bedroom window orientation and job strain.

Conclusion

Noise levels modelled for the most exposed façade likely overestimate the actual exposure and thus may not be a precise predictor of poor sleep. Bedroom window orientation seems more relevant. Potential additive interaction effects between bedroom window orientation and job strain should be considered when interpreting epidemiological study results on noise-induced sleep disturbances.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00420-021-01696-w.

A Psychoacoustic Approach to Building Knowledge about Human Response to Noise of Unmanned Aerial Vehicles

We are on the cusp of a revolution in the aviation sector, driven by the significant progress in electric power and battery technologies, and autonomous systems. Several industry leaders and governmental agencies are currently investigating the use of Unmanned Aerial Vehicles (UAVs), or "drones" as commonly known, for an ever-growing number of applications-from blue light services to parcel delivery and urban mobility. Undoubtedly, the operation of UAVs will lead to noise exposure, which has the potential to become a significant public health issue. This paper first describes the main acoustic and operational characteristics of UAVs, as an unconventional noise source compared to conventional civil aircraft. Gaps in the literature and the regulations on the noise metrics and acceptable noise levels are identified and discussed. The state-of-the-art evidence on human response to aircraft and other environmental noise sources is reviewed and its application for UAVs discussed. A methodological framework is proposed for building psychoacoustic knowledge, to inform systems and operations development to limit the noise impact on communities.

Development of a new night-time noise index: Integration of neurophysiological theory and epidemiological findings

Background:

The effects of environmental noise on sleep are of great interest to public health. Numerous studies have been conducted to investigate these effects; however, these previous studies applied existing sound-level statistics that were not based on neurophysiology.

Aims:

This study aimed to develop a new night-time noise index based on neurophysiology and epidemiology.

Methods:

First, we derived a formula for predicting the noise effects on sleep based on a neurophysiological model of brainstem sleep regulation, where awakening was associated with greater electrical potentials in the brainstem. Second, we investigated the noise effects on sleep using the results of an epidemiological study conducted in the vicinity of the Kadena military airfield in Okinawa, Japan. Thirty volunteers participated in the study. Vibrations of whole-body movements were recorded using sheet-shaped sleep monitors for 26 consecutive nights. The onset of motility, which was defined by monitor vibrations, was used to index awakening reactions.

Results:

Our statistical model could properly predict the fluctuating risk of motility onset. The new index, which is the mean of the sound level above 60 dB, can be successfully used, irrespective of the duration of noise exposure. Additionally, it out-performed existing event-related noise indices.

Conclusions:

We derived a new night-time noise index for evaluating the noise effects on sleep. To our knowledge, this is the first study to explain the noise effects on sleep with the consideration of neurophysiology and epidemiology.

Transportation noise and gestational diabetes mellitus: A nationwide cohort study from Denmark

BACKGROUND

Few studies have investigated whether road traffic noise is associated with gestational diabetes mellitus (GDM), and have yielded inconsistent findings. We aimed to investigate whether maternal exposure to residential transportation noise, before and during pregnancy, was associated with GDM in a nationwide cohort.

METHODS

From the Danish population (2004-2017) we identified 629,254 pregnancies using the Danish Medical Birth Register. By linkage with the National Patient Registry, we identified 15,973 pregnancies complicated by GDM. Road traffic and railway noise (L_den) at the most and least exposed façades for all residential addresses from five years before pregnancy until birth were estimated for all. Analyses were conducted using generalized estimating equation models with adjustment for various individual and area-level sociodemographic covariates gathered from Danish registries, as well as green space and air pollution (PM_2.5) estimated for all addresses.

RESULTS

We found no positive associations between road traffic noise at either façade and GDM. For railway noise, a 10 dB increase in railway noise at the most and least exposed façades during the first trimester was associated with GDM, with an odds ratio (OR) of 1.06 (95% confidence interval (CI): 1.03-1.10) and 1.07 (95% CI: 1.02-1.13), respectively. We found indications of higher odds of GDM among women exposed to both high road traffic and railway noise at the least exposed facade during the first trimester (OR: 1.24; 95% CI: 1.07-1.44).

CONCLUSION

In conclusion, this nationwide study suggests that railway noise but not road traffic noise might be associated with GDM.

The impact of aircraft noise on vascular and cardiac function in relation to noise event number: a randomized trial

Aims

Nighttime aircraft noise exposure has been associated with increased risk of hypertension and myocardial infarction, mechanistically linked to sleep disturbance, stress, and endothelial dysfunction. It is unclear, whether the most widely used metric to determine noise exposure, equivalent continuous sound level (L_eq), is an adequate indicator of the cardiovascular impact induced by different noise patterns.

Methods and results

In a randomized crossover study, we exposed 70 individuals with established cardiovascular disease or increased cardiovascular risk to two aircraft noise scenarios and one control scenario. Polygraphic recordings, echocardiography, and flow-mediated dilation (FMD) were determined for three study nights. The noise patterns consisted of 60 (Noise60) and 120 (Noise120) noise events, respectively, but with comparable L_eq, corresponding to a mean value of 45 dB. Mean value of noise during control nights was 37 dB. During the control night, FMD was 10.02 ± 3.75%, compared to 7.27 ± 3.21% for Noise60 nights and 7.21 ± 3.58% for Noise120 nights (P < 0.001). Sleep quality was impaired after noise exposure in both noise scenario nights (P < 0.001). Serial echocardiographic assessment demonstrated an increase in the E/E′ ratio, a measure of diastolic function, within the three exposure nights, with a ratio of 6.83 ± 2.26 for the control night, 7.21 ± 2.33 for Noise60 and 7.83 ± 3.07 for Noise120 (P = 0.043).

Conclusions

Nighttime exposure to aircraft noise with similar L_eq, but different number of noise events, results in a comparable worsening of vascular function. Adverse effects of nighttime aircraft noise exposure on cardiac function (diastolic dysfunction) seemed stronger the higher number of noise events.

BCNDataset: Description and Analysis of an Annotated Night Urban Leisure Sound Dataset

Acoustic pollution has been associated with adverse effects on the health and life expectancy of people, especially when noise exposure happens during the nighttime. With over half of the world population living in urban areas, acoustic pollution is an important concern for city administrators, especially those focused on transportation and leisure noise. Advances in sensor and network technologies made the deployment of Wireless Acoustic Sensor Networks (WASN) possible in cities, which, combined with artificial intelligence (AI), can enable smart services for their citizens. However, the creation of such services often requires structured environmental audio databases to train AI algorithms. This paper reports on an environmental audio dataset of 363 min and 53 s created in a lively area of the Barcelona city center, which targeted traffic and leisure events. This dataset, which is free and publicly available, can provide researchers with real-world acoustic data to help the development and testing of sound monitoring solutions for urban environments.

A systematic analysis of mutual effects of transportation noise and air pollution exposure on myocardial infarction mortality: a nationwide cohort study in Switzerland

AIMS

The present study aimed to disentangle the risk of the three major transportation noise sources-road, railway, and aircraft traffic-and the air pollutants NO2 and PM2.5 on myocardial infarction (MI) mortality in Switzerland based on high quality/fine resolution exposure modelling.

METHODS AND RESULTS

We modelled long-term exposure to outdoor road traffic, railway, and aircraft noise levels, as well as NO2 and PM2.5 concentration for each address of the 4.40 million adults (>30 years) in the Swiss National Cohort (SNC). We investigated the association between transportation noise/air pollution exposure and death due to MI during the follow-up period 2000-08, by adjusting noise [Lden(Road), Lden(Railway), and Lden(Air)] estimates for NO2 and/or PM2.5 and vice versa by multipollutant Cox regression models considering potential confounders. Adjusting noise risk estimates of MI for NO2 and/or PM2.5 did not change the hazard ratios (HRs) per 10 dB increase in road traffic (without air pollution: 1.032, 95% CI: 1.014-1.051, adjusted for NO2 and PM2.5: 1.034, 95% CI: 1.014-1.055), railway traffic (1.020, 95% CI: 1.007-1.033 vs. 1.020, 95% CI: 1.007-1.033), and aircraft traffic noise (1.025, 95% CI: 1.006-1.045 vs. 1.025, 95% CI: 1.005-1.046). Conversely, noise adjusted HRs for air pollutants were lower than corresponding estimates without noise adjustment. Hazard ratio per 10 μg/m³ increase with and without noise adjustment were 1.024 (1.005-1.043) vs. 0.990 (0.965-1.016) for NO2 and 1.054 (1.013-1.093) vs. 1.019 (0.971-1.071) for PM2.5.

CONCLUSION

Our study suggests that transportation noise is associated with MI mortality, independent from air pollution. Air pollution studies not adequately adjusting for transportation noise exposure may overestimate the cardiovascular disease burden of air pollution.

Traffic Noise and Mental Health: A Systematic Review and Meta-Analysis

Recent evidence suggests that traffic noise may negatively impact mental health. However, existing systematic reviews provide an incomplete overview of the effects of all traffic noise sources on mental health. We conducted a systematic literature search and summarized the evidence for road, railway, or aircraft noise-related risks of depression, anxiety, cognitive decline, and dementia among adults. We included 31 studies (26 on depression and/or anxiety disorders, 5 on dementia). The meta-analysis of five aircraft noise studies found that depression risk increased significantly by 12% per 10 dB L_DEN (Effect Size = 1.12, 95% CI 1.02–1.23). The meta-analyses of road (11 studies) and railway traffic noise (3 studies) indicated 2–3% (not statistically significant) increases in depression risk per 10 dB L_DEN. Results for road traffic noise related anxiety were similar. We did not find enough studies to meta-analyze anxiety and railway or aircraft noise, and dementia/ cognitive impairment and any traffic noise. In conclusion, aircraft noise exposure increases the risk for depression. Otherwise, we did not detect statistically significant risk increases due to road and railway traffic noise or for anxiety. More research on the association of cognitive disorders and traffic noise is required. Public policies to reduce environmental traffic noise might not only increase wellness (by reducing noise-induced annoyance), but might contribute to the prevention of depression and anxiety disorders.

High-resolution spatiotemporal measurement of air and environmental noise pollution in Sub-Saharan African cities: Pathways to Equitable Health Cities Study protocol for Accra, Ghana

INTRODUCTION

Air and noise pollution are emerging environmental health hazards in African cities, with potentially complex spatial and temporal patterns. Limited local data are a barrier to the formulation and evaluation of policies to reduce air and noise pollution.

METHODS AND ANALYSIS

We designed a year-long measurement campaign to characterise air and noise pollution and their sources at high-resolution within the Greater Accra Metropolitan Area (GAMA), Ghana. Our design uses a combination of fixed (year-long, n=10) and rotating (week-long, n =~130) sites, selected to represent a range of land uses and source influences (eg, background, road traffic, commercial, industrial and residential areas, and various neighbourhood socioeconomic classes). We will collect data on fine particulate matter (PM_2.5), nitrogen oxides (NO_x), weather variables, sound (noise level and audio) along with street-level time-lapse images. We deploy low-cost, low-power, lightweight monitoring devices that are robust, socially unobtrusive, and able to function in Sub-Saharan African (SSA) climate. We will use state-of-the-art methods, including spatial statistics, deep/machine learning, and processed-based emissions modelling, to capture highly resolved temporal and spatial variations in pollution levels across the GAMA and to identify their potential sources. This protocol can serve as a prototype for other SSA cities.

ETHICS AND DISSEMINATION

This environmental study was deemed exempt from full ethics review at Imperial College London and the University of Massachusetts Amherst; it was approved by the University of Ghana Ethics Committee (ECH 149/18-19). This protocol is designed to be implementable in SSA cities to map environmental pollution to inform urban planning decisions to reduce health harming exposures to air and noise pollution. It will be disseminated through local stakeholder engagement (public and private sectors), peer-reviewed publications, contribution to policy documents, media, and conference presentations.

A Taxonomy Proposal for the Assessment of the Changes in Soundscape Resulting from the COVID-19 Lockdown

Many countries around the world have chosen lockdown and restrictions on people's mobility as the main strategies to combat the COVID-19 pandemic. These actions have significantly affected environmental noise and modified urban soundscapes, opening up an unprecedented opportunity for research in the field. In order to enable these investigations to be carried out in a more harmonized and consistent manner, this paper makes a proposal for a set of indicators that will enable to address the challenge from a number of different approaches. It proposes a minimum set of basic energetic indicators, and the taxonomy that will allow their communication and reporting. In addition, an extended set of descriptors is outlined which better enables the application of more novel approaches to the evaluation of the effect of this new soundscape on people's subjective perception.

A Taxonomy Proposal for the Assessment of the Changes in Soundscape Resulting from the COVID-19 Lockdown

Many countries around the world have chosen lockdown and restrictions on people's mobility as the main strategies to combat the COVID-19 pandemic. These actions have significantly affected environmental noise and modified urban soundscapes, opening up an unprecedented opportunity for research in the field. In order to enable these investigations to be carried out in a more harmonized and consistent manner, this paper makes a proposal for a set of indicators that will enable to address the challenge from a number of different approaches. It proposes a minimum set of basic energetic indicators, and the taxonomy that will allow their communication and reporting. In addition, an extended set of descriptors is outlined which better enables the application of more novel approaches to the evaluation of the effect of this new soundscape on people's subjective perception.

Individual Aircraft Noise Exposure Assessment for a Case-Crossover Study in Switzerland

Accurate exposure assessment is essential in environmental epidemiological studies. This is especially true for aircraft noise, which is characterized by a high spatial and temporal variation. We propose a method to assess individual aircraft noise exposure for a case-crossover study investigating the acute effects of aircraft noise on cardiovascular deaths. We identified all cases of cardiovascular death (24,886) occurring near Zürich airport, Switzerland, over fifteen years from the Swiss National Cohort. Outdoor noise exposure at the home address was calculated for the night preceding death and control nights using flight operations information from Zürich airport and noise footprints calculated for major aircraft types and air routes. We estimated three different noise metrics: mean sound pressure level (L_Aeq), maximum sound pressure level (L_Amax), and number above threshold 55 dB (NAT₅₅) for different nighttime windows. Average nighttime aircraft noise levels were 45.2 dB, 64.6 dB, and 18.5 for L_Aeq, L_Amax, and NAT₅₅ respectively. In this paper, we present a method to estimate individual aircraft noise exposure with high spatio-temporal resolution and a flexible choice of exposure events and metrics. This exposure assessment will be used in a case-crossover study investigating the acute effects of noise on health.

Classification of Urban Road Traffic Noise based on Sound Energy and Eventfulness Indicators

Noise energetic indicators, like Lden, show good correlations with long term annoyance, but should be supplemented by other parameters describing the sound fluctuations, which are very common in urban areas and negatively impact noise annoyance. Thus, in this paper, the hourly values of continuous equivalent level LAeqh and the intermittency ratio (IR) were both considered to describe the urban road traffic noise, monitored in 90 sites in the city of Milan and covering different types of road, from motorways to local roads. The noise data have been processed by clustering methods to detect similarities and to figure out a criterion to classify the urban sites taking into account both equivalent noise levels and road traffic noise events. Two clusters were obtained and, considering the cluster membership of each site, the decimal logarithm of the day-time (06:00–22:00) traffic flow was used to associate each new road with the clusters. In particular, roads with average day-time hourly traffic flow ≥1900 vehicles/hour were associated with the cluster with high traffic flow. The described methodology could be fruitfully applied on road traffic noise data in other cities.

Noise pollution in Mumbai Metropolitan Region (MMR): An emerging environmental threat

Noise pollution in urban areas is an emerging environmental threat which local agencies and state authorities must consider in planning and development. Excessive noise is becoming a significant problem adversely affecting the physiological and psychological health of the citizens. Present study was carried out to assess and quantitatively evaluate ambient noise levels in Mumbai Metropolitan Region (MMR) consisting of 9 cities namely Bhiwandi-Nizampur, Kalyan-Dombivli, Mira-Bhayandar, Mumbai, Navi Mumbai, Panvel, Thane, Ulhasnagar and Vasai-Virar. The noise environment was assessed on the basis of equivalent continuous sound pressure levels (L_eq), day-night noise levels (L_DN) and noise limit exceedance factor (NEF) during day and night time of working and non-working days in four different area categories, viz. industrial, commercial, residential and silence zones. Present study shows that silence zones have been the worst affected areas where noise pollution levels and NEF indicate excessive violation of permissible noise limits due to unplanned, congested and unruly spaces for developmental and commercial activities, followed closely by residential and commercial zones. Cities with separate industrial and commercial zones showed less noisy surroundings in comparison with those cities where land use pattern of industrial and commercial zones is around or overlapping each other. It can thus be concluded that appropriate demarcation and planned use of city space is important to avoid exposure to rising noise pollution levels. Based on the noise pollution in (MMR), various control measures are suggested including awareness campaign and strict compliance of the rules and regulations.

Adverse Cardiovascular Effects of Traffic Noise with a Focus on Nighttime Noise and the New WHO Noise Guidelines

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.

Application of the Intermittency Ratio Metric for the Classification of Urban Sites Based on Road Traffic Noise Events

Human hearing adapts to steady signals, but remains very sensitive to fluctuations as well as to prominent, salient noise events. The higher these fluctuations are, the more annoying a sound is possibly perceived. To quantify these fluctuations, descriptors have been proposed in the literature and, among these, the intermittency ratio (IR) has been formulated to quantify the eventfulness of an exposure from transportation noise. This paper deals with the application of IR to urban road traffic noise data, collected in terms of 1 s A-weighted sound pressure level (SPL), without being attended, monitored continuously for 24 h in 90 sites in the city of Milan. IR was computed on each hourly data of the 251 time series available (lasting 24 h each), including different types of roads, from motorways to local roads with low traffic flow. The obtained hourly IR values have been processed by clustering methods to extract the most significant temporal pattern features of IR in order to figure out a criterion to classify the urban sites taking into account road traffic noise events, which potentially increase annoyance. Two clusters have been obtained and a “non-acoustic” parameter x, determined by combination of the traffic flow rate in three hourly intervals, has allowed to associate each site with the cluster membership. The described methodology could be fruitfully applied on road traffic noise data in other cities. Moreover, to have a more detailed characterization of noise exposure, IR, describing SPL short-term temporal variations, has proved to be a useful supplementary metric accompanying L_Aeq, which is limited to measure the energy content of the noise exposure.

Self-Reported Sleep Disturbance from Road, Rail and Aircraft Noise: Exposure-Response Relationships and Effect Modifiers in the SiRENE Study

This survey investigates the cross-sectional association between nighttime road, rail and aircraft noise exposure and the probability to be highly sleep disturbed (%HSD), as measured by self-report in postal and online questionnaires. As part of the Swiss SiRENE study, a total of 5592 survey participants in the entire country were selected based on a stratified random sample of their dwelling. Self-reported sleep disturbance was measured using an ICBEN-style 5-point verbal scale. The survey was carried out in four waves at different times of the year. Source-specific noise exposure was calculated for several façade points for each dwelling. After adjustment for potential confounders, all three noise sources showed a statistically significant association between the nighttime noise level LNight at the most exposed façade point and the probability to report high sleep disturbance, as determined by logistic regression. The association was strongest for aircraft noise and weakest for road traffic noise. We a priori studied the role of a range of effect modifiers, including the “eventfulness” of noise exposure, expressed as the Intermittency Ratio (IR) metric, bedroom window position, bedroom orientation towards the closest street, access to a quiet side of the dwelling, degree of urbanization, sleep timing factors (bedtime and sleep duration), sleep medication intake, survey season and night air temperature. While bedroom orientation exhibited a strong moderating effect, with an Leq-equivalent of nearly 20 dB if the bedroom faces away from the nearest street, the LNight-%HSD associations were not affected by bedroom window position, sleep timing factors, survey season, or temperature.

Associations of Various Nighttime Noise Exposure Indicators with Objective Sleep Efficiency and Self-Reported Sleep Quality: A Field Study

It is unclear which noise exposure time window and noise characteristics during nighttime are most detrimental for sleep quality in real-life settings. We conducted a field study with 105 volunteers wearing a wrist actimeter to record their sleep during seven days, together with concurrent outdoor noise measurements at their bedroom window. Actimetry-recorded sleep latency increased by 5.6 min (95% confidence interval (CI): 1.6 to 9.6 min) per 10 dB(A) increase in noise exposure during the first hour after bedtime. Actimetry-assessed sleep efficiency was significantly reduced by 2%-3% per 10 dB(A) increase in measured outdoor noise (Leq, 1h) for the last three hours of sleep. For self-reported sleepiness, noise exposure during the last hour prior to wake-up was most crucial, with an increase in the sleepiness score of 0.31 units (95% CI: 0.08 to 0.54) per 10 dB(A) Leq,1h. Associations for estimated indoor noise were not more pronounced than for outdoor noise. Taking noise events into consideration in addition to equivalent sound pressure levels (Leq) only marginally improved the statistical models. Our study provides evidence that matching the nighttime noise exposure time window to the individual's diurnal sleep-wake pattern results in a better estimate of detrimental nighttime noise effects on sleep. We found that noise exposure at the beginning and the end of the sleep is most crucial for sleep quality.

Effects of combined traffic noise on the synaptic ultrastructure and expressions of p-CaMKII and NMDAR1 in the hippocampus of young SD rats

In order to explore the effects of combined traffic noise (CTN) on learning and memory function, young Sprague-Dawley (SD) rats were exposed to CTN from highway and high-speed railway for 52 days, whose day-night equivalent continuous A-weighted sound pressure level (L_dn) was 70 dB(A) (corresponding sound pressure level was 80 dB). The synaptic ultrastructure and the expressions of phosphorylated calcium/calmodulin-dependent protein kinase II (p-CaMKII) and N-methyl-D-aspartate receptor 1 (NMDAR1 or NR1) in the hippocampus were tested by transmission electron microscopy (TEM) and Western blot, respectively. Results showed that there was no significant difference in the synaptic ultrastructure and the expressions of p-CaMKII and NR1 in the hippocampus of young rats between the experimental group and control group. Compared with single high-speed railway noise (HSRN) with L_dn of 70 dB(A), CTN had less influences on learning and memory function, which was closely related to smaller intermittency of CTN and less anxiety caused by CTN. In comparison with white noise with a sound pressure level of 80 dB, CTN had less impacts on learning and memory function, which was mainly associated with CTN's smaller R-weighted sound pressure level based on rats' auditory sensitivity.

Comparison of sensitivity and annoyance to road traffic and community noise between a South African and a Swiss population sample

In developing countries, noise annoyance and noise sensitivity are not commonly investigated. The present study aimed to assess the annoyance and sensitivity to noise in 364 adults living in informal settings in the Western Cape Province, South Africa and to compare with a similar study conducted in Switzerland. Compared to Switzerland, higher percentages of highly noise sensitive individuals (women: 35.1% vs 26.9%; men: 25% vs 20.5%) and people highly annoyed to road traffic noise (women: 20.5% vs 12.4%; men: 17.9% vs 11.1%) were observed in South Africa. While in South Africa women were more annoyed to neighborhood noise than in Switzerland (21.1% vs 9.4%), this was not the case among men (7.1% vs 7.8%). Multivariable logistic regression models showed that in both countries men tended to be less sensitive and less annoyed by noise. Corresponding associations with age and education were somewhat different between the countries, which may be explained by socioeconomic and environmental differences. This study indicates that noise exposure considerably affects people living in informal settlements, and noise should be considered when improving the housing conditions.

The effect of aircraft, road, and railway traffic noise on stroke - results of a case-control study based on secondary data

AIM

To examine the stroke risks associated with aircraft, road traffic, and railway noise exposure in a large case-control study.

MATERIALS AND METHODS

All people aged ≥40 years living around the Frankfurt airport that were insured by one of three large statutory health insurance funds between 2005 and 2010 were included in the study (n = 1,026,670). Address-specific exposure to aircraft, road, and railway traffic noise was estimated for 2005. We used insurance claim data to identify 25,495 newly diagnosed cases of stroke between 2006 and 2010 and compared them with 827,601 control participants. Logistic regression analysis was used to calculate the odds ratios adjusted for age, sex, local proportion of people receiving unemployment benefits, and if available individual indicators of socioeconomic status (education, occupation).

RESULTS

For 24-h continuous aircraft noise exposure, neither increased risk estimates nor a positive linear exposure-risk relation was found. However, stroke risk was statistically significantly increased by 7% [95% confidence intervals (95%CI): 2-13%] for people who were exposed to <40 dB of 24-h continuous aircraft noise, but ≥6 events of maximum nightly sound pressure levels ≥50 dB. For road and railway traffic noise, there was a positive linear exposure-risk relation: Per 10 dB the stroke risk increased by 1.7% (95%CI: 0.3-3.2%) for road traffic noise and by 1.8% (95%CI: 0.1-3.3%) for railway traffic noise. The maximum risk increase of 7% (95%CI: 0-14%) for road traffic noise and 18% (95%CI: 2-38%) for railway traffic noise was found in the exposure category ≥65 to <70 dB.

CONCLUSION

This large case-control study indicates that traffic noise exposure may lead to an increase in stroke risk. It furthermore suggests that maximum aircraft noise levels at night increase the stroke risk even when continuous noise exposure is low, and thus highlights the relevance of maximum noise levels for research and policies on noise protection.

Long-term exposure to transportation noise and air pollution in relation to incident diabetes in the SAPALDIA study

Background

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.

Methods

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.

Results

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.

Conclusions

Transportation noise may be more relevant than AP in the development of diabetes, potentially acting through noise-induced sleep disturbances.

Diurnal variability of transportation noise exposure and cardiovascular mortality: A nationwide cohort study from Switzerland

BACKGROUND

Most epidemiological noise studies consider 24 h average noise exposure levels. Our aim was to exploratively analyze the impact of noise exposure at different time windows during day and night on cardiovascular mortality.

METHODS

We generated Switzerland-wide exposure models for road traffic, railway and aircraft noise for different time windows for the year 2001. Combined noise source equivalent continuous sound levels (L_eq) for different time windows at the most exposed façade were assigned to each of the 4.41 million Swiss National Cohort adult participants. Follow-up period was from 2000 to 2008. Hazard ratios (HR) of noise effects on various cardiovascular primary causes of death were computed by Cox regression models adjusted for potential confounders and NO₂ levels.

RESULTS

For most cardiovascular causes of death we obtained indications for a diurnal pattern. For ischemic heart disease the highest HR was observed for the core night hours from 01 h to 05 h (HR per standard deviation of L_eq: 1.025, 95% CI: 1.016-1.034) and lower HR for the daytime 07 h to 19 h (1.018 [1.009-1.028]). Heart failure and daytime L_eq yielded the highest HR (1.047 [1.027-1.068]).

CONCLUSION

For acute cardiovascular diseases, nocturnal intermittent noise exposure tended to be more relevant than daytime exposure, whereas it was the opposite for chronic conditions such as heart failure most strongly associated with continuous daytime noise. This suggests that for acute diseases sleep is an important mediator for health consequences of transportation noise.