Comparative evaluation of soundscapes in human activities spatial contexts of pedestrian spaces adjacent to arterial roads

Pedestrian spaces adjacent to arterial roads are characterized by the dominance of traffic noise alongside various human activities. Research on the impact of traffic noise on the soundscape evaluation of pedestrian spaces has not considered human activities spatial contexts. To address this research gap, the present study constructed auditory environments for pedestrian spaces in the contexts of commuting, residential, and commercial activities. A total of seven auditory environments were subjected to laboratory auditory evaluations, including perceived dominance of sound source, acoustic comfort, and perceived affective quality of the soundscape. The results indicated that in pedestrian spaces with constant traffic noise, the presence of significant human activity sounds led to a decreased perceived dominance of traffic noise and an increased acoustic comfort, despite the higher acoustic energy. Thus, pedestrian spaces with a variety of human activity received better soundscape evaluations. The elements that reflected the human activities spatial contexts, including the types and intensity of human activities, played a crucial role in soundscape evaluations. Better acoustic comfort was reported in pedestrian spaces characterized by low-intensity residential activities and high-intensity commercial activities. Additionally, pedestrian spaces with more intense activities offered an actively engaging soundscape. The findings can provide reference for a more accurate evaluation of the soundscape in pedestrian spaces and guide the soundscape design of pedestrian environments.

Air pollution, traffic noise, greenness, and temperature and the risk of incident type 2 diabetes: Results from the KORA cohort study

Introduction

Type 2 diabetes (T2D) is a major public health concern, and various environmental factors have been associated with the development of this disease. This study aimed to investigate the longitudinal effects of multiple environmental exposures on the risk of incident T2D in a German population-based cohort.

Methods

We used data from the KORA cohort study (Augsburg, Germany) and assessed exposure to air pollutants, traffic noise, greenness, and temperature at the participants' residencies. Cox proportional hazard models were used to analyze the associations with incident T2D, adjusting for potential confounders.

Results

Of 7736 participants included in the analyses, 10.5% developed T2D during follow-up (mean: 15.0 years). We found weak or no association between environmental factors and the risk of T2D, with sex and education level significantly modifying the effects of air pollutants.

Conclusion

Our study contributes to the growing body of literature investigating the impact of environmental factors on T2D risks and suggests that the impact of environmental factors may be small.

[Air pollution, noise and hypertension : Partners in crime]

Air pollution and traffic noise are two important environmental risk factors that endanger health in urban societies and often act together as "partners in crime". Although air pollution and noise often co-occur in urban environments, they have typically been studied separately, with numerous studies documenting consistent effects of individual exposure on blood pressure. In the following review article, we examine the epidemiology of air pollution and noise, especially regarding the cardiovascular risk factor arterial hypertension and the underlying pathophysiology. Both environmental stressors have been shown to lead to endothelial dysfunction, oxidative stress, pronounced vascular inflammation, disruption of circadian rhythms and activation of the autonomic nervous system, all of which promote the development of hypertension and cardiovascular diseases. From a societal and political perspective, there is an urgent need to point out the potential dangers of air pollution and traffic noise in the American Heart Association (AHA)/American College of Cardiology (ACC) prevention guidelines and the European Society of Cardiology (ESC) guidelines on prevention. Therefore, an essential goal for the future is to raise awareness of environmental risk factors as important and, in particular, preventable risk factors for cardiovascular diseases.

Investigating important and necessary conditions to analyse traffic noise levels at intersections in mid-sized cities

Traffic noise is a major problem for urban residents, especially near intersections. In order to effectively manage and control traffic noise, there is a need for a better understanding of noise-influencing variables at intersections. In this way, the study aims to identify and distinguish the important and necessary conditions corresponding to the particular traffic noise level. Using 342 h of field data from 19 intersections in Kanpur, the current research has used the Partial Least Square-Structural Equation Modelling (PLS-SEM) and Necessary Condition Analysis (NCA). The study determines that traffic volume, honking, speed, and median width are important factors. Traffic volume and honking are positively affecting traffic noise level, while speed and median width have a negative effect. Further investigation reveals that only traffic volume and honking are necessary to achieve a particular traffic noise level. Policymakers can use these findings to manage and control traffic noise at intersections.

Urban environment in pregnancy and postpartum depression: An individual participant data meta-analysis of 12 European birth cohorts

BACKGROUND

Urban environmental exposures associate with adult depression, but it is unclear whether they are associated to postpartum depression (PPD).

OBJECTIVES

We investigated associations between urban environment exposures during pregnancy and PPD.

METHODS

We included women with singleton deliveries to liveborn children from 12 European birth cohorts (N with minimum one exposure = 30,772, analysis N range 17,686-30,716 depending on exposure; representing 26-46 % of the 66,825 eligible women). We estimated maternal exposure during pregnancy to ambient air pollution with nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10), road traffic noise (Lden), natural spaces (Normalised Difference Vegetation Index; NDVI, proximity to major green or blue spaces) and built environment (population density, facility richness and walkability). Maternal PPD was assessed 3-18 months after birth using self-completed questionnaires. We used adjusted logistic regression models to estimate cohort-specific associations between each exposure and PPD and combined results via meta-analysis using DataSHIELD.

RESULTS

Of the 30,772 women included, 3,078 (10 %) reported having PPD. Exposure to PM10 was associated with slightly increased odds of PPD (adjusted odd ratios (OR) of 1.08 [95 % Confidence Intervals (CI): 0.99, 1.17] per inter quartile range increment of PM10) whilst associations for exposure to NO2 and PM2.5 were close to null. Exposure to high levels of road traffic noise (≥65 dB vs. < 65 dB) was associated with an OR of 1.12 [CI: 0.95, 1.32]. Associations between green spaces and PPD were close to null; whilst proximity to major blue spaces was associated with increased risk of PPD (OR 1.12, 95 %CI: 1.00, 1.26). All associations between built environment and PPD were close to null. Multiple exposure models showed similar results.

DISCUSSION

The study findings suggest that exposure to PM10, road traffic noise and blue spaces in pregnancy may increase PPD risk, however future studies should explore this causally.

Traffic noise distribution characteristics of high-rise buildings along ultra-wide cross section highway with multiple noise reduction measures

Nowadays, ultra-wide cross section highway is a hotspot in construction and brings some unique noise distribution characteristics. In this work, we further investigate noise distribution characteristics of diverse building layouts along ultra-wide cross section highway in Guangdong Province with multiple noise mitigation measures. By the aid of vehicle noise emission model and noise mapping, the influence of high-rise building layouts and shielding in the urban planning on noise mitigation is also considered. Some key findings are summarized as follows: (1) Under the same distance, the noise level of non-frontage building facades is higher than frontage building facades. After taking noise reduction measures, the noise reduction effect of non-street-facing building facades, buildings facing the road, and buildings at a long distance to the road is greater than street-facing building facades, buildings sideways to the road, and buildings at a short distance; (2) the distribution trend of insertion loss (IL) of non-frontage buildings is influenced by the height of the frontage buildings. Specifically, the trend of insertion loss first increases and then decreases as the floor rises when the height of non-frontage buildings is higher than frontage buildings. Comparatively, the trend of insertion loss decreases as the floor rises when the height of non-frontage buildings is equal to frontage buildings; (3) when double noise reduction measures are implemented, the noise distribution trend in buildings is similar to that observed with individual noise reduction measure, where the difference between both is only 0.6 dB(A). Thanks to the high representativeness of the case area, this work can provide some design guidance for the urban planning and the selection of noise reduction measures along the ultra-wide cross section highway.

The impact of traffic noise on the capitalization of public walking area: A hedonic analysis of Vienna, Austria

Traffic noise is a burden at home and outdoors. Economic literature confirms mostly negative effects of traffic noise on house prices, often based on distance between high noise and house location. We extend this literature using rich micro data to examine not only the impact of traffic noise at the house but also provide new results on the impact of traffic noise in public areas surrounding a home. Using Hedonic regression in Vienna, Austria, we confirm that very loud traffic noise (≥65 dB) experienced at the house reduces housing prices and further show that the value of public walking areas near a home, while positive overall, are substantially reduced when exposed to noise. Our findings help to establish spatial patterns in noise capitalization reflecting household exposure and the impact on the capitalized values of public areas in a context where active transportation (e.g. walking, biking) is an important mode of transportation. For policymakers, our findings help quantify and raise important questions as how to address and link the public bad nature of noise pollution to nearby residents.

Childhood sound disturbance and sleep problems in Alpine valleys with high levels of traffic exposures and greenspace

Sound disturbance and sleep problems are regarded as the most common adverse effects of environmental noise but evidence of the role of air pollution and greenspace is scant. This is especially true for children who find themselves in a sensitive developmental period and experience their environment differently than adults. This study examined the joint effects of traffic exposures and residential greenspace on child sound disturbance and sleep problems via perceptions of neighborhood quality. We used cross-sectional data for 1251 schoolchildren (8-12 years) in the Tyrol region of Austria/Italy. Questionnaires provided information on sociodemographic and housing factors, perceived neighborhood quality, sound disturbance in different situations, and sleep problems. Modelled acoustic indicators included day-evening-night sound levels and the highest percentile level, and night-time sound level and a bespoke sleep disturbance index. Nitrogen dioxide served as a proxy for traffic-related air pollution. The normalized difference vegetation index was calculated as a measure of residential greenspace, and presence of a domestic garden was self-reported. Results showed that higher level of traffic-related exposures was positively associated with sound disturbance and sleep problems, while living in a greener area, especially in a house with a garden, was associated with lower sound disturbance and less sleep problems even in the presence of traffic. Traffic exposures contributed to more unfavorable, and greenspace to more positive perceptions in terms of traffic-related stressors, opportunities for outdoor recreation, and general satisfaction with the neighborhood. This indirect path seemed more important for greenspace than for traffic exposures. In conclusion, it seems advantageous to combine traffic-related mitigation with improving access to greenspace in interventions for supporting the acoustic comfort of children during day and nighttime. Even highly nature-dominated environments could still benefit from proximal green infrastructure, especially from domestic gardens.

Concomitant exposure to air pollution, green space and noise, and risk of myocardial infarction: a cohort study from Denmark

AIMS

The three correlated environmental exposures (air pollution, road traffic noise, and green space) have all been associated with the risk of myocardial infarction (MI). The present study aimed to analyse their independent and cumulative association with MI.

METHODS AND RESULTS

In a cohort of all Danes aged 50 or older in the period 2005-17, 5-year time-weighted average exposure to fine particles (PM2.5), ultrafine particles, elemental carbon, nitrogen dioxide (NO2), and road traffic noise at the most and least exposed façades of residence was estimated. Green space around residences was estimated from land use maps. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence interval (CI), and cumulative risk indices (CRIs) were calculated. All expressed per interquartile range. Models were adjusted for both individual and neighbourhood-level socio-demographic covariates. The cohort included 1 964 702 persons. During follow-up, 71 285 developed MI. In single-exposure models, all exposures were associated with an increased risk of MI. In multi-pollutant analyses, an independent association with risk of MI was observed for PM2.5 (HR: 1.026; 95% CI: 1.002-1.050), noise at most exposed façade (HR: 1.024; 95% CI: 1.012-1.035), and lack of green space within 150 m of residence (HR: 1.018; 95% CI: 1.010-1.027). All three factors contributed significantly to the CRI (1.089; 95% CI: 1.076-1.101).

CONCLUSION

In a nationwide cohort study, air pollution, noise, and lack of green space were all independently associated with an increased risk of MI. The air pollutant PM2.5 was closest associated with MI risk.

Contributions of residential traffic noise to depression and mental wellbeing in Hong Kong: A prospective cohort study

Prior studies on the association between traffic noise and mental health have been mostly conducted in settings with lower population densities. However, evidence is lacking in high population-density settings where traffic noise is more pervasive and varies by topography and the vertical elevation of the residential unit. This study aimed to assess the mental health impact of residential traffic noise in one of the world's most urbanised populations. Data were analysed from 13,401 participants aged ≥15 years in a prospective cohort in Hong Kong from 2009 to 2014. Residential traffic noise level was estimated using 3D-geocoding and validated models that accounted for sound propagation in a highly vertical landscape. The 24-h day-night exposure to traffic noise, denoted as Ldn, was estimated with a 10-dB(A) penalty for night hours. Probable depression and mental wellbeing were assessed using the Patient Health Questionnaire-9 and the Short Form Health Questionnaire SF-12v2, respectively. Mixed effect regressions with random intercepts were used to examine the association between traffic noise and mental health outcomes. Residential road traffic noise (for each increment of 10 A-weighted decibels [dB(A)] 24-h average exposure) was associated with probable depression (odds ratio (OR) = 1.17, 95% CI: 1.05, 1.31), and poorer mental wellbeing (mean difference = -0.19, 95% CI: 0.31, -0.06), adjusting for sociodemographics, smoking, body mass index, self-reported health, proximity to green space, and neighbourhood characteristics (average household income, population density, and Gini coefficient). The results were robust to further adjustment for air pollution. In stratified analyses, residential traffic noise was associated with probable depression and poorer mental wellbeing among students and individuals aged 15-34 years. Residential traffic noise was associated with probable depression and poorer mental wellbeing in a highly urbanised setting. As traffic noise is increasing in urban settings, the public health impact of noise pollution could be substantial.

Long-Term Exposure to Traffic Noise and Risk of Incident Cardiovascular Diseases: a Systematic Review and Dose-Response Meta-Analysis

While noise pollution from transportation has become an important public health problem, the relationships between different sources of traffic noise and cardiovascular diseases (CVDs) remain inconclusive. A comprehensive meta-analysis was therefore conducted to quantitatively assess the effects of long-term exposure to road traffic, railway, and aircraft noise on CVDs and relevant subtypes. We systematically retrieved PubMed, Embase, and Web of Science for articles published before April 4, 2022. Summary relative risks (RRs) and 95% confidence intervals (CIs) were estimated by the fixed- or random-effects models. In total, 23 articles were included in our meta-analysis. The risk of CVDs increased by 2% (RR 1.020, 95% CI 1.006-1.035) and 1.6% (RR 1.016, 95% CI 1.000-1.032) for every 10 dB increment of road traffic and aircraft noise. For CVD subtypes, the risk increased by 3.4% (1.034, 1.026-1.043) for stroke and 5% (1.050, 1.006-1.096) for heart failure with each 10 dB increment of road traffic noise; the risk of atrial fibrillation increased by 1.1% (1.011, 1.002-1.021) with each 10 dB increment of railway noise; and the risk increased by 1% (1.010, 1.003-1.017) for myocardial infarction, 2.7% (1.027, 1.004-1.050) for atrial fibrillation, and 2.3% (1.023, 1.016-1.030) for heart failure with each 10 dB increment in aircraft noise. Further, effects from road traffic, railway, and aircraft noise all followed positive linear trends with CVDs. Long-term exposure to traffic noise is positively related to the incidence risk of cardiovascular events, especially road traffic noise which significantly increases the risk of CVDs, stroke, and heart failure.

Exposure to long-term source-specific transportation noise and incident breast cancer: A pooled study of eight Nordic cohorts

BACKGROUND

Environmental noise is an important environmental exposure that can affect health. An association between transportation noise and breast cancer incidence has been suggested, although current evidence is limited. We investigated the pooled association between long-term exposure to transportation noise and breast cancer incidence.

METHODS

Pooled data from eight Nordic cohorts provided a study population of 111,492 women. Road, railway, and aircraft noise were modelled at residential addresses. Breast cancer incidence (all, estrogen receptor (ER) positive, and ER negative) was derived from cancer registries. Hazard ratios (HR) were estimated using Cox Proportional Hazards Models, adjusting main models for sociodemographic and lifestyle variables together with long-term exposure to air pollution.

RESULTS

A total of 93,859 women were included in the analyses, of whom 5,875 developed breast cancer. The median (5th-95th percentile) 5-year residential road traffic noise was 54.8 (40.0-67.8) dB Lden, and among those exposed, the median railway noise was 51.0 (41.2-65.8) dB Lden. We observed a pooled HR for breast cancer (95 % confidence interval (CI)) of 1.03 (0.99-1.06) per 10 dB increase in 5-year mean exposure to road traffic noise, and 1.03 (95 % CI: 0.96-1.11) for railway noise, after adjustment for lifestyle and sociodemographic covariates. HRs remained unchanged in analyses with further adjustment for PM2.5 and attenuated when adjusted for NO2 (HRs from 1.02 to 1.01), in analyses using the same sample. For aircraft noise, no association was observed. The associations did not vary by ER status for any noise source. In analyses using <60 dB as a cutoff, we found HRs of 1.08 (0.99-1.18) for road traffic and 1.19 (0.95-1.49) for railway noise.

CONCLUSIONS

We found weak associations between road and railway noise and breast cancer risk. More high-quality prospective studies are needed, particularly among those exposed to railway and aircraft noise before conclusions regarding noise as a risk factor for breast cancer can be made.

The co-benefits of electric mobility in reducing traffic noise and chemical air pollution: Insights from a transit-oriented city

Traffic noise is a growing threat to the urban population. Prolonged exposure to traffic noise has been linked to negative health consequences such as annoyance, sleep disturbances and cardiovascular diseases. While electric vehicles are known to have lower noise profiles, the impacts of electric mobility on traffic noise, especially for electrified heavy-duty vehicles, have not been thoroughly examined. This study aims to examine the impacts of both electric light-duty vehicles and electric buses on traffic noise levels in a highly urbanized city. Traffic noise along the source line and pedestrian network was first estimated and mapped to illustrate its spatiotemporal variations. Then, scenario analysis was used to compare the impacts. Population potentially benefiting from reduced traffic noise in the neighbourhoods and the associated health impacts were also estimated. Results indicate that electric buses have a greater potential to reduce traffic noise, with a maximum reduction of 4.4 dBA during daytime in the urban cores. With all bus fleet electrified, around 60% of the population can benefit from a reduction of 1 dBA at the street environment, 15.3% for 1-2 dBA, and 4.3% for more than 2 dBA. The estimated reduction of preventable deaths and preventable cases of diseases per 100,000 population are 4.15 and 112.99 respectively. The findings shed important insights into prioritizing bus routes to be electrified in urban areas for maximizing health co-benefits.

Traffic noise annoyance in the LIFE-adult study in Germany: Exposure-response relationships and a comparison to the WHO curves

BACKGROUND

Noise annoyance is the second-highest cause of lost disability-adjusted life-years due to environmental noise in Europe. Evidence on exposure-response relationships (ERRs) for traffic noise annoyance with more accurate exposure values is still needed.

OBJECTIVES

In an analysis of the population-based LIFE-Adult study in Leipzig, Germany, we aimed to investigate the effect of road, railway (train and tram), and aircraft noise on high annoyance (HA).

METHODS

Traffic exposure data was taken for 2012 and data on noise annoyance was evaluated between 2018 and 2021. HA was defined according to international standardized norms. We calculated risk estimates using logistic regression, controlling for age, sex, and socioeconomic status, and compared our ERRs with those from the last WHO review on this topic.

RESULTS

Aircraft noise had the highest relative risk for noise-related HA (OR = 12.7, 95% CI: 9.37-17.10 per 10 dB L_den increase). The road and railway traffic risk estimates were similar to each other (road: OR = 3.55, 95% CI: 2.78-4.54; railway: OR = 3.31, 95% CI: 2.77-3.97 per 10 dB L_den increase). Compared to the WHO curves, the proportion of highly annoyed individuals was somewhat lower for road and rail traffic noise, but higher for aircraft noise.

DISCUSSION

Aircraft noise is particularly annoying. There were differences between our study's ERRs and those in the WHO review, especially for aircraft noise. These differences may be partly explained by the improved accuracy of the exposure values, as we considered secondary road networks and tram noise, and by a lack of a nighttime flight ban at the Leipzig airport. Geographical, regional and climatic variations, inconsistency in HA cut-offs, as well as temporal developments in the annoyance experience may also explain the differences. Since ERRs serve as a basis for decision making in public policies, regular updates of the curves based on new evidence is recommended.

Joint associations and pathways from greenspace, traffic-related air pollution, and noise to poor self-rated general health: A population-based study in Sofia, Bulgaria

BACKGROUND

Little is still known of how multiple urban exposures interact as health determinants. This study investigated various ways in which greenspace, traffic-related air pollution, and noise could operate together, influencing general health status.

METHODS

In 2022, a cross-sectional population-based survey was conducted in Sofia, Bulgaria. Included were 917 long-term adult residents who completed questionnaires on poor self-rated health (PSRH), total time spent in physical activity (PA), home garden presence, time spent in urban greenspace and nature, and sociodemographics. Residential greenspace was operationalized using the normalized difference vegetation index (NDVI), tree cover density, number of trees, and access to local greenspace and parks. Nitrogen dioxide (NO₂) was modeled for the study area. Road traffic, railway, and aircraft day-evening-night sound levels (L_den) were extracted from EU noise maps. Area-level income and urbanicity were considered. Analyses included multivariate ordinal regressions, interactions, and structural equation modeling (SEM).

RESULTS

Associations with PSRH were per 0.10 NDVI _300 m: OR = 0.65 (0.42-1.01), home garden: OR = 0.72 (0.49-1.07), per 5 μg/m³ NO₂: OR = 1.57 (1.00-2.48), per 5 dB(A) L_den road traffic: OR = 1.06 (0.91-1.23), railway: OR = 1.11 (1.03-1.20), and aircraft: OR = 1.22 (1.11-1.34). Spending >30 min/week in nature related to better health. In multi-exposure models, only associations with aircraft and railway L_den persisted. People with lower education and financial difficulties or living in poorer districts experienced some exposures stronger. In SEM, time spent in nature and PA mediated the effect of greenspace.

CONCLUSIONS

Greenspace was associated with better general health, with time spent in nature and PA emerging as intermediate pathways. NO₂, railway, and aircraft noise were associated with poorer general health. These results could inform decision-makers, urban planners, and civil society organizations facing urban development problems. Mitigation and abatement policies and measures should target socioeconomically disadvantaged citizens.

A study on the impact of road traffic noise exposure on work efficiency of housewives

Housewives are individuals who take on the caregiving role in the family in virtually every society and while discharging their duties experience serious psychological difficulties due to external environmental pollutants like air, noise, etc., which influences their efficiency of performing household activities. This study hypothesizes a causal association between perception of traffic noise and the reduction in performance of housewives in their daily household activities. A simple mediation model was utilized for the study with traffic noise perception as the exposure variable. The sensitivity to traffic noise, annoyance caused due to traffic noise, and the effect of traffic noise on housewives were evaluated using questionnaire survey. Of the respondents, 57.33% reported high level of traffic noise perception, while 65.81% reported high annoyance due to traffic noise perception. Of the respondents, 88.69% reported higher levels of agreement with regard to negative effect of traffic noise on their household activities. The results supported the hypothesis with respondents belonging to high and moderate noise perception groups reporting a higher reduction in performance as compared to those belonging to the low noise perception group at higher values of sensitivity. There was no significant direct effect among those who perceived traffic noise as high and moderate. However, the indirect path revealed that there was a significantly higher reduction in performance among those belonging to the high and moderate noise perception group as compared to those belonging to the low noise perception group while those who perceived traffic noise as high and moderate did not differ significantly only at higher levels of sensitivity. Using OGRS computational tool, a sensitivity value of 5.586 was identified as the Johnson-Neyman boundary of significance for the direct effect. The results from the study highlight the need for including environmental noise related regulations with regard to residential structures by the concerned authorities and also the need for undertaking more rigorous studies by health authorities and organizations so that the effects are minimized if not eliminated completely.

Numerical modeling and field test of sonic crystal acoustic barriers

The rapid development of highway traffic has gradually deteriorated the acoustic environment along the line. Sonic crystal theory provides new ideas for traffic acoustic barrier. However, the lack of practical numerical models and field test verifications has restricted the promotion and application of sonic crystal acoustic barriers (SCABs). In this study, a field test was conducted to study the noise reduction performance of SCAB. The SCAB exhibits excellent wave attenuation in the band gap, when compared with concrete acoustic barriers (CABs) along highways, the noise reduction performance in the band gap is improved by 0.5-2.1 dB(A), especially at the local peak in the highway noise spectrum. However, from the perspective of total insertion loss, CAB performs better than SCAB in all distances in the protected area. Next, the 3D FEM model is established based on the highway site and validated by the measured results. Compared with the commonly used 2D model, the 3D FEM model is more practical for considering the top diffraction and ground reflection, which influence the noise reduction performance a lot and need to be considered. To improve the noise reduction performance of SCAB, three types of optimization measures are explored. The gradient combination of scatterers can effectively improve the noise reduction effect in the low-frequency band gap, especially the high- to low-gradient layout. Besides, not only the porous sound-absorbing material but also the microperforated plates can improve the noise reduction effect, especially outside the band gap. The larger perforation rates and smaller apertures of microperforated plate are preferred in SCAB. This work provides field test support and promotes the application of SCABs in traffic noise control.

Assessment of Hidden Hearing Loss in Individuals Exposed to Occupational Noise Using Cochlear, Neural, Temporal Functions and Quality of Life Measures

The present study aims to identify the objective tests that can identify hidden hearing loss in a group of individuals exposed to occupational noise, which is not otherwise evident as a clinically relevant permanent threshold shift. A standard group comparison design was used to study the hidden auditory effect of occupational noise on traffic police officers. A total of 50 participants (n = 25 exposed to occupational noise; n = 25 non-occupational noise-exposed) were included in the study. The test battery comprised of behavioral tests (hearing thresholds from 250 to 16,000 Hz), fine structure Distortion product otoacoustic emissions (DPOAE's) as physiological measure, Click and CE-chirp® evoked auditory brain stem response (ABR) as electrophysiological, and Gap detection test (GDT) and Temporal modulation transfer function (TMTF) as psychophysical measures. Among the measures evaluated, extended high-frequency audiometry, fine structure DPOAE amplitude, CE-chirp® ABR, GDT, and TMTF showed a significant difference (p < 0.05) between the traffic police individuals exposed to occupational noise and the controls. However, routine audiometry and click-evoked ABR did not show any significant differences. The high-frequency audiometric thresholds, fine structure DPOAEs, CE-chirp® evoked ABR, GDT and TMTF have been shown to be affected in individuals exposed to occupational noise. This finding indicates a hidden hearing loss in the study group. Hence, this study paves the way for early identification and intervention of noise-induced hearing loss by including these measures along with routine test protocol in susceptible individuals.

Traffic noise and adiposity: a systematic review and meta-analysis of epidemiological studies

Traffic noise has attracted much attention as a significant and intractable public health threat. This study was designed as a systematical review to explore the association of traffic noise with different indicators of obesity, thus providing updated quantitative estimates for the pooled effect estimates of the existing literature. We conducted an extensive search for epidemiological studies that investigated the association of traffic noise with obesity in three electronic databases till February 23, 2021. We used random-effects meta-analysis to calculate the summary effect estimates for each 10-dB(A) increase in noise and compared the highest with the lowest category of noise in relation to seven obesity indicators. Meanwhile, we assessed the risk of bias and the overall quality of the evidence of each study as well as the level of evidence for each exposure-outcome pair. The initial search identified 30 studies, 13 of which were ultimately included. The meta-analysis for the highest versus the lowest category of noise exposure was generally associated with higher waist circumfluence (WC) ranging from 0.326 cm (95% confidence interval (CI) = 0.078, 0.574) to 0.705 cm (95% CI = 0.071, 1.340) and higher odds of central obesity ranging from 1.055 (95% CI = 1.000, 1.109) to 1.167 (95% CI = 1.037, 1.298). When the continuous exposure (each 10 dB(A) increase in noise) was introduced, similar results were found. This study indicated positive associations of traffic noise with WC and central obesity. However, in consideration of some limitations, there is an urgent need for future studies to increase the sample size, discriminate the etiological differences in different noise and obesity indicators, and thoroughly consider socioeconomic status.

Useful tools for integrating noise maps about noises other than those of transport, infrastructures, and industrial plants in developing countries: Casework of the Aburra Valley, Colombia

The behavior of environmental noise in developing countries is conditioned by characteristics that are not only linked to transport, infrastructures, and industrial plants in the annuity (common representation in noise maps), but also to other types of sources and periodicities that can influence significantly in noise levels. For this reason, this work proposes different temporal analyzes during the annuity that can be linked to the noisy activities typical of developing tropical countries. To do this, a noise monitoring network composed of seven monitors representing different sources present in the Aburrá Valley (AV) in Colombia is analyzed with measurements of LAeq, every hour, in a period between August 2016 and July 2019. The results show that AV noise is strongly influenced by leisure activities related to high-power sound systems, different celebrations, and continuous noise from car traffic that affect the population mainly on weekends and nights. This work marks a clear path to precisely address noise pollution in the action plans of developing countries.

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.

A study on road traffic noise exposure and prevalence of insomnia

The potential of the nocturnal traffic noise to affect the quality and the quantity of sleep makes it a serious threat to public health. The present study is an attempt to provide insights into the ways through which nocturnal traffic noise causes insomnia. A total of 4525 respondents participated in the study. Modelled nocturnal noise levels were used, and the assessment of insomnia-related symptoms was done using the Jenkins sleep problem scale. A directed acyclic graph was used to obtain the minimum set of confounders that need to be adjusted for obtaining unbiased estimates. DASS-21 item scale was used to evaluate the mental health of respondents. The study reported significant associations between traffic noise exposure and all insomnia-related symptoms. For the total study population, the highest risk occurred for difficulty in falling asleep symptom (OR = 1.45; 95% CI = 1.01 - 2.07). Based on the sensitivity analysis, respondents with bedrooms facing the road were found to have higher risks as compared to the overall sample with the highest risks occurring for difficulty in maintaining the sleep symptom (OR = 1.65; 95% CI = 1.08 - 2.51). Severity levels of mental disorders showed an increasing trend with the increasing noise levels. Females were found to have a higher risk as compared to males (OR = 1.75; 95% CI = 1.14 - 2.69). No significant association was found between traffic noise exposure and sleep medication usage. Future research on large populations can help in minimizing the impacts of nocturnal noise on public health.

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.

An experimental test of chronic traffic noise exposure on parental behaviour and reproduction in zebra finches

Chronic traffic noise is increasingly recognised as a potential hazard to wildlife. Several songbird species have been shown to breed poorly in traffic noise exposed habitats. However, identifying whether noise is causal in this requires experimental approaches. We tested whether experimental exposure to chronic traffic noise affected parental behaviour and reproductive success in zebra finches (Taeniopygia guttata). In a counterbalanced repeated-measures design, breeding pairs were exposed to continuous playback of one of two types of highway noise previously shown to be either neutral (control) or aversive. Parental nest attendance positively correlated with feeding effort and was higher for the aversive than the control sound and this effect was more pronounced for parents attending larger broods. However, neither noise condition affected offspring number, growth or body mass. The absence of an effect held when we combined our data with data from two other comparable studies into a meta-analysis. We discuss whether the increased nest attendance could be a compensatory strategy that alleviated detrimental noise effects on the chicks, and whether it could be caused by impaired parent-offspring or within-pair communication. Future work should test these hypotheses and investigate potential long-term costs of increased parental engagement.

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.

Traffic noise-induced changes in wake-propensity measured with the Odds-Ratio Product (ORP)

Nocturnal traffic noise can disrupt sleep and impair physical and mental restoration, but classical sleep scoring techniques may not fully capture subtle yet clinically relevant alterations of sleep induced by noise. We used a validated continuous measure of sleep depth and quality based on automatic analysis of physiologic sleep data, termed Wake Propensity (WP), to investigate temporal changes of sleep in response to nocturnal noise events in 3-s epochs. Seventy-two healthy participants (mean age 40.3 years, range 18-71 years, 40 females, 32 males) slept for 11 nights in a laboratory, during which we measured sleep with polysomnography. In 8 nights, participants were exposed to 40, 80 or 120 road, rail and/or aircraft noise events with maximum noise levels of 45-65 dB L_AS,max during 8-h sleep opportunities. We analyzed sleep macrostructure and event-related change of WP during noise exposure with linear mixed models. Nocturnal traffic noise led to event-related shifts towards wakefulness and less deep, more unstable sleep (increase in WP relative to pre-noise baseline ranging from +29.5% at 45 dB to +38.3% at 65 dB; type III effect p < 0.0001). Sleep depth decreased dynamically with increasing noise level, peaking when L_AS,max was highest. This change in WP was stronger and occurred more quickly for events where the noise onset was more rapid (road and rail) compared to more gradually time-varying noise (aircraft). Sleep depth did not immediately recover to pre-noise WP, leading to decreased sleep stability across the night compared to quiet nights, which was greater with an increasing number of noise events (standardized β = 0.053, p = 0.003). Further, WP was more sensitive to noise than classical arousals. Results demonstrate the usefulness of WP as a measure of the effects of external stimuli on sleep, and show WP is a more sensitive measure of noise-induced sleep disruption than traditional methods of sleep analysis.

Evaluation of noise barriers based on geometries and materials: a review

The acoustical properties of a barrier are highly dependent on the physical properties of the material and the internal structure of the material. The acoustical material can curtail the quality of sound or enhance the dispersion, depending on the application being considered. The efficient acoustic performance of noise barriers possessing different shapes and materials including waste materials is reviewed for field implementation to achieve the low-cost sustainable noise barrier application in the Indian context. The review analysis of research papers demonstrates that the acoustic performance of barriers is dependent on different shapes, materials, and textures as well as onsite geometry. Based on the review study, T-shaped barriers with a soft top surface are found to be efficient at noise attenuation. For transparent barriers, perceived loudness and noise annoyance are assessed lower than that for opaque barriers and utilization of waste materials viz. plastic, rubber, bottom coal ash, etc. gives high noise attenuation along with low-cost efficiency. Noise pollution levels are high from prescribed noise limits in most of the Indian metropolitan cities. The Indian government is working on mitigation strategies of noise pollution as well as abiding laws regarding noise standards for the zone (residential, industrial, commercial, and silences) wise. In contrast, some communities which are adjacent to roads are suffering from high noise levels in the ambience. Therefore, it requires a coherent strategy for long-term measures intended at minimizing exposure of noise hence providing much more comfort to live, work, and shop near high-traffic roads. Noise barriers are highly beneficial in mitigating the emitted noise from the traffic.

Home environment and noise disturbance in a national sample of multi-family buildings in Sweden-associations with medical symptoms

BACKGROUND

Poor acoustic conditions at home can have negative health impact. The aim was to investigate home environment factors and medical symptoms associated with noise disturbance.

METHODS

All adults (≥18 y) registered in selected apartments in Sweden were invited to participate in a questionnaire survey including medical questions and personal factors. Totally 5775 adults participated (response rate 46%). Information on home environment was obtained through an indoor environment questionnaire. Two-level logistic regression models (individual, municipality) were performed to estimate associations.

RESULTS

Totally 11.9% reported noise disturbance in general at home. Noise disturbance from voice/radio/TV/music/similar sounds from neighbours (13.2%), scraping sound/footsteps/thumping from neighbours (16.5%) and road traffic (16.1%) were common. Younger age and smoking were related to more noise disturbance and more medical symptoms. Noise disturbance was related to tiredness, headache and difficulty concentrating (OR = 1.70-8.19). Renting the apartment (OR = 2.53) and living above ground floor (OR = 1.37) were related to more noise disturbance in general. Living in newer buildings (constructed from 1986 to 2005) was related to less noise disturbance in general (OR = 0.40-0.59). A warmer climate (OR = 1.95), higher municipality population density (OR = 1.24), a longer living time (OR = 1.34), construction year (1961-1975) (OR = 2.42), renting (OR = 1.80-2.32), living above ground floor (OR = 1.45) and having a bathroom fan (OR = 1.84) were associated with increased noise disturbance from neighbours. Factors associated with increased noise disturbance from installations or ventilation/fans/heat pumps included a warmer climate, higher municipality population density, construction year (1961-1995), renting and any mechanical ventilation. Higher municipality population density, construction year (especially 1961-1985) and renting were associated with more noise disturbance from traffic (OR = 1.77-3.92). Renting the apartment (OR = 1.73) and living above ground floor (OR = 1.60) were related to more severe traffic noise disturbances. Noise disturbance in general was partly a mediator of the effects of old buildings, renting the apartment and lack of mechanical ventilation on medical symptoms (% of total effect mediated by noise disturbance: 19-44.8%).

CONCLUSIONS

Noise disturbance can be associated medical symptoms. Younger age, smoking, a warmer climate, higher municipality population density and different building factors (e.g. renting the apartment, construction period 1961-1985) can be associated with noise disturbance.

Association of road traffic noise exposure and prevalence of coronary artery disease: A cross-sectional study in North India

Epidemiological studies have established that noise from transportation sources exceeding the safe limits elevates the risk for cardiovascular diseases. The results however have remained heterogeneous. The present study was conducted to investigate the association between road traffic noise exposure and prevalence of coronary artery disease besides sub-group analysis was performed for identifying the most susceptible population. Traffic noise exposure was measured using the L_den metric in both continuous and categorical forms. A cross-sectional study was performed and information about sociodemographic, lifestyle, and health-related factors was collected. Noise level < 60 dB(A) representing the quiet areas was used as the reference group. Univariate and multivariate logistic regressions were performed to estimate the odds for self-reported coronary artery disease concerning road traffic noise after adjusting for confounding variables. The residents living in noisy areas were found to have a 2.25 times higher risk per 5 dB(A) increment in the noise levels (95% CI = 1.38 to 3.67). Males were at a higher risk of CAD (OR = 2.61; 95% CI = 1.84 to 3.72) as compared to females (OR = 2.07; 95% CI = 1.37-3.13). The subgroup analysis revealed that being sensitive to noise, belonging to a higher age group, reporting higher stress levels, and poor sleep quality were associated with higher risk. The study also provides evidence that exposure to noise levels greater than 60 dB(A) is associated with the prevalence of coronary artery disease in adults.

Long-term residential exposure to air pollution is associated with hair cortisol concentration and differential leucocyte count in Flemish adolescent boys

BACKGROUND

Exposure to air pollution and traffic noise are associated with adverse health outcomes in adolescents. Chronic endocrine stress and systemic inflammation have been hypothesized to underlie the adverse health effects. Simultaneous assessment of inflammation and chronic endocrine stress in epidemiological studies is lacking. The aim of the study was to investigate biomarkers of chronic endocrine stress and inflammation in relation to long-term residential exposure to air pollution and traffic noise in adolescents.

METHODS

In Flemish adolescents (14-15 years), we determined hair cortisol concentration (HCC) as a chronic stress biomarker in 3-cm scalp-near hair sections (n = 395), and leucocyte and leucocyte subtype counts (neutrophils, monocytes, lymphocytes) as inflammatory biomarkers in peripheral blood (n = 385). Daily particulate matter (PM_2.5, PM₁₀), nitrogen dioxide (NO₂) and black carbon (BC) concentrations were modelled at the residential address and averaged over 3-month and 1-year periods prior to sampling. Residential traffic noise level was estimated and classified in 5 dB intervals. Sex-specific associations between residential exposures and effect biomarkers were studied using linear regression models, adjusted for a priori selected covariates.

RESULTS

In boys, HCC increased with a factor 1.30 (95% CI: 1.10, 1.54) for an increase in 1-year mean NO₂ from the 25th to 75th percentile (p75/p25), after adjustment for age, BMI, personal and neighborhood socioeconomic status. The corresponding estimate for PM₁₀ was 1.24 (95% CI: 1.02, 1.51). Total leucocyte count in boys, adjusted for the aforementioned covariates and recent health complaints, was positively associated with PM_2.5, PM₁₀, NO₂ and BC. In particular, the neutrophil count increased with a factor 1.11 (95% CI: 1.03, 1.19) for a (p75/p25)-factor increase in 1-year mean BC, corresponding estimates for PM_2.5, PM₁₀ and NO₂ were 1.10 (95% CI: 1.01, 1.19), 1.10 (95% CI: 1.01, 1.20) and 1.08 (95% CI: 1.00, 1.16). Lymphocyte count increased with a factor 1.05 (95% CI: 1.01, 1.10) for a (p75/p25)-factor increase in 1-year mean NO₂. Similar results were observed for 3-month mean exposures. Results were robust to adjustment for recent air pollution exposure. In girls, air pollutants were not associated with HCC or differential leucocyte count. Residential traffic noise level was not associated with HCC or leucocyte counts in boys nor girls.

CONCLUSIONS

Long-term residential exposure to air pollutants was positively associated with chronic endocrine stress and inflammation in adolescent boys, not in girls. This study may contribute to a better understanding of the early pathophysiological changes that may underlie adverse health effects of air pollution exposure in adolescents.

Transportation noise and risk for colorectal cancer: a nationwide study covering Denmark

PURPOSE

Few studies have suggested that traffic noise is a risk factor for cancer, but evidence is inconclusive. We aimed to investigate whether road traffic and railway noise are associated with risk of colorectal cancer.

METHODS

We obtained address history for all 3.5 million people above 40 years of age and living in Denmark for the period 1990-2017 and estimated road traffic and railway noise (L_den) at the most and least exposed facades of all addresses as well as air pollution (PM_2.5). During follow-up (2000-2017), 35,881 persons developed colon cancer and 19,755 developed rectal cancer. Information on individual and area-level demographic and socioeconomic variables was collected from Danish registries. We analyzed data using Cox proportional hazards models, including traffic noise as time-varying 10-year average exposure.

RESULTS

Exposure to road traffic noise at the most exposed façade was associated with an incidence rate ratio and 95% confidence interval for proximal colon cancer of 1.018 (0.999-1.038) per 10 dB higher noise. We observed no associations for road traffic noise at the least exposed façade or for railway noise in relation to proximal colon cancer. Also, we found no association between road traffic or railway noise and risk for distal colon cancer or rectal cancer.

CONCLUSION

Traffic noise did not seem associated with higher risk for colorectal cancer, although the suggestion of a slightly higher risk of proximal colon cancer following exposure to road traffic noise warrants further research.

Modelling traffic noise in a wide gradient interval using artificial neural networks

As classical traffic noise prediction models lack a deeper consideration of the impact of the gradient, the characteristics of longitudinal gradients from multiple roads were collected as data in the mountain city of Chongqing county, which was chosen as the entry point, to study the noise characteristics for a wide range of road gradients and to build a traffic noise prediction model based on artificial neural networks (ANNs). The field data consisted of traffic volumes, heavy-vehicle ratios, average vehicle speeds, road gradients, and corresponding equivalent sound pressure levels. An optimal ANN model was determined and compared with two classical models. The results demonstrated that a one-hidden-layer ANN model was suitable for traffic noise prediction in mountain cities and presented better predictive performance than the conventional models. The best-performing ANN model yielded a determination coefficient of 0.9447 and a mean-squared error of 0.2708 dBA. Moreover, this study confirmed that road gradients were significant for constructing traffic noise prediction models.

Modelling road traffic Noise under heterogeneous traffic conditions using the graph-theoretic approach

A traffic noise system involves several subsystems like road traffic subsystem, human subsystem, environment subsystem, traffic network subsystem, and urban prosperity subsystem. The study's main aim was to develop road traffic noise models using a graph theory approach involving the parameters related to road traffic subsystem. The road traffic subsystem variables selected for the modeling purposes included vehicular speed, traffic volume, carriageway width, number of heavy vehicles, and number of honking events. The interaction of the selected variables considered in the form of permanent noise function is given in the matrix form. Eigenvalues and corresponding eigenvectors are calculated for removing any human judgmental error. The permanent noise function matrix was then updated using the eigenvectors, which was ultimately utilized for obtaining the permanent noise index. Data regarding the selected variables were collected for three months, and the noise parameters included in the study were equivalent noise level (Leq,1h), maximum noise level (L10,1h), and background noise level (L90,1h). A logarithmic transformation was applied to the permanent noise index and linear regression models were developed for Leq,1h , L90,1h , and L10,1h respectively. The models were validated using the data collected from the same locations for nine months. The models were found to provide satisfactory results, although the results were somewhat overestimated. The method can prove beneficial for estimating future noise levels, given the expected changes in values for the independent variables considered in the study.

Does exposure to noise pollution influence the incidence and severity of COVID-19?

Research that analyzes the effect of different environmental factors on the impact of COVID-19 focus primarily on meteorological variables such as humidity and temperature or on air pollution variables. However, noise pollution is also a relevant environmental factor that contributes to the worsening of chronic cardiovascular diseases and even diabetes. This study analyzes the role of short-term noise pollution levels on the incidence and severity of cases of COVID-19 in Madrid from February 1 to May 31, 2020. The following variables were used in the study: daily noise levels averaged over 14 days; daily incidence rates, average cumulative incidence over 14 days; hospital admissions, Intensive Care Unit (ICU) admissions and mortality due to COVID-19. We controlled for the effect of the pollutants PM10 and NO2 as well as for variables related to seasonality and autoregressive nature. GLM models with Poisson regressions were carried out using significant variable selection (p < 0.05) to calculate attributable RR. The results of the modeling using a single variable show that the levels of noise (leq24 h) were related to the incidence rate, the rate of hospital admissions, the ICU admissions and the rate of average cumulative incidence over 14 days. These associations presented lags, and the first association was with incidence (lag 7 and lag 10), then with hospital admissions (lag 17) and finally ICU admissions (lag 22). There was no association with deaths due to COVID-19. In the results of the models that included PM10, NO2, Leq24 h and the control variables simultaneously, we observed that only Leq24 h went on to become a part of the models using COVID-19 variables, including the 14-day average cumulative incidence. These results show that noise pollution is an important environmental variable that is relevant in relation to the incidence and severity of COVID-19 in the Province of Madrid.

Comparison of Road Traffic Noise prediction models: CNOSSOS-EU, Nord2000 and TRANEX

Road traffic noise is the most pervasive source of ambient outdoor noise pollution in Europe. Traffic noise prediction models vary in parameterisation and therefore may produce different estimates of noise levels depending on the geographical setting in terms of emissions sources and propagation field. This paper compares three such models: the European standard, Common Noise Assessment Methods for the EU Member States (hereafter, CNOSSOS), Nord2000 and Traffic Noise Exposure (TRANEX) model based on the UK methodology, in terms of their source and propagation characteristics. The tools are also compared by analysing estimated noise (L_Aeq) from CNOSSOS, Nord2000 (2006 version), and TRANEX for more than one hundred test cases (N = 111) covering a variety of source and receiver configurations (e.g. varying source to receiver distance). The main aim of this approach was to investigate the potential pattern in differences between models' performance for certain types of configurations. Discrepancies in performance may thus be linked to the differences in parameterisations of the CNOSSOS, Nord2000, and TRANEX (e.g. handling of diffraction, refraction). In most cases, both CNOSSOS and TRANEX reproduced L_Aeq levels of Nord2000 (2006 version) within three to five dBA (CNOSSOS: 87%, TRANEX: 94%). The differences in L_Aeq levels of CNOSSOS, compared to Nord2000, can be related to several shortcomings of the existing CNOSSOS algorithms (e.g. ground attenuation, multiple diffractions, and mean ground plane). The analyses show that more research is required in order to improve CNOSSOS for its implementation in the EU. In this context, amendments for CNOSSOS proposed by an EU Working Group hold significant potential. Overall, both CNOSSOS and TRANEX produced similar results, with TRANEX reproducing Nord2000 L_Aeq values slightly better than the CNOSSOS. The lack of measured noise data highlights one of the significant limitations of this study and needs to be addressed in future work.

An observation of the impact of CoViD-19 recommendation measures monitored through urban noise levels in central Stockholm, Sweden

Sweden stands out among the other European countries by the degree of restrictive measures taken towards handling the 2019 coronavirus outbreak, associated with the CoViD-19 pandemic. While several governments have imposed a nationwide total or partial lockdown in order to slow down the spread of the virus, the Swedish government has opted for a recommendation-based approach together with a few imposed restrictions. In the present contribution, the impact of this strategy will be observed through the monitored variation of the city noise levels during the associated period. The data used are recorded during a campaign of over a full year of noise level measurements at a building façade situated in a busy urban intersection in central Stockholm, Sweden. The noise level reductions, observed during the period of restrictions, are shown to be comparable to those found for the two most popular public holidays in Sweden with a peak reduction occurring during the first half of April 2020. Contrary to what has been recently discussed in public media, the spread of the virus, the recommendations, and the restrictions imposed during the ongoing pandemic clearly have had a significant effect on the transport and other human-related activities in Stockholm. In this unique investigation, the use of distributed acoustic sensors has thus shown to be a viable solution not only to enforce regulations but also to monitor the effectiveness of their implementation.

Traffic noise prediction model of an Indian road: an increased scenario of vehicles and honking

Noise is considered as an underrated and underemphasized pollutant in contrast to other pollutants of the environment. Due to the non-acute response of health effects, people are not vigilant towards consequences regarding noise pollution. The expansion of the transportation industry is contributing towards the increment in the public and private vehicular volume which causes an increment in noise pollution. For evaluation of respective scenario, the research study has been conducted on one of the minor roads of Nagpur, India; for 2 years, viz., 2012 and 2019. The study concludes an increment of 5-6 dB(A) in noise level, 4-6 times in honking, and 1.7 times in traffic volume. The study confirms increment in sound pressure by 65.9% and 81.9% for the year 2012 and 2019 during morning and evening sessions, respectively. Noise prediction model has also been developed for the abovementioned years, using multiple regression analysis, considering traffic volume, honking, and speed against noise equivalent level. Honking has been further characterized into honk by light and medium category vehicles as acoustical properties of horns vary with respect to category of vehicle and introduced into the noise prediction model. Noise prediction model for 2019 has predicted the noise level in a range of - 1.7 to + 1.4 dB (Leq) with 84% of observations in the range of - 1 to + 1 dB (Leq), when compared with observed Leq on the field. For proper management of noise pollution, a noise prediction model is essentially needed so that the noise level can be anticipated, and accordingly, measures can be outlined and executed. This increased noise level has serious impacts on human hearing capacity and overall health. Accordingly, noise mitigation preventive measures are recommended to control traffic noise in the urban environment.

The association between road traffic noise and myocardial infarction: A systematic review and meta-analysis

This systematic review and meta-analysis study aimed to investigate the association between exposure to road traffic noise (RTN) and myocardial infarction (MI). Of 681 studies found by searching in databases, including Scopus, Web of Science, Embase, and PubMed on November 29, 2019, the number of 13 studies, including seven cohort, five case-control, and one cross-sectional studies with 1,626,910 participants and 45,713 cases of MI was included. The pooled relative risk (RR) and 95% confidence interval (CI) of MI were calculated using a random-effect model across studies. Heterogeneity measures by reporting the I-square index. Subgroup analysis according to the designs and sensitivity analysis based on the Jackknife approach was performed. We observed in the eight studies the association was investigated in different noise exposure groups and in the 10 studies (including two conference papers) the risk of MI was provided per specific unit increment of RTN. We ran two independent types of meta-analyses involving a categorical analysis (comparing the highest and the lowest category of noise exposure groups) and an exposure-response analysis (the risk of MI per 10-dB increment of RTN). The pooled RR (95% CI) of MI for the categorical and exposure-response meta-analyses was calculated 1.03 (0.93, 1.13) and 1.02 (1.00, 1.05), respectively. For both types of meta-analyses, subgroup analysis indicates a significant association in the studies with case-control and cross-sectional designs but not cohort studies. For the exposure-response meta-analysis, a significantly greater risk of MI was observed after excluding the two conference papers (RR = 1.03 and 95% CI = 1.00, 1.05) and by further excluding the studies provided originally the risk of MI only for the categorical analysis (RR = 1.02 and 95% CI = 1.01, 1.03). We did not show a significant publication bias across studies. In conclusion, our study suggests a significant odds of association between exposure to RTN and the risk of MI.

[Adverse health effects due to environmental noise exposure in urban areas]

Environmental noise is a great burden for the population in Germany, especially in urban areas. People are often exposed not only to one but several noise sources. Long-term exposure to environmental noise can have several and severe adverse effects on human health, such as noise annoyance, sleep disturbances, ischaemic heart disease and depression. Additional burdens arise from multiple exposure to particulate matter or air pollutants. The current article describes the relevant adverse health effects due to long-term environmental noise exposure, discusses the challenges of environmental noise in urban areas different and introduces measures and instruments to abate environmental noise.

The spatial relationship between traffic-related air pollution and noise in two Danish cities: Implications for health-related studies

Air pollution and noise originating from urban road traffic have been linked to the adverse health effects e.g. cardiovascular disease (CVD), although their generation and propagation mechanisms vary. We aimed to (i) develop a tool to model exposures to air pollution and noise using harmonized inputs based on similar geographical structure (ii) explore the relationship (using Spearman's rank correlation) of both pollutions at residential exposure level (iii) investigate the influence of traffic speed and Annual Average Daily Traffic (AADT) on air-noise relationship. The annual average (2005) air pollution (NO_x, NO₂, PM₁₀, PM_2.5) and noise levels (L_day, L_eve, L_night, L_den, L_Aeq,24h) are modelled at address locations in Copenhagen and Roskilde (N = 11,000 and 1500). The new AirGIS system together with the Operational Street Pollution Model (OSPM®) is used to produce air pollution estimates. Whereas, noise is estimated using Common Noise Assessment Methods in the EU (CNOSSOS-EU, hereafter CNOSSOS) with relatively coarser inputs (100 m CORINE land cover, simplified vehicle composition). In addition, noise estimates (L_day, L_eve, L_night) from CNOSSOS are also compared with noise estimates from Road Traffic Noise 1996 (RTN-96, one of the Nordic noise prediction standards). The overall air-noise correlation structure varied significantly in the range |r_S| = 0.01-0.42, which was mainly affected by the background concentrations of air pollution as well as non-traffic emission sources. Moreover, neither AADT nor traffic speed showed substantial influence on the air-noise relationship. The noise levels estimated by CNOSSOS were substantially lower, and showed much lower variation than levels obtained by RTN-96. CNOSSOS, therefore, needs to be further evaluated using more detailed inputs (e.g. 10 m land cover polygons) to assess its feasibility for epidemiological noise exposure studies in Denmark. Lower to moderate air-noise correlations point towards significant potential to determine the independent health effects of air pollution and noise.

Effects of adding natural sounds to urban noises on the perceived loudness of noise and soundscape quality

Introducing pleasant natural sounds to mask urban noises is an important soundscape design strategy to improve acoustic comfort. This study investigates the effects of signal-to-noise ratio (SNR) between natural sounds (signal) and the target noises (noise) and their temporal characteristics on the perceived loudness of noise (PLN) and overall soundscape quality (OSQ) through a laboratory experiment. Two types of urban noise sources (hydraulic breaker and traffic noises) were set to A-weighted equivalent sound pressure levels (SPL) of 55, 65, and 75 dB and then augmented with two types of natural sounds (birdsong and stream), across a range of SNRs. Each acoustic stimulus was a combination of noise and natural sound at SNRs from -6 to 6 dB. Averaged across all cases, the subjective assessment of PLN showed that augmenting urban noise separately with the two natural sounds reduced the PLN by 17.9%, with no significant differences found between the birdsong and stream sounds. Adding natural sounds increased the OSQ by on average 18.3% across the cases, but their effects gradually decreased as the noise level increased. The OSQ of the birdsong and stream sounds were similar for traffic noise, whereas the stream sound was rated higher than the birdsong for the breaker noise. The results suggest that increasing the dissimilarity in temporal structure between the target noise and natural sounds could enhance the soundscape quality. Appropriate SNRs were explored considering both PLN and OSQ. The results showed that the SNR of -6 dB was desirable when the A-weighted SPL of the noise rose to 75 dB.

Short-term effects of traffic noise on suicides and emergency hospital admissions due to anxiety and depression in Madrid (Spain)

Studies show a relationship between some mental illnesses and suicides and different environmental variables such as air pollution, characterized by stress at the neuropsychological level. Despite the fact that traffic noise is also a powerful neurological stressor, studies that relate traffic noise to these mental disorders are practically non-existent. The objective is to analyze the short-term impact that chemical air pollution, traffic noise and thermal extremes have on emergency hospital admissions due to anxiety, dementia and suicides in the city of Madrid. This ecological, longitudinal study uses generalized linear models with Poisson link to analyze the short-term impact of the average daily concentrations of chemical pollutants (NO₂, PM₁₀, PM_2.5, O₃), noise pollution indicators (Leq_day, Leq_night and Leq_24h) and temperatures during heat waves (T_heat) and cold waves (T_cold) on daily admissions to emergency services in the city of Madrid from 2010 to 2013 due to anxiety (ICD-10: F32), depression (ICD-10: F40-F42) and suicide (ICD-10: X60-X84). The results show no association between any of the chemical pollutants considered and the dependent variables studied. On the contrary, the values of Leq_day are associated with the three variables analyzed in lag 0 for the cases of anxiety and depression and in lag 1 for suicides, with RR: 1.20 (IC95% 1.14 1.26), RR: 1.11 (IC95% 1.06 1.16) and RR: 1.17 (IC95% 1.05 1.30), respectively, for increases of 1 dB(A) in the values of Leq_day. An association was also found between T_cold and admissions for anxiety in lag 9 with RR: 1.62 (IC95% 1.18 2.22) for increases of 1 °C in the values of T_cold. Traffic noise can be considered an important risk factor related to the illnesses and anxiety and depression and for suicides in the city of Madrid, although new studies are needed to support the findings shown here.

High-resolution assessment of road traffic noise exposure in Denmark

Recent studies show associations between transportation noise and various diseases. However, selection bias remains an inherent limitation in many cohort studies. In this study, we aimed to model road traffic noise exposure across the entire Danish population and investigate its distribution in relation to area-level socioeconomic indicators and green space. Based on the Nordic prediction method, we estimated road traffic noise for all Danish residential addresses, in total 2,761,739 addresses, for the years 1995, 2000, 2005, 2010, and 2015 at the most and least exposed façades. Area-level sociodemographic variables encompassing education, income, and unemployment were collected and residential green within a 150 m radius buffer at the address level was estimated using high-resolution national land use classification data. Median levels of noise at both the most and least exposed facades across Denmark increased slightly from 1995 to 2015. Correlations between most and least exposed façades varied based on population density and building type, with the highest correlations between the most and least exposed façades found for semidetached homes and lowest for multistory buildings. Increasing median noise levels were observed across increasing levels of higher education, lower income, and higher unemployment. A decreasing trend in median noise levels with increasing levels of green space was observed. In conclusion, we showed that it is feasible to estimate nationwide, address-specific exposure over a long time-period. Furthermore, the low correlations found between most and least exposed façade for multistory buildings, which characterize metropolitan centers, suggests that the most exposed façade estimation used in most previous studies and predicts exposure at the silent façade relatively poorly.

Transportation noise impairs cardiovascular function without altering sleep: The importance of autonomic arousals

AIMS

Chronic exposure to nocturnal transportation noise has been linked to cardiovascular disorders with sleep impairment as the main mediator. Here we examined whether nocturnal transportation noise affects the main stress pathways, and whether it relates to changes in the macro and micro structure of sleep.

METHODS AND RESULTS

Twenty-six young healthy participants (12 women, 24.6 ± 0.7 years, mean ± SE) spent five consecutive 24-h days and one last morning in the laboratory. The first (baseline) and last (recovery) nights comprised a quiet ambient scenario. In-between, four different noise scenarios (low/medium/high intermittent road or rail scenarios with an identical equivalent continuous sound level of 45 dB) were randomly presented during the 8-h nights. Participants felt more annoyed from the transportation noise scenarios compared to the quiet ambient scenario played back during the baseline and recovery nights (F_5,117 = 10.2, p < 0.001). Nocturnal transportation noise did not significantly impact polysomnographically assessed sleep macrostructure, blood pressure, nocturnal catecholamine levels and morning cytokine levels. Evening cortisol levels increased after sleeping with highly intermittent road noise compared to baseline (p = 0.002, noise effect: F_4,83 = 4.0, p = 0.005), a result related to increased cumulative duration of autonomic arousals during the noise nights (F_5,106 = 3.4, p < 0.001; correlation: r_pearson = 0.64, p = 0.006).

CONCLUSION

Under controlled laboratory conditions, highly intermittent nocturnal road noise exposure at 45 dB increased the cumulative duration of autonomic arousals during sleep and next-day evening cortisol levels. Our results indicate that, without impairing sleep macrostructure, nocturnal transportation noise of 45 dB is a physiological stressor that affects the hypothalamic-pituitary-adrenal axis during the following day in healthy young good sleepers.

Artificial intelligence based ensemble model for prediction of vehicular traffic noise

Vehicular traffic noise is the main source of noise pollution in major cities around the globe. A reliable and accurate method for the estimation of vehicular traffic noise is therefore essential for creating a healthy noise-free environment. In this study, 2 linear (simple average and weighted average) and 2-nonlinear (neural network and neuro-fuzzy) ensemble models were developed by combining the outputs of three Artificial Intelligence (AI) based non-linear models; Adaptive Neuro Fuzzy Inference System (ANFIS), Feed Forward Neural Network (FFNN), Support Vector Regression (SVR) and one Multilinear regression (MLR) model to enhance the performance of the single black box models in predicting vehicular traffic noise of Nicosia city, North Cyprus. In this way, first a nonlinear sensitivity analysis was applied to select the most relevant and dominant input parameters of the traffic data obtained from 12 observation points in the study area. The most dominant parameters in order of their importance were determined to be number of cars, number of van/pickups, number of trucks, average speed and number of buses. Classifying the number of vehicles into five categories before feeding the traffic data into the AI models was observed to improve performance of the single models up to 29% in the verification phase. Out of the four ensembles models developed, the nonlinear ANFIS ensemble was found to be the most robust by improving the performance of ANFIS, FFNN, SVR and MLR models in the verification stage by 11%, 19%, 21% and 31%, respectively.

Surrounding green, air pollution, traffic noise exposure and non-accidental and cause-specific mortality

BACKGROUND

Most previous studies that investigated associations of surrounding green, air pollution or traffic noise with mortality focused on single exposures.

OBJECTIVES

The aim of this study was to evaluate combined associations of long-term residential exposure to surrounding green, air pollution and traffic noise with total non-accidental and cause-specific mortality.

METHODS

We linked a national health survey (Public Health Monitor, PHM) conducted in 2012 to the Dutch longitudinal mortality database. Subjects of the survey who were 30 years or older on 1 January 2013 (n = 339,633) were followed from 1 January 2013 till 31 December 2017. We used Cox proportional hazard models to evaluate associations of residential surrounding green (including the average Normalized Difference Vegetation Index (NDVI) in buffers of 300 m and 1000 m), annual average air pollutant concentrations (including particulate matter (PM₁₀, PM_2.5), nitrogen dioxide (NO₂)) and traffic noise with non-accidental, circulatory disease, respiratory disease, lung cancer and neurodegenerative disease mortality.

RESULTS

We observed 26,886 non-accidental deaths over 1.627.365 person-years of follow-up. Surrounding green, air pollution and traffic noise exposure were not significantly associated with non-accidental or cause-specific mortality. For non-accidental mortality, we found a hazard ratio (HR) of 0.99 (0.98, 1.01) per IQR increase in NDVI 300 m, a HR of 0.99 (95% CI: 0.97, 1.01) per IQR increase in NO₂, a HR of 0.98 (0.97, 1.00) per IQR increase in PM_2.5 and a HR of 0.99 (95% CI: 0.97, 1.01) per IQR increase in road-traffic noise. Analyses restricted to non-movers or excluding subjects aged 85+ years did not change the findings.

CONCLUSION

We found no evidence for associations of long-term residential exposures to surrounding green, air pollution and traffic noise with non-accidental or cause-specific mortality in a large population based survey in the Netherlands, possibly related to the relatively short follow-up period.

An innovative approach of urban noise monitoring using cycle in Nagpur, India

Noise is one of the most significant sources of environmental pollution in metro cities. Traffic noise plays an important role to contribute to ambient noise pollution. Noise pollution monitoring was carried out using sound level meter mounted on the cycle with the help of mould fixed on it. Cycle is a noiseless mode of transport and therefore, it was used for noise monitoring over 700 locations in Nagpur City. Noise levels were recorded at each location for 5 min during peak rush hours of traffic in the morning and in the evening at an interval of 1 s leading to around 300 readings each. Noise indices like L_eq, L₉₀, L₁₀, L_max and L_min were calculated for noise level data analysis. TNI was also determined for analysis of traffic noise on intersections of roads. Equivalent noise levels were transferred into the Geographic Information System (GIS) and spatial analysis tool was used to create spatial and strategic noise maps. Based on the maps, it is revealed that noise levels are exceeded all over the city with respect to ambient noise standards. It was experienced that intersections of roads during peak rush time are very noisy due to honking. The study recommends the noise monitoring through cycle-mounted sound level meter since it covers unapproachable sites, more coverage in the city that helps in identifying hotspot area of concern for noise abatement strategies and planning.

Residential surrounding green, air pollution, traffic noise and self-perceived general health

Self-perceived general health (SGH) is one of the most inclusive and widely used measures of health status and a powerful predictor of mortality. However, only a limited number of studies evaluated associations of combined environmental exposures on SGH. Our aim was to evaluate associations of combined residential exposure to surrounding green, air pollution and traffic noise with poor SGH in the Netherlands. We linked data on long-term residential exposure to surrounding green based on the Normalized Difference Vegetation Index (NDVI) and a land-use database (TOP10NL), air pollutant concentrations (including particulate matter (PM₁₀, PM_2.5), and nitrogen dioxide (NO₂)) and road- and rail-traffic noise with a Dutch national health survey, resulting in a study population of 354,827 adults. We analyzed associations of single and combined exposures with poor SGH. In single-exposure models, NDVI within 300 m was inversely associated with poor SGH [odds ratio (OR) = 0.91, 95% CI: 0.89, 0.94 per IQR increase], while NO₂ was positively associated with poor SGH (OR = 1.07, 95% CI: 1.04, 1.11 per IQR increase). In multi-exposure models, associations with surrounding green and air pollution generally remained, but attenuated. Joint odds ratios (JOR) of combined exposure to air pollution, rail-traffic noise and decreased surrounding green were higher than the odds ratios of single-exposure models. Studies including only one of these correlated exposures may overestimate the risk of poor SGH attributed to the studied exposure, while underestimating the risk of combined exposures.

A nuanced approach to the Environmental Noise Guidelines for the European Region related to traffic noise

The recently published guide "Environmental Noise Guidelines for the European Region" provides evidence of the non-auditory effects of environmental noise on population health. This guide reflects the current state of knowledge about how traffic noise affects cardiovascular diseases among others. Despite the valuable contributions of this document in terms of current knowledge, there are different points of improvement in terms of implementation of the guide for all Europe. The studies related to Southern Europe have little presence, probably due to the lack of research in this issue, it means, there are few studies that evaluate short-term effects of noise on morbid-mortality. In this sense, it would be advisable to include the most recently published papers on the subject. Due to the aforementioned, the noise exposure assessment should be considerate at the short and long term to evaluate completely the noise effects on health, specially taking into account the characteristics of countries in which leisure-related noise is especially problematic.

Nocturnal noise and habitat homogeneity limit species richness of owls in an urban environment

Habitat loss and fragmentation are listed among the most significant effects of urbanization, which is regarded as an important threat to wildlife. Owls are the top predators in most terrestrial habitats, and their presence is a reliable indicator of ecosystem quality and complexity. However, influence of urbanization on owl communities, anthropogenic noise in particular, has not been investigated so far. The aim of this study was to identify the role of noise and landcover heterogeneity in the species richness of owl assemblage in the urban ecosystem. Owls were surveyed in the city of Kraków (southern Poland) on 65 randomly selected sample plots (1 km²). The area of main landcover types, landcover diversity index, mean size of landcover patch, and nocturnal noise level were defined within the sample plots and correlated with owl species richness. Five owl species were recorded in the study area with forests as the dominant landcover type for Tawny and Ural owls, grasslands for Long-eared and Barn owls, and gardens for Little owls. In total, 52% of sample plots were occupied by at least one species (1-3 species per plot). The number of owl species was positively correlated with landcover diversity index and negatively correlated with nocturnal noise emission. This study demonstrates that species richness of owls in urban areas may be shaped by landcover heterogeneity and limited by noise intensity. This indicates that noise changes top predator assemblage, which in consequence may disturb predator-prey interactions within human-transformed habitats.