Acousto-optic measurement of sound (AOMoS) has been widely utilized in various acoustic studies owing to its noninvasive nature. However, the presence of significant measurement noise often degrades ...the acousto-optic signals and thus hinders promising applications. This is partly because the characteristics of the noises in AOMoS have not been fully clarified, which prevents us from adequately predicting and controlling them. To address this challenge, we theoretically and experimentally investigate three specific measurement noises in AOMoS: optical intensity noise, optical phase noise, and environmental noise. Convenient notations for evaluating optical noises in acoustic units are provided, which make it easier to understand the AOMoS noises from an acoustic point of view. Our findings showed that among the six noise sources we investigated, optical shot noise defines the white noise floor at high frequencies while background sound noise determines the low-frequency noise spectrum. The analysis provided in this article will serve as an exhaustive guide for designing and implementing an AOMoS system with a desired noise level.
In recent years, the rapid construction of roads and railways in cities has brought convenience to urban residents, but the noise generated by the functioning of these transport infrastructures also ...affects the normal life of residents in the buildings around them. Buildings adjacent to both roads and railways are exposed to multiple traffic noises at the same time, which presents difficulties for targeted noise assessment and control. To solve this problem, this paper proposes a deep learning-based traffic noise source identification method, which feeds the time-frequency spectrum of the noise or vibration monitoring signals into the trained deep learning based model, so that the sources of noise at various moments can be identified. In addition, the performance of the proposed method was presented using noise and vibration signals monitored in Beijing, and noise evaluations for two buildings were conducted as case studies to investigate the statistical characteristics of noise caused by rail and road traffic in buildings. The result demonstrates the feasibility of the proposed method, and shows that different types of noise pollution need to be attended to on different floors in buildings adjacent to underground railways, the lower floors of the building are exposed to more significant low-frequency structural noise induced by the underground railway, while the higher floors of the building are exposed to more significant airborne noise caused by road traffic. Also, extensive areas adjacent to elevated railways are affected by airborne noise, and buildings in these areas require attention to the prevention of noise.
•A novel traffic noise identification method is proposed based on deep learning.•The feasibility of the method was verified using noises monitored in Beijing.•The ground floor of buildings near the metro is exposed to structural noise.•Extensive areas adjacent to elevated railways are affected by the airborne noise.
As the traffic and other environmental noise generating activities are growing in The Kingdom of Saudi Arabia (KSA), adverse health and other impacts are expected to develop. The management of such ...problem involves many actions, of which noise mapping has been proven to be a helpful approach. The objective of the current study was to test the adequacy of the available data in KSA municipalities for generating urban noise maps and to verify the applicability of available environmental noise mapping and noise annoyance models for KSA. Therefore, noise maps were produced for Al-Fayha District in Jeddah City, KSA using commercially available noise mapping software and applying the French national computation method "NMPB" for traffic noise. Most of the data required for traffic noise prediction and annoyance analysis were available, either in the Municipality GIS department or in other governmental authorities. The predicted noise levels during the three time periods, i.e., daytime, evening, and nighttime, were found higher than the maximum recommended levels established in KSA environmental noise standards. Annoyance analysis revealed that high percentages of the District inhabitants were highly annoyed, depending on the type of planning zone and period of interest. These results reflect the urgent need to consider environmental noise reduction in KSA national plans. The accuracy of the predicted noise levels and the availability of most of the necessary data should encourage further studies on the use of noise mapping as part of noise reduction plans.
Transportation noise is increasingly acknowledged as a cardiovascular risk factor, but the evidence base for an association with stroke is sparse.
We aimed to investigate the association between ...transportation noise and stroke incidence in a large Scandinavian population.
We harmonized and pooled data from nine Scandinavian cohorts (seven Swedish, two Danish), totaling 135,951 participants. We identified residential address history and estimated road, railway, and aircraft noise for all addresses. Information on stroke incidence was acquired through linkage to national patient and mortality registries. We analyzed data using Cox proportional hazards models, including socioeconomic and lifestyle confounders, and air pollution.
During follow-up (
), 11,056 stroke cases were identified. Road traffic noise (
) was associated with risk of stroke, with a hazard ratio (HR) of 1.06 95% confidence interval (CI): 1.03, 1.08 per 10-dB higher 5-y mean time-weighted exposure in analyses adjusted for individual- and area-level socioeconomic covariates. The association was approximately linear and persisted after adjustment for air pollution particulate matter (PM) with an aerodynamic diameter of
(
) and
. Stroke was associated with moderate levels of 5-y aircraft noise exposure (40-50 vs.
) (
; 95% CI: 0.99, 1.27), but not with higher exposure (
,
; 95% CI: 0.79, 1.11). Railway noise was not associated with stroke.
In this pooled study, road traffic noise was associated with a higher risk of stroke. This finding supports road traffic noise as an important cardiovascular risk factor that should be included when estimating the burden of disease due to traffic noise. https://doi.org/10.1289/EHP8949.
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CEKLJ, DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
In this study, six aircraft noise reduction strategies including the optimization of aircraft type, regulation of night flight number, optimization of flight procedure, modification of operating ...runway, land use planning and installation of sound insulation windows were proposed to alleviate the harmful impact of aircraft noise on the local area and population near Guangzhou Baiyun International Airport (BIA) in China. The effects of all proposed strategies except for land use planning and sound insulation windows were simulated and analyzed using CadnaA software. The results indicate that these noise reduction strategies have their own advantages and each of them can serve as an effective noise reduction measure for different applications. For instance, the replacement of noisy aircraft with low-noise aircraft can simultaneously reduce the area and population exposed to a high noise level, while the optimization of flight procedure can only reduce the population exposed under relatively low noise levels (70 ≤LWECPN ≤ 75 dB). Nevertheless, the modification of operating runway is more effective in reducing the population suffering under high noise levels (LWECPN > 85 dB). Among these strategies, reducing the number of night flights is found to be most effective in reducing the overall noise-exposed area and population. Additionally, with the assistance of noise mapping, proper land use planning was suggested according to national standards, and the installation of sound insulation windows with different sound reduction grades can be determined for different areas impacted by the aircraft noise of BIA. It is believed that the results of this study can be applied as a reference in selecting suitable noise reduction strategies to improve the acoustic environment of a specific airport.
Following the Parma Declaration on Environment and Health adopted at the Fifth Ministerial Conference (2010), the Ministers and representatives of Member States in the WHO European Region requested ...the World Health Organization (WHO) to develop updated guidelines on environmental noise, and called upon all stakeholders to reduce children's exposure to noise, including that from personal electronic devices. The WHO Environmental Noise Guidelines for the European Region will provide evidence-based policy guidance to Member States on protecting human health from noise originating from transportation (road traffic, railway and aircraft), wind turbine noise, and leisure noise in settings where people spend the majority of their time. Compared to previous WHO guidelines on noise, the most significant developments include: consideration of new evidence associating environmental noise exposure with health outcomes, such as annoyance, cardiovascular effects, obesity and metabolic effects (such as diabetes), cognitive impairment, sleep disturbance, hearing impairment and tinnitus, adverse birth outcomes, quality of life, mental health, and wellbeing; inclusion of new noise sources to reflect the current noise environment; and the use of a standardized framework (grading of recommendations, assessment, development, and evaluations: GRADE) to assess evidence and develop recommendations. The recommendations in the guidelines are underpinned by systematic reviews of evidence on several health outcomes related to environmental noise as well as evidence on interventions to reduce noise exposure and/or health outcomes. The overall body of evidence is published in this Special Issue.
This article evaluates Southall et al. (2007) in light of subsequent scientific findings and proposes revised noise exposure criteria to predict the onset of auditory effects in marine mammals. ...Estimated audiograms, weighting functions, and underwater noise exposure criteria for temporary and permanent auditory effects of noise are presented for six species groupings, including all marine mammal species. In-air criteria are also provided for amphibious species. Earlier marine mammal hearing groupings were reviewed and modified based on phylogenetic relationships and a comprehensive review of studies on hearing, auditory anatomy, and sound production. Auditory weighting functions are derived for each group; those proposed here are less flattened and closer to audiograms than the Southall et al. M-weightings. As in Southall et al., noise sources are categorized as either impulsive or non-impulsive, and criteria use multiple exposure metrics to account for different aspects of exposure. For continuous (non-impulsive) noise sources, exposure criteria are given in frequency-weighted sound exposure level (SEL, given in units relative to 1 microPa.sup.2-s or (20 microPa.sup.2)-s for water and air, respectively). Dual exposure metrics are provided for impulsive noise criteria, including frequency-weighted SEL and unweighted peak sound pressure level (SPL, given in units relative to 1 microPa or 20 microPa for water and air, respectively). Exposures exceeding the specified respective criteria level for any exposure metric are interpreted as resulting in predicted temporary threshold shift (TTS) or permanent threshold shift (PTS) onset. Scientific findings in the last decade provide substantial new insight but also underscore remaining challenges in deriving simple, broadly applicable quantitative exposure criteria for such diverse taxa. These criteria should be considered with regard to relevant caveats, recommended research, and with the expectation of subsequent revision. Key Words: hearing, marine mammals, noise exposure, TTS, PTS, weighting, criteria
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Epidemiologic studies have linked transportation noise to increased morbidity and mortality, particularly for cardiovascular outcomes. However, studies investigating metabolic outcomes such as ...diabetes are limited and have focused only on noise exposures estimated for the loudest residential façade.
We aimed to examine the influence of long-term residential exposure to transportation noise at the loudest and quietest residential façades and the risk for type 2 diabetes.
Road traffic and railway noise exposures (Lden) at the most and least exposed façades were estimated for all dwellings in Denmark during 1990-2017. Aircraft noise was estimated in 5-dB categories. Ten-year time-weighted mean noise exposures were estimated for
individuals
of age. From 2000 to 2017, 233,912 incident cases of type 2 diabetes were identified using hospital and prescription registries, with a mean follow-up of 12.9 y. We used Cox proportional hazards models adjusting for individual- and area-level covariates and long-term residential air pollution. The population-attributable fraction (PAF) was also computed.
Hazard ratios (HRs) and 95% confidence intervals (CIs) for type 2 diabetes in association with 10-dB increases in 10-y mean road traffic noise at the most and least exposed façades, respectively, were 1.05 (95% CI: 1.04, 1.05) and 1.09 (95% CI: 1.08, 1.10). Following subsequent adjustment for fine particulate matter particulate matter
in aerodynamic diameter (10-y mean), the HRs (CIs) were 1.03 (95% CI: 1.03, 1.04) and 1.08 (95% CI: 1.07, 1.09), respectively. For railway noise, the HRs per 10-dB increase in 10-y mean exposure were 1.03 (95% CI: 1.02, 1.04) and 1.02 (95% CI: 1.01, 1.04) for the most and least exposed façades, respectively. Categorical models supported a linear exposure-outcome relationship for road traffic noise and, to a lesser extent, for railway noise. Aircraft noise
was associated with a 1-4% higher likelihood of type 2 diabetes compared with those who were unexposed. We found road traffic and railway noise associated with a PAF of 8.5% and 1.4%, respectively, of the diabetes cases.
Long-term exposure to road, railway, and possibly aircraft traffic noise was associated with an increased risk of type 2 diabetes in a nationwide cohort of Danish adults. Our findings suggest that diabetes should be included when estimating the burden of disease due to transportation noise. https://doi.org/10.1289/EHP9146.
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Dostopno za:
CEKLJ, DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
The present study aims to explore the effects of noise sensitivity on psychophysiological responses to floor impact noises and road traffic noise. A standard impact source (i.e. an impact ball) and ...two real impact sources (i.e. an adult's walking and a child's running) were used to record floor impact noises, while road traffic noise was introduced as an outdoor noise stimulus. A total of 34 subjects were recruited based on their self-rated noise sensitivity and classified into low and high noise sensitivity groups. During the laboratory experiments, all the noise stimuli were presented for 5 min each, and the subjects rated their annoyance with each stimulus at the end of each session. Their physiological responses (heart rate: HR, electrodermal activity: EDA, and respiratory rate: RR) were measured throughout the experiment. The obtained noise annoyance ratings increased with increasing noise levels for all the sources, and the high noise sensitivity group exhibited higher annoyance ratings than the low noise sensitivity group. All physiological measures varied significantly with the duration of noise exposure. In particular, the EDA and RR values decreased sharply after 30 s, demonstrating strong habituation over time. Noise sensitivity was found to significantly affect physiological responses, whereas noise levels showed no significant influence.
•High noise sensitivity group exhibited higher noise annoyance than low noise sensitivity group.•Electrodermal activity and respiration rate decreased sharply after 30s, demonstrating strong habituation over time.•High noise sensitivity group showed more pronounced changes in the physiological responses.•The physiological responses were not affected by the type of noise source and the sound pressure level.
High-quality seismic data are the basis for stratigraphic imaging and interpretation, but the existence of random noise can greatly affect the quality of seismic data. At present, most understanding ...and processing of random noise still stay at the level of Gaussian white noise. With the reduction of resource, the acquired seismic data have lower signal-to-noise ratio and more complex noise natures. In particular, the random noise in the desert area has the characteristics of low frequency, non-Gaussian, nonstationary, high energy, and serious aliasing between effective signal and random noise in the frequency domain, which has brought great difficulties to the recovery of seismic events by conventional denoising methods. To solve this problem, an improved feed-forward denoising convolution neural network (DnCNN) is proposed to suppress random noise in desert seismic data. DnCNN has the characteristics of automatic feature extraction and blind denoising. According to the characteristics of desert noise, we modify the original DnCNN from the aspects of patch size, convolution kernel size, network depth, and training set to make it suitable for low-frequency and non-Gaussian desert noise suppression. Both simulation and practical experiments prove that the improved DnCNN has obvious advantages in terms of desert noise and surface wave suppression as well as effective signal amplitude preservation. In addition, the improved DnCNN, in contrast to existing methods, has considerable potential to benefit from large data sets. Therefore, we believe that it can open a new direction in the area of seismic data processing.
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