Showing papers on "Noise pollution published in 2020"

Changes in noise levels in the city of Madrid during COVID-19 lockdown in 2020

Abstract: The lockdown that Madrid has suffered during the months of March to June 2020 to try to control and minimize the spread of COVID-19 has significantly altered the acoustic environment of the city. The absence of vehicles and people on the streets has led to a noise reduction captured by the monitoring network of the City of Madrid. In this article, an analysis has been carried out to describe the reduction in noise pollution that has occurred and to analyze the changes in the temporal patterns of noise, which are strongly correlated with the adaptation of the population's activity and behavior to the new circumstances. The reduction in the sound level ranged from 4 to 6 dBA for the indicators Ld, Le, and Ln, and this is connected to a significant variation in the daily time patterns, especially during weekends, when the activity started earlier in the morning and lasted longer at midday, decreasing significantly in the afternoon.

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

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

Analysing urban traffic volumes and mapping noise emissions in Rome (Italy) in the context of containment measures for the COVID-19 disease

Abstract: This study presents the result of a traffic simulation analysis based on Floating Car Data and a noise emission assessment to show the impact of mobility restriction for COVID-19 containment on urban vehicular traffic and road noise pollution on the road network of Rome, Italy The adoption of strong and severe measures to contain the spreading of Coronavirus during March-April 2020 generated a significant reduction in private vehicle trips in the city of Rome (-646% during the lockdown) Traffic volumes, obtained through a simulation approach, were used as input parameters for a noise emission assessment conducted using the CNOSSOS-EU method, and an overall noise emissions reduction on the entire road network was found, even if its extent varied between road types

Evaluation of urban traffic noise pollution based on noise maps

Abstract: Traffic noise pollution has become a major environmental issue that plagues urban residents. The purpose of this study is to evaluate the traffic noise pollution based on noise maps. Twenty-four-hour noise maps of the Chancheng District in Foshan, China were developed for this study, and the results analyzed. The study area is divided into four types, based on the land use requirements for the acoustic environment, and the calculated noise value is compared to the noise limits of each class of the area. The average equivalent sound pressure level of the entire study area indicates the noise pollution is modest, but further analysis of the noise data in various types of areas shows a high magnitude of noise and long-lasting noise pollution near street-front buildings as well as the areas where quietness is required. It was also found that the noise level of the city is higher during off-peak hours than during rush hours, probably due to the faster speed and larger traffic volume during the off-peak hours. It is urgent to develop effective noise reduction measures to mitigate traffic noise pollution at night, based on the evaluation results.

Measuring Methods of Acoustic Properties and Influence of Physical Parameters on Natural Fibers: A Review

Abstract: Nowadays, the world becomes more contaminated due to various factors such as pollution, global warming and unhealthy human practices. In this review paper, noise pollution is taken into major conce...

Evidence of the impact of noise pollution on biodiversity: a systematic map

Abstract: Ecological research now deals increasingly with the effects of noise pollution on biodiversity. Indeed, many studies have shown the impacts of anthropogenic noise and concluded that it is potentially a threat to the persistence of many species. The present work is a systematic map of the evidence of the impacts of all anthropogenic noises (industrial, urban, transportation, etc.) on biodiversity. This report describes the mapping process and the evidence base with summary figures and tables presenting the characteristics of the selected articles. The method used was published in an a priori protocol. Searches included peer-reviewed and grey literature published in English and French. Two online databases were searched using English terms and search consistency was assessed with a test list. Supplementary searches were also performed (using search engines, a call for literature and searching relevant reviews). Articles were screened through three stages (titles, abstracts, full-texts). No geographical restrictions were applied. The subject population included all wild species (plants and animals excluding humans) and ecosystems. Exposures comprised all types of man-made sounds in terrestrial and aquatic media, including all contexts and sound origins (spontaneous or recorded sounds, in situ or laboratory studies, etc.). All relevant outcomes were considered (space use, reproduction, communication, etc.). Then, for each article selected after full-text screening, metadata were extracted on key variables of interest (species, types of sound, outcomes, etc.). Our main result is a database that includes all retrieved literature on the impacts of anthropogenic noise on species and ecosystems, coded with several markers (sources of noise, species concerned, types of impacts, etc.). Our search produced more than 29,000 articles and 1794 were selected after the three screening stages (1340 studies (i.e. primary research), 379 reviews, 16 meta-analyses). Some articles (n = 19) are written in French and all others are in English. This database is available as an additional file of this report. It provides an overview of the current state of knowledge. It can be used for primary research by identifying knowledge gaps or in view of further analysis, such as systematic reviews. It can also be helpful for scientists and researchers as well as for practitioners, such as managers of transportation infrastructure. The systematic map reveals that the impacts of anthropogenic noises on species and ecosystems have been researched for many years. In particular, some taxonomic groups (mammals, birds, fishes), types of noise (transportation, industrial, abstract) and outcomes (behavioural, biophysiological, communication) have been studied more than others. Conversely, less knowledge is available on certain species (amphibians, reptiles, invertebrates), noises (recreational, military, urban) and impacts (space use, reproduction, ecosystems). The map does not assess the impacts of anthropogenic noise, but it can be the starting point for more thorough synthesis of evidence. After a critical appraisal, the included reviews and meta-analyses could be exploited, if reliable, to transfer the already synthesized knowledge into operational decisions to reduce noise pollution and protect biodiversity.

Low-Cost Sensors for Urban Noise Monitoring Networks-A Literature Review.

Abstract: Noise pollution reduction in the environment is a major challenge from a societal and health point of view. To implement strategies to improve sound environments, experts need information on existing noise. The first source of information is based on the elaboration of noise maps using software, but with limitations on the realism of the maps obtained, due to numerous calculation assumptions. The second is based on the use of measured data, in particular through professional measurement observatories, but in limited numbers for practical and financial reasons. More recently, numerous technical developments, such as the miniaturization of electronic components, the accessibility of low-cost computing processors and the improved performance of electric batteries, have opened up new prospects for the deployment of low-cost sensor networks for the assessment of sound environments. Over the past fifteen years, the literature has presented numerous experiments in this field, ranging from proof of concept to operational implementation. The purpose of this article is firstly to review the literature, and secondly, to identify the expected technical characteristics of the sensors to address the problem of noise pollution assessment. Lastly, the article will also put forward the challenges that are needed to respond to a massive deployment of low-cost noise sensors.

Internet of Things for Noise Mapping in Smart Cities: State of the Art and Future Directions

Abstract: Noise pollution has been an issue since ancient times. Recently, this problem has been exacerbated due to rapid population growth and urbanization. Noise mapping is a strategic action plan that visualizes the long-term and real-time noise pollution of our cities, industrial sites, and other regions of interest. This article first discusses the working principle of general model-based noise mapping and the lessons learned. Then, in-depth descriptions of the technical challenges and design issues of noise mapping using mobile crowdsensing and acoustic sensor networks are presented. Finally, we provide our insights for future research directions regarding artificial intelligence assisted noise prediction, constructive interference for multimedia transmission, and simultaneous noise sensing and sound energy harvesting as well as inaudible sound attacks and defense.

Time-Series Prediction of Environmental Noise for Urban IoT Based on Long Short-Term Memory Recurrent Neural Network

Abstract: Noise pollution is one of the major urban environmental pollutions, and it is increasingly becoming a matter of crucial public concern. Monitoring and predicting environmental noise are of great significance for the prevention and control of noise pollution. With the advent of the Internet of Things (IoT) technology, urban noise monitoring is emerging in the direction of a small interval, long time, and large data amount, which is difficult to model and predict with traditional methods. In this study, an IoT-based noise monitoring system was deployed to acquire the environmental noise data, and a two-layer long short-term memory (LSTM) network was proposed for the prediction of environmental noise under the condition of large data volume. The optimal hyperparameters were selected through testing, and the raw data sets were processed. The urban environmental noise was predicted at time intervals of 1 s, 1 min, 10 min, and 30 min, and their performances were compared with three classic predictive models: random walk (RW), stacked autoencoder (SAE), and support vector machine (SVM). The proposed model outperforms the other three existing classic methods. The time interval of the data set has a close connection with the performance of all models. The results revealed that the LSTM network could reflect changes in noise levels within one day and has good prediction accuracy. Impacts of monitoring point location on prediction results and recommendations for environmental noise management were also discussed in this paper.

Deep spatio-spectral Bayesian posterior for hyperspectral image non-i.i.d. noise removal

Abstract: The noise pollution issue seriously obstructs subsequent interpretation and application of the hyperspectral image (HSI). In this work, differing from most existing HSI denoising methods ideally assumed that noise in different bands denotes independent & identically distributed (i.i.d.), we propose a novel HSI denoising approach focusing on non-i.i.d. noise removal. The presented framework collaboratively models the non-i.i.d. noise embedding within HSI and removals them under a deep spatio-spectral Bayesian posterior (DSSBP) structure. Specifically, the non-i.i.d. noise estimation, distribution and removal procedure are both executed with the model-driven based strategy and data-driven based strategy. Through blending the Bayesian variational posterior and deep convolutional neural network, the proposed method both inherits the reliability of traditional model-driven based methods for HSI noise modeling and the high efficiency of data-driven based methods for parameters learning. Simulated and real experiments in different HSIs and non-i.i.d. noise scenarios testify that the proposed DSSBP approach outperforms other existing methods for non-i.i.d. noise removal, in terms of evaluation indexes and executive efficiency.

Current State-of-the-Art and New Directions in Strategic Environmental Noise Mapping

Abstract: Environmental noise mapping has the potential to act as a powerful resource for policymakers as a decision support tool for the mitigation of the negative effects of environmental noise pollution and its impact on public health. The aim of this paper is to review current state-of-the-art developments in how the strategic noise mapping (SNM) process has progressed at the EU level since the introduction of the Environmental Noise Directive (END) in 2002. Reviewing such developments is important because of the relevance of SNM to public health. In this regard, the development of a new standardized noise calculation method (i.e. CNOSSOS-EU) is also considered, as well as the future potential for noise mapping and the impact of technology on the development of noise pollution assessment.

Assessment of noise pollution and its effects on human health in industrial hub of Pakistan

Abstract: Faisalabad is one of the major industrial cities of Pakistan, which may cause noise pollution to the local residents due to the development of robust industrial and transport systems. This study aimed at (i) mapping the noise pollution levels at various locations of Faisalabad city; (ii) comparing noise pollution levels in the morning, the afternoon, and the evening for each source; and (iii) assessing nonauditory effects of noise on human health. Two industries and 43 famous/busy locations of Faisalabad Sadar were selected to study noise pollution by using the sound level meter for the period of 24 h. A questionnaire-based survey was carried out near the sampling points to get a public perception about the health impacts of noise pollution. The measured equivalent sound pressure levels (SPLeq) were higher than the permissible limits at all the sampling locations during morning, afternoon, and evening hours. The maximum sound pressure level (SPLmax) was 102 dB inside the production unit in the afternoon at Mian Muhammad Siddiq Textile Loom industry. The average SPL was found at State Bank road (102 dB), Children’s Hospital (101 dB), Jhang Bazar (100 dB) in the afternoon and at Punjab Medical College in the evening (97 dB). Based on the survey, 94% of respondents reported headache, 76% sleeplessness, 74% hypertension, 74% physiological stress, 64% elevated blood pressure levels, and 60% dizziness due to noise. Noise pollution is higher than the standard limits and causes auditory as well as nonauditory effects on humans. The vehicles and industrial machinery should be maintained, and sound proofing and protection equipment should be provided to the workforce in order to protect them from extreme noise levels.

Usage of Microscopic Simulation to Estimate the Environmental Impact of Road Transport

Abstract: The purpose of the transport system is providing access to goods, jobs and services. However, the increase in the level of transport services provision is accompanied by negative consequences. Within the concept of sustainable development of urban transport systems, it is necessary to ensure a safe environmental load for people. Therefore, the purpose of this study is the search and testing of methods to correctly estimate the degree of environmental impact by road transport, reducing the environmental burden, and substantiating the rationality of the implementation of the proposed measures for greening transport. As research methods were used: the theory of traffic flows, simulation, computer experiment, methods of direct measurement of environmental emissions on the road segment under study. The use of simulation allows to find an acceptable solution for the volume of exhaust gases and noise pollution, by varying the parameters of the transport system objects (the configuration of the road network, the characteristics and modes of operation of the road infrastructure elements). It is shown that micromodelling is an effective approach, in which the unit of modeling is a separate vehicle. It makes possible to take into account the individual characteristics of the vehicle (current mileage, engine type, environmental safety class), which allows an estimation of the environmental impact of the vehicle fleet operating in the area. Examples of using this approach are given, computer experiments on specific sections of the road network are conducted (in particular at intersections of multi-lane roads with traffic lights, as well as locations of road service facilities, such as gas stations, car parks, etc., which increase the negative environmental impact on the adjacent territory).

A Novel Capsule Network Based on Wide Convolution and Multi-Scale Convolution for Fault Diagnosis

Abstract: In the prognostics health management (PHM) of rotating machinery, the accurate identification of bearing fault is critical. In recent years, various deep learning methods can well identify bearing fault based on monitoring data. However, facing changing operating conditions and noise pollution, the accuracy of these algorithms decreases significantly, which makes the algorithms difficult in practical applications. To solve this problem, a novel capsule network based on wide convolution and multi-scale convolution (WMSCCN) is proposed for fault diagnosis. The proposed WMSCCN algorithm takes one-dimensional vibration signal as an input and no additional manual processing is required. In addition, the adaptive batch normalization (AdaBN) algorithm is introduced to further enhance the adaptability of WMSCCN under noise pollution and load changes. On generalization experiments under different loads, the proposed WMSCCN and WMSCCN-AdaBN algorithms achieve average accuracy rates of 96.44% and 97.44%, respectively, which is superior to other advanced algorithms. In the noise resistance experiment, the proposed WMSCCN-AdaBN can maintain a 92.3% diagnostic accuracy in a strong noise environment with a signal to noise ratio (SNR) = −4 dB, showing a very strong anti-noise ability. When the SNR exceeds 4 dB, the accuracy reaches 100%, indicating that the proposed algorithm has a very good accuracy at low noise levels. Two experiments have effectively verified the validity and generalizability of the proposed model.

Life cycle sustainability assessment of window renovations in schools against noise pollution in tropical climates

Abstract: Because of the significant increase in the number of noise complaints, reducing and limiting noise pollution have become prevalent subjects related to the retrofitting of school buildings. The present case study considers a multi-apartment school building in the city of Johor, Malaysia. The life cycle criteria evaluated in this study are carbon dioxide (CO2) emissions and the cost and social impacts of each window type. The preliminary assessment showed that the school's current noise level is 74.31 dB (A), which exceeds the acceptable threshold of 55 dB (A). In the next step, three more windows were applied and reevaluated, with the triple glazing window performing the best (48.66 dB (A)), followed by the double glazing window (51.3 dB (A)). In terms of carbon emissions and cost, the preference window had the best performance. Meanwhile, considering the social aspect, the double glazing window performed the best. Because three different windows were deemed the best choice depending on which of the four criteria was considered, multi-criteria decision making (MCDM) was applied by TOPSIS to weigh and estimate each alternative. The final decision was made by giving priority to the four criteria as follows: noise (0.322), cost (0.257), CO2 emissions (0.227), and SLCA (0.194). The MCDM process revealed that the double glazing window is the most sustainable choice for school buildings. Furthermore, two sensitivity analyses were performed to eliminate human subjectivity involved in AHP.

Acute cardiovascular health effects in a panel study of personal exposure to traffic-related air pollutants and noise in Toronto, Canada.

Abstract: Urban populations are often simultaneously exposed to air pollution and environmental noise, which are independently associated with cardiovascular disease. Few studies have examined acute physiologic responses to both air and noise pollution using personal exposure measures. We conducted a repeated measures panel study of air pollution and noise in 46 non-smoking adults in Toronto, Canada. Data were analyzed using linear mixed-effects models and weighted cumulative exposure modeling of recent exposure. We examined acute changes in cardiovascular health effects of personal (ultrafine particles, black carbon) and regional (PM2.5, NO2, O3, Ox) measurements of air pollution and the role of personal noise exposure as a confounder of these associations. We observed adverse changes in subclinical cardiovascular outcomes in response to both air pollution and noise, including changes in endothelial function and heart rate variability (HRV). Our findings show that personal noise exposures can confound associations for air pollutants, particularly with HRV, and that impacts of air pollution and noise on HRV occur soon after exposure. Thus, both noise and air pollution have a measurable impact on cardiovascular physiology. Noise should be considered alongside air pollution in future studies to elucidate the combined impacts of these exposures in urban environments.

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

Abstract: 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.

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

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