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In many developing countries with surging vehicular traffic and inadequate traffic management, excessive road traffic noise exposure poses substantial health concerns, linked to increased stress, insomnia and other metabolic disorders. This study aims to assess the linkage between sociodemographic factors, traffic noise levels in residential areas and health effects using a cross-sectional study analyzing respondents' perceptions and reports. Noise levels were measured at 57 locations in Srinagar, India, using noise level meter. Sound PLAN software was employed to generate noise contour maps, enabling the visualization of noise monitoring locations and facilitating the assessment of noise levels along routes in proximity to residential areas. Correlation analysis showed a strong linear relationship between field-measured and modelled noise (r2 = 0.88). Further, a questionnaire-based survey was carried out near the sampling points to evaluate the association of ischemic heart disease with traffic noise. Residents exposed to noise levels (Lden > 60 dB(A)) were found to have a 2.24 times higher odds ratio. Compared to females, males reported a 16% higher prevalence of the disease. Multi-faceted policy strategies involving noise mapping initiatives, source noise standards, traffic flow urban mobility optimization, smart city initiatives and stringent litigatory measures could significantly reduce its detrimental impact on public health. Finally, this study envisions a region-specific strong regulatory framework for integrating noise pollution mitigation strategies into the public health action plans of developing nations. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had profound global repercussions, leading to substantial fatalities and economic losses worldwide. However, amidst these adversities, the pandemic inadvertently offered a unique opportunity to assess the impact of reduced human activity on environmental noise levels. This study focuses on monitoring and mapping noise pollution levels at 101 locations managed by the Bhubaneswar Development Authority (BDA) in Bhubaneswar, Odisha, India, during three distinct periods: pre-COVID, during COVID-lockdown, and post-COVID. Using ArcGIS 10.2.1, noise data are spatially analysed across different zones designated by the Central Pollution Control Board (CPCB), namely Industrial, Commercial, Residential, and Silence Zones. The findings reveal a significant reduction in traffic noise during the COVID-19 lockdown period compared to both pre-COVID and post-COVID periods across all four zones. To assess the potential impact on human health, the study employs equations developed by Miedema and Vos (Acoust Soc Am 104:3432–3445, 1998, ) for calculating percentages of highly annoyed individuals and estimating sleeping disorders. Additionally, Structural Equation Modeling (SEM) is applied to explore associations between noise levels and health outcomes across different time periods. Despite the significant reduction in traffic noise observed during the COVID-19 lockdown, our analysis suggests that this decrease did not have a statistically significant effect on annoyance levels (p-value: 0.0542) or sleeping disorders (p-value: 0.121). This study provides valuable insights into the unintended consequences of urban lockdowns on environmental noise pollution and their potential implications for public health and urban planning. [ABSTRACT FROM AUTHOR]

Increased use of recreational areas after the lifting of COVID-19 pandemic restrictions has led to increased noise levels. This study aims to determine the level of noise pollution experienced in recreational areas with the increasing domestic and international tourism activities after the lifting of pandemic lockdowns, to produce spatial distribution maps of noise pollution, and to develop strategic planning suggestions for reducing noise pollution in line with the results obtained. Antalya-Konyaaltı Beach Recreation Area, the most important international tourism destination of Turkey, is determined as the study area. To determine the existing noise pollution, 31 measurement points were marked at 100 m intervals within the study area. Noise measurements were taken during the daytime (07:00–19:00), evening (19:00–23:00), and nighttime (23:00–07:00) on weekdays (Monday, Wednesday, Friday) and weekends (Sunday) over 2 months in the summer when the lockdown was lifted. In addition, the sound level at each measurement point was recorded for 15 min, while the number of vehicles passing through the area during the same period was determined. The database created as a result of measurements and observations was analyzed using statistical and geostatistical methods. After the analysis of the data, it was found that the co-kriging-stable model showed superior performance in noise mapping. Additionally, it was revealed that there is a high correlation between traffic density and noise intensity, with the highest equivalent noise level (Leq) on weekdays and weekend evenings due to traffic and user density. In conclusion, regions exposed to intense noise pollution were identified and strategic planning recommendations were developed to prevent/reduce noise sources in these identified regions. [ABSTRACT FROM AUTHOR]

German noise action plans aim to reduce negative health outcomes from noise exposure and identify quiet areas free of noise pollution. Quiet area identification in German noise action plans is based primarily on noise mapping and spatial analysis and not empirical or qualitative data about acoustic environments, thus leaving a gap in the understanding of the quality of formally recognized quiet areas in noise action plans. This work presents a comparative empirical case study in Dortmund, Germany, with the aim to describe the diurnal dB(A) and biophonic properties of quiet areas versus noise 'hot spots'. Sound observations (n = 282,764) were collected in five different natural or recreational land use patch types larger than four acres within 33 proposed quiet areas in Dortmund (n = 70) and 23 noise hot spots between 27 April 2022 and 2 March 2023. We found that quiet areas are on average more than 20 dB(A) quieter than noise hot spots almost every hour of the day. Forests, managed tree stands, cemeteries, and agriculture diel patterns are dominated by dawn dusk chorus in spring and summer, whereas sports and recreation as well as noise hot spots are dominated by traffic and human noise. A novel composite biophony mapping procedure is presented that finds distinct temporal distribution of biophony in forested and agriculture peri-urban locations positively associated with patch size, distance away from LDEN > 55, proximity to water, and the number of vegetation layers in the plant community. Anthrophony distribution dominates urban land uses in all hours of the day but expands during the day and evening and contracts at night and in dusk hours. The procedures presented here illustrate how qualitative information regarding quiet areas can be integrated into German noise action planning. [ABSTRACT FROM AUTHOR]

The F1 Race is one of the most popular international sports events in the world, attracting a huge number of tourists every year. However, the sound emission may lead to hearing damage or unpleasantness from a psychological or physiological perspective. This study selected two sites near the Singapore Formula 1 Night Race racing tracks in 2023 to record and compare the noise profiles with the respective ambient conditions. Both the regular sound pressure level and the psychoacoustic analysis will be included. The A-weighted Leq value was over 95 dBA near the straight racing tracks during the Formula 1 Singapore Airline Singapore Grand Prix session, and the LAmax value can reach more than 120 dBA. Meanwhile, the LAeq and LAmax values near the bend during the afternoon race sessions were over 91 dBA and 117 dBA. Besides, the average LCeq values can be even higher. Additionally, the psychoacoustic parameters of loudness, sharpness and roughness differentiate the acoustic character at the bends and straight tracks. With similar LAeq and LAmax values, the averaged loudness and sharpness values were significantly higher at the straight tracks, while the roughness values were higher at the bend.

Noise pollution is a major challenge in urban contexts all around the world. The study was designed to assess road traffic noise pollution with possible health effects on those living in the study region. The IDW spatial interpolation approach and an ArcGIS-based evaluation were used to map the recorded noise levels in the research region. The noise descriptors including Noise Climate (NC), Traffic Noise Index (TNI), Equivalent Noise Level (Leq), and Noise Pollution Level (NPL) were computed. The required information has been collected through a questionnaire survey and previously published documents. The study reveals that the current noise level is higher than the recommended national threshold at every location. According to the study, the Nathullabad region had the highest level of noise pollution (86.5 dBA), while the Kaunia Abasik area had the lowest level (67.8 dBA). Study findings also show that in the area context, the highest levels of noise pollution are found in commercial areas (82 dBA), followed by industrial areas (80.4 dBA),mixed areas (81.3 dBA), and residential areas (72.7 dBA). The lowest level is found in sensitive areas (72.5 dBA). Statistical analyses, including one-way ANOVA, Tukey HSD post-hoc and LSD post-hoc test results, showed that there was no statistically significant difference (p > 0.05) between the noise pollution levels (NPL) in the morning, noon, and evening shifts. The results showed that 32 % of respondents stated they felt disturbed while working, and 27% of respondents said it was somewhat sensitive for them. As the last step in minimizing noise pollution in the research area, 37 % of respondents reported enforcing the regulations, 31% suggested making hydraulic horns illegally, and 21 % suggested raising public awareness. This study may contribute to academic knowledge and assist decision-makers of government officials in formulating appropriate local strategies to deal with this grave environmental problem.

Environmental noise is a major environmental concern in metropolitan cities. The rapid social and economic growth in the 20th century is not always accompanied by adequate land planning and environmental management measures. As a consequence of rapid urbanization processes, cities are facing an increase in noise pollution. Noise is being recognized as a serious environmental problem and one which must be accounted for in a sustained development policy designed to improve the quality of life for citizens. Therefore, the monitoring of noise is a crucial aspect of urban planning to allow urban planners to create harmonious and livable environments for communities worldwide. This research aims at assessing the noise levels and associated sources of noise in downtown areas through the involvement of crowdsourcing techniques. The incorporation of noise mapping and increased public awareness are achieved by a framework that enables a comparative scheme between two cities: Alexandria, Egypt and Zagreb, Croatia. The methodology depends on combining crowdsourcing techniques using mobile applications and geographic information system (GIS) tools to detect and analyze noise. Finally, this research provides a comparison between the two cities using the adopted methodology and introduces recommendations to enhance urban planning decisions. [ABSTRACT FROM AUTHOR]

Environmental noise control is a major health and social issue. Numerous environmental policies require local authorities to draw up noise maps to establish an inventory of the noise environment and then propose action plans to improve its quality. In general, these maps are produced using numerical simulations, which may not be sufficiently representative, for example, concerning the temporal dynamics of noise levels. Acoustic sensor measurements are also insufficient in terms of spatial coverage. More recently, an alternative approach has been proposed, consisting of using citizens as data producers by using smartphones as tools of geo-localized acoustic measurement. However, a lack of calibration of smartphones can generate a significant bias in the results obtained. Against the classical metrological principle that would aim to calibrate any sensor beforehand for physical measurement, some have proposed mass calibration procedures called "blind calibration". The method is based on the crossing of sensors in the same area at the same time, which are therefore supposed to observe the same phenomenon (i.e., measure the same value). The multiple crossings of a large number of sensors at the scale of a territory and the analysis of the relationships between sensors allow for the calibration of the set of sensors. In this article, we propose to adapt a blind calibration method to data from the NoiseCapture smartphone application. The method's behavior is then tested on NoiseCapture datasets for which information on the calibration values of some smartphones is already available. [ABSTRACT FROM AUTHOR]

The present study presents an investigation into the utilization of artificial neural networks (ANN) and multiple linear regression model (MLR) for the prediction of traffic noise levels in various locations of Dhanbad city at varying intervals. Traffic noise indices measurements were carried out using sound pressure level meter (SLM). The prediction of equivalent A-weighted sound level (LAeq) and the sound level exceeding 10 percent of the time (L10) is carried out using various influencing factors such as number of cars, number of 2 wheelers, number of 3 wheelers, number of heavy vehicle, number of medium commercial vehicles, and traffic speed. The findings demonstrate the ANN model's proficiency in comparison of MLR model for providing precise prediction accuracy of traffic noise indices with a R2 of 0.94 for LAeq and 0.91 for L10. Furthermore, the frequency spectrum analysis reveals that high peaks were observed at lower frequencies ranging from 31.5 Hz to 50 Hz, middle frequencies from 500 to 800 Hz and higher frequencies from 3.5 kHz to 5 kHz. The noise maps at varying intervals revealed that most of the locations are having higher noise levels due to increase in vehicular movement. The study emphasizes on the potential significance of the proposed neural network-based prediction model in collaboration with noise mapping as a vital tool for the anticipation of traffic noise levels and the formulation of noise mitigation strategies in context of the mid-sized smart city like Dhanbad, India.

The accurate prediction of noise levels at outdoor locations requires detailed data of the noise sources and terrain parameters and an efficient model for prediction. However, the possibility of predicting noise with reasonable accuracy using less input data is a challenge and needs to be studied scientifically. The qualities of the noise data, terrain parameters, and prediction model can impact the accuracy of the prediction significantly. This study primarily focuses on the dependency of noise data for efficient noise prediction and mapping. This research article proposes a detailed methodology to predict and map the noise and exposure levels in Ratapur, Uttar Pradesh, India, with various granularities of noise data inputs. The noise levels were measured at various places and at different times of the day at 10 min intervals. Different data input proportions and qualities were used for noise prediction, namely, (1) a large data-based method, (2) a small data-based method, (3) a source point average data-based method, (4) a Google navigation data-based method, and (5) accurate modelling using an ANN-based method, integrating accurate noise data with a sophisticated modelling algorithm for noise prediction. The analysis of the variation between the predicted and measured noise levels was conducted for all five of the methods using the ANOVA technique. Various methods based on less noise data methods predicted the noise levels with accuracies within the ±4–10 dB(A) range, while the ANN-based technique predicted it with an accuracy of ±0.5–2.5 dB(A). Interestingly, the estimation of the noise exposure levels (>85 dB(A)) and the identification of hazard zones around the studied road intersection could also be performed efficiently even when using the data-deficient models. This paper also showcased the possibility of predicting an accurate 3D map for an area by extracting vehicles and terrain features from satellite images without any direct recording of noise data. This paper thus demonstrated approaches to reduce the noise data dependency for noise prediction and mapping and to enable accurate noise-hazard zonation mapping.

The accurate prediction of noise levels at outdoor locations requires detailed data of the noise sources and terrain parameters and an efficient model for prediction. However, the possibility of predicting noise with reasonable accuracy using less input data is a challenge and needs to be studied scientifically. The qualities of the noise data, terrain parameters, and prediction model can impact the accuracy of the prediction significantly. This study primarily focuses on the dependency of noise data for efficient noise prediction and mapping. This research article proposes a detailed methodology to predict and map the noise and exposure levels in Ratapur, Uttar Pradesh, India, with various granularities of noise data inputs. The noise levels were measured at various places and at different times of the day at 10 min intervals. Different data input proportions and qualities were used for noise prediction, namely, (1) a large data-based method, (2) a small data-based method, (3) a source point average data-based method, (4) a Google navigation data-based method, and (5) accurate modelling using an ANN-based method, integrating accurate noise data with a sophisticated modelling algorithm for noise prediction. The analysis of the variation between the predicted and measured noise levels was conducted for all five of the methods using the ANOVA technique. Various methods based on less noise data methods predicted the noise levels with accuracies within the ±4–10 dB(A) range, while the ANN-based technique predicted it with an accuracy of ±0.5–2.5 dB(A). Interestingly, the estimation of the noise exposure levels (>85 dB(A)) and the identification of hazard zones around the studied road intersection could also be performed efficiently even when using the data-deficient models. This paper also showcased the possibility of predicting an accurate 3D map for an area by extracting vehicles and terrain features from satellite images without any direct recording of noise data. This paper thus demonstrated approaches to reduce the noise data dependency for noise prediction and mapping and to enable accurate noise-hazard zonation mapping. [ABSTRACT FROM AUTHOR]

The soundscape study of an eastern Indian coastal city (Puri) has been investigated. Acoustic data were collected at 36 sampling locations during two time intervals in and around Puri. A number of noise indices, namely, Lmin, Lmax, and Leq, were calculated to demonstrate the noise level of this city. Noise maps are generated using ARC-GIS to investigate the impact of road traffic noise on the soundscape of the city. The response of the public was appraised by a questionnaire. Due to variable traffic features, the equivalent noise level (Leq) as well as peak (L10) and background noise (L90) levels varied with location and time of the day. It was found that socio-demographic characteristics have no bearing on the amount of annoyance. However, a link was observed between age, hearing condition, and noise perception, as well as between gender and impacts of noise. [ABSTRACT FROM AUTHOR]

The civil security sirens are used by the authorities in a wide range of countries to signal an imminent or ongoing threat. Even if their sound level is known, it is nevertheless difficult to evaluate their audibility across a given zone, especially in complex urban environments. An experimental protocol was deployed around a siren installed in a town in France, to assess its audibility perceptually and through modeling. Sound level measurements during source activation were made with the NoiseCapture smartphone application at different distances and on several axes by a group of 25 participants. They were also asked to fill in a questionnaire on perceptual information about the siren such as its audibility, the perceived sound level, or the masking of the siren by passing vehicles. A comparison between acoustic measurement levels using NoiseCapture and simulated sound levels using NoiseModelling was performed. The results of this study validate the use of the Common Noise Assessment Methods in Europe model to evaluate the audibility of a warning system located in an urban environment within a radius of 2.8 km around the siren. Finally, a metric linking audibility to modeled sound level is proposed, enabling the development of siren audibility maps in the study area.

The Environmental Noise Directive (END), published in 2002, was transposed into Romanian local law in 2005, and it was the starting point for the first urban noise mapping exercises, initially conducted in nine Romanian cities. This paper presents the main evolutionary aspects of the noise assessment process, the development of strategic noise maps, and action plans, dealing with both the legislative side and the practical approach and results obtained. The study considers the specific regulations established by the European Commission regarding environmental noise assessment and deals with the global context at the country level, in which they have been implemented and applied.

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The present study aimed to evaluate the possible impact of noise pollution. This study was conducted in Raipur, the capital of Chhattisgarh state, India, to analyze the relationship between noise pollution and health complaints. A total of 18 locations were selected for monitoring noise pollution levels in the morning (9:00-10:30 AM) and evening (7:00-8:30 PM). Noise maps were prepared for both the time interval, and it was found that the highest equivalent noise level (Leq) of 81.31 dBA was observed at location L3 whereas the lowest Leq of 63.25 dBA was observed at L16 in the morning and in the evening 77.33 dBA at L3 and 60.14 dBA at L16 were observed. A questionnaire survey was performed on the population (n = 400) exposed to noise and analyzed through a variance-based partial least square (PLS) structural equation model (SEM). From the survey, it was found that most of the respondents are exposed to higher noise levels and are facing health issues of "pain in the ear," "rise in blood pressure," "loss of sleep," "whistling and buzzing" in their ear, "headache," "heaviness" and "efficiency problem." A total of 109 hypotheses were proposed and analyzed through bootstrapping with a subsample size of 5000 in SmartPLS software. 18 hypotheses were found to be significant in the proposed model. SEM analysis revealed an interrelation between noise pollution and health effects. It is recommended that strict regulation in nearby sensitive areas must be imposed and an awareness drive on a large scale shall be conducted to enlighten the city's population regarding noise effects as well as various measures for controlling. [ABSTRACT FROM AUTHOR]

German noise action plans aim to reduce negative health outcomes from noise exposure and identify quiet areas free of noise pollution. Quiet area identification in German noise action plans is based primarily on noise mapping and spatial analysis and not empirical or qualitative data about acoustic environments, thus leaving a gap in the understanding of the quality of formally recognized quiet areas in noise action plans. This work presents a comparative empirical case study in Dortmund, Germany, with the aim to describe the diurnal dB(A) and biophonic properties of quiet areas versus noise ‘hot spots’. Sound observations (n = 282,764) were collected in five different natural or recreational land use patch types larger than four acres within 33 proposed quiet areas in Dortmund (n = 70) and 23 noise hot spots between 27 April 2022 and 2 March 2023. We found that quiet areas are on average more than 20 dB(A) quieter than noise hot spots almost every hour of the day. Forests, managed tree stands, cemeteries, and agriculture diel patterns are dominated by dawn dusk chorus in spring and summer, whereas sports and recreation as well as noise hot spots are dominated by traffic and human noise. A novel composite biophony mapping procedure is presented that finds distinct temporal distribution of biophony in forested and agriculture peri-urban locations positively associated with patch size, distance away from LDEN > 55, proximity to water, and the number of vegetation layers in the plant community. Anthrophony distribution dominates urban land uses in all hours of the day but expands during the day and evening and contracts at night and in dusk hours. The procedures presented here illustrate how qualitative information regarding quiet areas can be integrated into German noise action planning.

Environmental noise is a major environmental concern in metropolitan cities. The rapid social and economic growth in the 20th century is not always accompanied by adequate land planning and environmental management measures. As a consequence of rapid urbanization processes, cities are facing an increase in noise pollution. Noise is being recognized as a serious environmental problem and one which must be accounted for in a sustained development policy designed to improve the quality of life for citizens. Therefore, the monitoring of noise is a crucial aspect of urban planning to allow urban planners to create harmonious and livable environments for communities worldwide. This research aims at assessing the noise levels and associated sources of noise in downtown areas through the involvement of crowdsourcing techniques. The incorporation of noise mapping and increased public awareness are achieved by a framework that enables a comparative scheme between two cities: Alexandria, Egypt and Zagreb, Croatia. The methodology depends on combining crowdsourcing techniques using mobile applications and geographic information system (GIS) tools to detect and analyze noise. Finally, this research provides a comparison between the two cities using the adopted methodology and introduces recommendations to enhance urban planning decisions.

Environmental noise control is a major health and social issue. Numerous environmental policies require local authorities to draw up noise maps to establish an inventory of the noise environment and then propose action plans to improve its quality. In general, these maps are produced using numerical simulations, which may not be sufficiently representative, for example, concerning the temporal dynamics of noise levels. Acoustic sensor measurements are also insufficient in terms of spatial coverage. More recently, an alternative approach has been proposed, consisting of using citizens as data producers by using smartphones as tools of geo-localized acoustic measurement. However, a lack of calibration of smartphones can generate a significant bias in the results obtained. Against the classical metrological principle that would aim to calibrate any sensor beforehand for physical measurement, some have proposed mass calibration procedures called “blind calibration”. The method is based on the crossing of sensors in the same area at the same time, which are therefore supposed to observe the same phenomenon (i.e., measure the same value). The multiple crossings of a large number of sensors at the scale of a territory and the analysis of the relationships between sensors allow for the calibration of the set of sensors. In this article, we propose to adapt a blind calibration method to data from the NoiseCapture smartphone application. The method’s behavior is then tested on NoiseCapture datasets for which information on the calibration values of some smartphones is already available.

The university setting significantly impacts the student’s learning and academic achievement. A vital aspect shaping their productivity and well-being within this environment is the indoor soundscape. Different organizations, nationally and internationally, have emphasized the importance of addressing noise-related issues and have established guidelines. This study investigates how indoor soundscapes affect student learning and achievement in university classrooms. The present study analyses noise levels at nine locations during morning, afternoon, and evening study hours using a class 1 sound level meter. Results show noise levels ranging from 49.8 to 77.6 dBA, averaging 66.1 dBA. Over 96% exceeded the ANSI, CPCB noise limit of 50 dBA, with 62.96% surpassing WHO’s 55 dBA standards. Seven of nine locations maintained acceptable noise levels 95% of the time, considering a ±10 dBA fluctuation allowed by CPCB. Libraries and computer labs generally had lower noise, while engineering labs had higher levels due to noisy equipment. This research holds significance for educational institutions, policymakers, and stakeholders in creating conducive learning environments. Understanding prevailing soundscapes informs the design and management of study areas, and helps optimize learning spaces for improved productivity.

The present study reports the analysis of hourly equivalent noise levels of 100 sites in the NCT (National Capital Territory) of Delhi and correlates with the community perception that has not been reported so far. The study presents the environmental noise scenario of 100 sites in the NCT of Delhi, India, including 19 commercial, 9 industrial, 16 residential, 43 silence zones, 3 highway sites, and 10 intersection sites. The hourly equivalent noise levels of 100 sites were monitored at various timings between 9 AM and 8 PM to analyze the environmental noise pollution scenario in the city. Along with the hourly equivalent continuous sound levels (LAeq, 1 h); 10-percentile exceeded sound levels (L10), Traffic Noise Index (TNI), Noise Climate (NC), and Noise Pollution Level (NPL) of these sites were also computed. The LAeq, 1 h levels varied from 66.5 to 84.7 dB(A), and majority of the sites (90.0% sites) exhibited LAeq, 1 h between 70 and 80 dB(A). A noise map was developed in addition to a socio-acoustic survey conducted to analyze the public perception toward noise pollution and associated health hazards. The study revealed that road traffic noise along with honking noise is the major dominant source of noise pollution. It shall be very helpful in recommending appropriate noise control strategies for abatement and control of environmental noise pollution in the city. [ABSTRACT FROM AUTHOR]

The Environmental Noise Directive (END), published in 2002, was transposed into Romanian local law in 2005, and it was the starting point for the first urban noise mapping exercises, initially conducted in nine Romanian cities. This paper presents the main evolutionary aspects of the noise assessment process, the development of strategic noise maps, and action plans, dealing with both the legislative side and the practical approach and results obtained. The study considers the specific regulations established by the European Commission regarding environmental noise assessment and deals with the global context at the country level, in which they have been implemented and applied. [ABSTRACT FROM AUTHOR]

Although ambient air filters are commonly used to improve air quality in urban areas, their operation often produces significant noise levels. In this study, we investigated and addressed the issue of ambient air filter noise exposure in open areas of Chinese cities, with a focus on various typical urban forms. Firstly, fifteen common urban blocks with different forms and of 250 × 250 m each were chosen as sample sites, for which urban form indices and noise distribution indices were defined. Then noise mapping was conducted to investigate air filter noise exposure in open areas and the effects of urban form indices on noise distribution indices. Results show that urban form has considerable effects on filter noise exposure in open areas. Among the six urban form indices examined, the distance between the first-row building and the air filter was found to be the most critical factor affecting noise levels with the highest correlation coefficient (R = 0.754). The orientation of the first-row building shows the significant resisting effect on both average and background noise levels. Furthermore, the resisting effect of first-row buildings can create a maximum reduction of 12.0 dB (A) for peak noise. These indices could be profiled and used as an "a priori" tool for urban sound environment planning. [ABSTRACT FROM AUTHOR]

This study presents the results of a traffic simulation analysis and emissions (greenhouse gas and noise) assessment comparing pre-pandemic (2019) and post-pandemic (2022) periods. The estimation of road traffic demand is based on conventional data sources and floating car data; next, the traffic simulation procedure was performed providing road network traffic volumes, which are the input for the emission models. The diffusion of teleworking, e-commerce, as well as the digitization of many processes, services and activities, lead to a significant change in urban mobility. Results show a significant though still not complete resumption of commuters travel activity (−10% compared to pre-pandemic period) in the morning peak-hour. This translates into an 11% reduction of greenhouse gas emissions and a 0.1% increase in noise emissions.

The paper presents an original methodology for the identification of intervention priorities through a tailored priority index IP in areas that are highly-exposed to port noise. The methodology is applied to a case study developed in the framework of the European project ANCHOR, acronym of Advanced Noise Control strategies in HarbOuR, funded as part of the announcement Life 2017.

Excessive noise exposure during the manufacturing process is a widespread issue. This research aimed to analyze noise exposure in the kernel recovery station in the manufacturing process of palm oil. We conduct some measurements and calculations for noise exposure analysis to get the Equivalent Noise Level (Leq) value during the daytime for each measurement point. The noise measurement was conducted on four machines, including a depericarper and polishing drum machine, ripple mill machine, silo dryer machine, and clay bath machine. In addition, this research showed noise contour mapping to define the noise distribution. The results of this research are that only the clay bath machine had Ls below the threshold. The clay bath machine workstation has good noise levels. The Depericarper, Polishing Drum, Ripple Mill, and Silo Dryer Machine must be quieter. Thus, this research used the Hierarchy of Control Approach to reduce and control hazardous noise exposure. The stage of HOC includes elimination, substitution, engineering, administrative control, and Personal Protective Equipment (PPE).

Noise pollution is one of the important environmental problems brought about by accelerating urbanization, especially in Altınordu, which is the central district, following the granting of metropolitan status to Ordu province. The number of noise sources such as motor vehicles that contribute to noise pollution is increasing day by day due to the increasing urban population. The Ordu University Cumhuriyet Campus, located on one of the important transportation routes of the Black Sea, can be adversely affected by traffic-related noise pollution. Studies show that high sound pressure levels significantly reduce the efficiency of education in university campuses where education and training activities are carried out at the undergraduate and graduate level. In this context, our study determines the temporal and spatial distribution of the environmental noise level in the case of the Ordu University Cumhuriyet Campus. For this purpose, sound pressure levels were measured in the morning (9.00-10.00), at noon (12.00-13.00) and in the evening (16.00-17.00) throughout the week at pre-determined 25 points in the campus. The obtained data were processed in the geographic information system software and noise maps of the campus were created, and the differences in the noise level on the campus were evaluated with statistical methods. It was determined that the main noise source directly affecting the campus was the E70 highway during the week and only human mobility on weekdays. There is a high negative correlation between the distance to the highway and the equivalent noise level measured in the campus. The highest equivalent noise level average in the campus was recorded at the weekend with 70.3 dB(A) in the north of the campus. The lowest noise level with 40.2 dB(A) was measured in the rectorate parking lot located in the south of the campus at the weekend. In line with the findings of the study, structural and vegetative solutions have been proposed to prevent noise in areas above the legal noise level. The results of the study and the suggestions developed are important in terms of being a guide for university administrators to keep noise levels at reasonable levels. With the implementation of the action plans in line with the suggestions developed, a more convenient learning environment for the students and a more peaceful working environment for the university staff will be created on the campus. [ABSTRACT FROM AUTHOR]

Determination of health hazards of noise pollution is a challenge for any developing city intersection. The people working at roadside open-air shops or near the congested roads of any intersection face intense noise pollution. It becomes very difficult to efficiently determine the hazards of noise on the health of people living near the intersection. An attempt was made to determine the noise-induced health hazards of the developing city of Bahadurpur, UP, India. The noise levels were monitored over 17 station points of the intersection for three months at different times of the day. Equivalent noise level (Leq) maps were determined within an accuracy of ±4dB. Areas adjacent to intersections indicated noise exposure levels close to 100 dB. Health hazards for the people of the intersection were determined through the testing of auditory and non-auditory health parameters for 100 people. A total of 75–92% of the people who work/live near the noisy intersection were found to be suffering from hearing impairment, tinnitus, sleep disturbance, cardiovascular diseases, hypertension, etc. Whether the recorded health hazards were indeed related to noise exposure was confirmed by testing the health parameters of people from the nearby and less noisy area of Pure Ganga. The nearby site reported mild hazards to the health of the population. An alarming level of hearing impairment was prevalent in the noisy Bahadurpur intersection (79–95%) compared to the same in Pure Ganga (13–30%). The estimated noise-induced health hazards were also compared for noisy and less-noisy study sites using ANOVA statistics. The results suggested that the health hazards reported in the two sites are not similar. Further, the severe hazards to people's health at the underdeveloped intersection were found to be primarily caused by the intense exposure to noise. [ABSTRACT FROM AUTHOR]

Tourism and the city are in a mutual relationship. Tourism affects the city and is affected by the city. In this context, smart environments that focus on the environment and quality of life come to the forefront in ensuring sustainability in tourism. In sustainable smart environments, noise pollution and control are important in terms of producing plan decisions and determining design criteria. In the study, it was aimed to obtain basic data for the measures to reduce and distribute the noise effect by mapping the noise caused by tourism density in Amasra, which is a small-scale touristic coastal town. In this context, noise maps were created by measuring the noise levels caused by tourism density for the city of Amasra, which is a touristic coastal settlement. In order to determine the noise levels, a total of 15 points were randomly selected, taking into account the proximity to urban uses such as hotels and restaurants as well as urban units such as avenues, streets, open spaces, or squares, provided that they are from various places in the city. Measurements were made regularly on weekdays and weekends in July. As a result of the data obtained, noise pollution levels for the city of Amasra were mapped for different situations (morning, noon, evening, weekdays, weekend, July general) using the Inverse Distance Weighting method. As a result of the measurements and maps prepared, it has been determined that the noise levels of the areas where the vehicle road, parking lot use, shopping and food and beverage places are located are mainly high. Finally, measures for noise control within the scope of sustainable smart environment were created in the study. [ABSTRACT FROM AUTHOR]

Noise emissions are a significant environmental impact caused by the mining industry in all technological phases of surface mining, mineral processing, and waste disposal. This paper presents the role of noise impact assessment and control in large-scale surface mining operations. Mine planning develops the model of mining operations, ore excavation, and waste dumping scheduling and processing rates, including spatial distribution of mining activities. Such a level of mine planning requires an environmental impact assessment study. This can be achieved by applying noise impact assessment models. The described approach can be used to verify the effectiveness of the proposed protection measures to reduce or eliminate the identified negative impacts. This paper presents a case study of environmental noise impact assessment and control at the Serbia Zijin Copper DOO Bor mine, encompassing the analysis of the noise protection measures efficiency within the planning of large-scale mining operations at the open-pit mine Veliki Krivelj. [ABSTRACT FROM AUTHOR]

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Although air filter towers are commonly used to improve air quality in urban areas, their operation often produces significant noise levels, and their noise impact is unknown. In this research paper, a case study on the noise impacts of an outdoor air filter tower in city open areas and on building façades is conducted by noise mapping. Noise levels around the filter tower were first measured in situ, and a prediction model for noise mapping was built and well-calibrated by comparing the predicted and measured results. Noise mapping was then carried out to investigate noise exposure in city open areas and on façades in four typical urban blocks with different morphology. Simulated results highlight noise level improvement with the increase of façade height at some high-rise buildings whose heights are higher than the neighboring ones. In addition, urban morphology, including building height and density, as well as the distance between the source and the building, has an impact on noise exposure. The utilization of sound-absorbing building envelopes has been identified as an effective means of reducing noise on building façades, with a maximum attenuation of approximately 4 dB(A) observed, but the effectiveness of this method is limited at certain positions. This study provides valuable insights into the impact of filter towers on noise levels and offers suggestions for urban sound planning.

This article analyses the most recent studies on urban traffic noise. About 67 relevant articles on urban road traffic noise and its mitigation strategies were preferred for a critical review. Only 5.97% of items describe how to monitor and record the noise measurement for urban roads, while 7.46% of articles enumerated urban traffic noise pollution exposure. 29.85% of articles proposed a model to evaluate noise reduction effects and predict the noise level. Also, many articles reported noise map generation and its analysis. 56.71% of articles described the noise mitigation strategies in detail, concerning noise control by green vegetation, land use planning, low noise tire and pavement material, noise reduction through façade shielding. Noise pollution standards are being breached in all areas. There is a need for the proper implementation of rules and regulations. Therefore, noise mitigation strategies such as designing noise barriers and other noise control materials are needed. Finally, it is summarized that economic and low-cost optimized noise pollution mitigation strategies like ingeniously made noise barriers, vegetation and landscaping are need of the hour for urban areas of developing countries.

Introduction: Each one of us is directly or indirectly exposed to noise pollution in our daily life. Noise has chronic effect on the human but many of us are not aware. In our modern research platform very few studies are available for monitoring and mitigating of noise pollution compared to other environmental pollution. Materials and methods: This study has been designed to monitor, map the noise pollution in educational institute and find out the sources of noise followed by identification of hot spot. In this regards National Institute of Technology Raipur, Chhattisgarh, India was selected as study area. Noise levels measurements were carried out at 15 locations within the study area at time intervals of forenoon (9:30 – 10:30 AM), noon (12:30-1:30 PM) and afternoon (4:30-5:30 PM) for 5 days of the week (working days). Using GIS tool observed noise levels were interpolated by Inverse Distance Weighted (IDW) method and graphical plots were prepared for different time intervals. Results: Noise Levels were found to be between 46 dBA to 72.08 dBA during our study. Sources contributing to higher levels of noise in the premises were traffic, honking of trains followed by students themselves. On comparing the finding with Central Pollution Control Board, New Delhi, India (CPCB) standards all the locations recorded higher noise levels than the prescribed limits. Conclusion: Based on our finding, mitigating approaches like: plantation of trees, construction of noise barriers, proper parking area, restricting high speed of vehicles etc. were suggested for making a healthy learning environment.

Noise is one of the inevitable environmental problems caused by the increasing population all over the world. There are various sources of noise that have physiological and psychological effects on people. One of these is traffic noise, which is especially effective in residential areas. This study aims to investigate the effect of different vegetation types on noise reduction in a highway model with heavy traffic. Six locations with dense planting along the highway in terms of plant groups and species density were selected, and the correlation of species density with noise analysis values was examined. For each location point, 2 points were assigned on the line, in front of and behind the vegetation, and measurements were made at 12 stations in total. Measurements were taken by performing fieldwork 5 times in different seasons and months and expressed as Leq differences. Since the vegetation types at the measurement points were not ordered, the species density analysis was determined in percentage (%) within the square areas of 100×100 meters in the existing field conditions. Mapping was completed using GIS to visualize the spatial spread of the noise measurement results, and zoning was done with interpolation to determine the noise contours and noise effect. According to all the findings obtained in this study, the leafy shrub or the tree group were found more effective in noise absorption than the coniferous species. Numerical calculations on maps suggest that plant community size and diversity can have a positive impact on noise reduction. [ABSTRACT FROM AUTHOR]

The long‐term effect of noise pollution is a serious environmental concern for those living near the road due to numerous anthropogenic activities. A calibrated sound level meter was used to assess the noise levels in a semi‐urban area known as Basudevpur Town (16 squares) in March 2021. A sample of the general public (126) was taken and interviewed using a questionnaire to find out how they felt about noise pollution and its impact on their health. A relationship between demographic characteristics and public health issues was discovered in the current investigation. The ANNOVA test was used to determine the association between noise exposure and the probable impacts of this noise exposure on this town, and the Chi‐square test in SPSS 20.0 was utilized to study the relationships between demographic character and irritation. The study reveals that the noise levels were greater than the CPCB's permissible limit for Indian road conditions. The primary source of noise, according to the study, is road traffic noise. The impact of noise pollution on the public's sleep problem was also analyzed. In order to limit noise pollution and its influence on public health, proper administrative planning is necessary. [ABSTRACT FROM AUTHOR]

Noise has become a very notable source of pollution with major impacts on health, especially in urban areas. To reduce these impacts, proper evaluation of noise is very important, for example by using noise mapping tools. The Noise-Planet project seeks to develop such tools in an open science platform, with a key open-source smartphone tool "NoiseCapture" that allows users to measure and share the noise environment as an alternative to classical methods, such as simulation tools and noise observatories, which have limitations. As an alternative solution, smartphones can be used to create a low-cost network of sensors to collect the necessary data to generate a noise map. Nevertheless, this data may suffer from problems, such as a lack of calibration or a bad location, which lowers its quality. Therefore, quality control is very crucial to enhance the data analysis and the relevance of the noise maps. Most quality control methods require a reference database to train the models. In the context of NC, this reference data can be produced during specifically organized events (NC party), during which contributors are specifically trained to collect measurements. Nevertheless, these data are not sufficient in number to create a big enough reference database, and it is still necessary to complete them. Other communities around the world use NC, and one may want to integrate the data they collected into the learning database. In order to achieve this, one must detect these data within the mass of available data. As these events are generally characterized by a higher density of measurements in space and time, in this paper we propose to apply a classical clustering method, called DBSCAN, to identify them in the NC database. We first tested this method on the existing NC party, then applied it on a global scale. Depending on the DBSCAN parameters, many clusters are thus detected, with different typologies. [ABSTRACT FROM AUTHOR]

Background: Noise pollution is increasing across the world due to the increase in human activities in the urban areas. The main causes of noise pollution are man-made and environmental noise. However, long exposure to noise pollution could lead to dire health consequences like cardiovascular diseases, hearing impairment, sleep disturbances, and adverse social behavior etc., which is rarely documented in the study area. Objective: Communities in the developing countries such as Ghana have little knowledge of effects of noise pollution on human health, which is demonstrated by their attitude towards this menace. This study assessed the health impacts of noise pollution and its spatial distribution in the Tarkwa Mining Community (TMC) of Ghana. Methods: To achieve the study objective, questionnaires were administered; as well as collation of health data from major health centers in the study area. Noise levels were measured and noise map produced using geographic information system (GIS) techniques. Overlay maps of some diseases were done using overlay techniques in GIS. The noise exposure and corresponding noise doses for churches, working sites and social centers were also calculated using the respective formulae. Results: The noise levels were found to be high above the prescribed Ghana Environmental Protection Agency (EPA) standards, with traffic noise levels ranging from 65.00 dBA to 98 dBA, while that of churches ranged from 73.10 dBA to 107.00 dBA and that of working sites from 74.4 dBA to 115.2 dBA. The calculated noise exposure and corresponding noise dose for churches ranged from 75.1 dBA to 104.6 dBA (i.e., 10%‒8 000%), while that for workers’ sites were from 75.8 dBA to 115 dBA (i.e., 12%‒90 000%). Statistical regression and correlation analyses were done for diseases such as hypertension, ear problems and sleep disturbances. Conclusion: The study has therefore revealed that the noise levels in the study area are very high and corresponding health impacts are prominent. Stakeholders and authorities should devise mitigating measures to combat this rising menace. The results revealed a strong positive correlation between noise and corresponding health impacts. Despite the positive correlation there are other causes and effects to the mentioned diseases.

The paper reports the main contents of the guidelines developed in the framework of the project ANCHOR, acronym of Advanced Noise Control strategies in HarbOuR, which is a European Project funded as part of the announcement Life 2017.

Current best practice aircraft noise calculations primarily focus on strategic noise mapping to assess compliance with legal noise limits. To date, the effects of shielding by buildings or reflections from buildings, forests or cliffs have not been considered in noise mapping, despite their potential impact on results, particularly in mountainous and/or densely built urban areas. In this study, the effects of shielding by buildings and reflections from buildings, forests and cliffs on aircraft noise results were assessed. Calculations were performed with the sonAIR simulation tool for a residential area close to the runway of a military airfield in a mountain valley in Switzerland. The calculations revealed that shielding and reflections may locally strongly affect the results. While this may yield valuable insights for special investigations, calculations without accounting for these effects are still recommended for large-scale noise mapping, to obtain a better overview of the noise exposure and legal compliance. • Analysis of shielding from buildings, reflections from buildings, cliffs and forest. • Barrier effects are more important for large-scale noise exposure than reflections. • In acoustical shadows zones, reflections play a significant role. • For aircraft noise mapping, accounting for these effects is not recommended. • The studied effects may be of interest for special and/or local investigations. [ABSTRACT FROM AUTHOR]