Noise Mapping Research Articles

Integration of cost-effective datasets to improve predictability of strategic noise mapping in transport corridors in Delhi city, India.

Assessing exposure to environmental noise levels at transport corridors remains complex in conditions where no standardized noise prediction model is available. In planning and policy implementation for noise control, noise mapping is an important step. In the present study, land use regression model has been developed to predict the environmental noise levels in Delhi city, India, using previously developed approaches along with machine learning techniques, however improved using new datasets. Lday, Lnight, LAeq,24h, and Ldn were modeled at daily resolution by utilizing an annual noise levels dataset from 31 locations in Delhi city. The noise-monitored data was integrated with travel time data, nighttime light data along with common parameters including land use, road networks, and meteorological parameters. The developed LUR models showed good fit with R2 of 0.72 for Lday, 0.55 for Lnight, 0.71 for LAeq,24h, and 0.61 for Ldn, which was further improved up to 0.88 for Lday, 0.79 for Lnight, 0.86 for LAeq,24h, and 0.81 for Ldn by integrating machine learning approaches. The developed models were validated through tenfold cross validation and by comparison to a separate noise level dataset. The average travel time variable was observed to be the most influential predictor of LUR models for Lday and LAeq,24h, which signifies the crucial impact of road traffic congestion on environmental noise levels. The study also analyzed the parametric sensitivity of various infrastructural factors reported in the study, which shall be helpful for planning for smart cities.

Noise Mapping and Impact of Land Use Land Cover on Urban Soundscape

Noise Mapping and Impact of Land Use Land Cover on Urban Soundscape

Straight road noise mapping prediction using probabilistic approach

Straight road noise mapping prediction using probabilistic approach

Depressive symptoms modify the association between noise and adiposity biomarkers: Evidence from a population study of Czech adults

ObjectiveEnvironmental noise exposure is associated with adiposity. However, less is known about the individual vulnerability to environmental noise in abnormal adiposity development, particularly in relation to mental health. This study investigated the association between environmental noise exposure and four adiposity biomarkers and tested the moderation effect of depressive symptoms. MethodsA cross-sectional population-based sample of 2031 participants aged 25–64 years (54.70% women) was drawn from the Kardiovize study in 2013. Global combined (road, railway, and airport) Lden (day-evening-night) noise exposures were obtained from the geographical prediction modelling for the 2nd report of Strategic noise mapping in the Czech Republic (2012). Four adiposity biomarkers (BMI, body fat percentage, waist circumference, and visceral fat area) were assessed. Depressive symptoms were measured by PHQ-9. Linear regression was used to estimate the separate effects of quartiles of noise exposure and depressive symptoms on adiposity biomarkers and to examine the interaction between noise exposure and depressive symptoms. ResultsThe average noise exposure was 53.79 dB, ranging from 42.50 dB to 66.97 dB. All biomarkers were significantly elevated in the highest noise exposure quartile (>56 dB), compared to the lowest quartile (<51 dB) (p < 0.05). The association between noise and adiposity biomarkers was modified by presence of depressive symptoms; the increase in all adiposity biomarkers in the highest quartile of noise was significantly larger among subjects with moderate to severe depressive symptoms (p < 0.005). ConclusionThe study confirmed the association between environmental noise exposure and several adiposity measures. The association was stronger in the presence of depressive symptoms.

Comparing acoustic models with measured noise levels in a Polypropylene production industrial complex

This paper presents a detailed comparison between the final noise source data, as documented in the Project Report, produced noise map during design phase, and the field-measured noise values, along with the empirically generated noise map during the plant's operational phase. The study investigates into the accuracy and reliability of the assessed noise map, evaluating its alignment with actual noise levels recorded on-site, identifies discrepancies between both the noise maps, pinpointing areas for improvement in predictive modelling. The goal is to see how well the predicted noise levels match up with the real-world situation, helping improve noise control strategies, specifically focus on noisy equipment, checking if the expected or calculated noise levels are the same with field measured values. By shedding light on these disparities, this study contributes to refining noise prediction models and improving the effectiveness of noise control measures in industrial settings.

Small-scale noise mapping for arbitrary regions using open source noise prediction module "NoiseModelling" and global databases

Extensive noise mapping has been crucial in shaping noise mitigation policies; however, assessing noise exposure in different scenarios remains challenging due to static maps that only represent pre-calculated sound levels. To fill this gap, this study introduces a novel noise mapping framework tailored to calculate sound levels in specific environments within small, arbitrary regions. Using the open-source noise prediction tool NoiseModelling and global databases of road networks, buildings, terrain, and population distribution on QGIS, this framework seamlessly integrates noise mapping procedures, including comprehensive data collection, receiver placement, sound level calculation, and visualization. The user-friendly graphical interfaces enable quick and easy generation of noise maps. The approach offers flexibility through customizable geometry and parameter settings to account for variations in noise sources and propagation characteristics, thereby providing stakeholders with valuable insights for policy formulation, environmental impact assessment, and community engagement. This methodology not only improves the accessibility and relevance of noise mapping but also empowers decision makers to implement tailored noise mitigation strategies that promote healthier and more livable environments.

Comparison of noise exposure cost and annoyance-related indicators in microscopic traffic simulations

Road traffic noise is one of the major sources of environmental noise and has been shown to increase risk of adverse health effects. For this reason, noise mapping is an efficient tool to assess and monitor city-wide noise levels in accordance with the Environmental Noise Directive (END). To relate these noise levels to the associated health effects, the noise map may be further analysed using exposure-response models, or with cost models that calculate the noise-related externalities of the traffic. With the use of microscopic traffic simulations, this assessment may be performed at a vehicle-specific level. A recently introduced methodology, the noise exposure cost, calculates the vehicle-specific contribution to the long-term social cost estimated at a macro-level based on the vehicle-specific noise contributions. However, the noise exposure cost methodology may not reflect the relative noise impact of individual vehicles, but rather solely reflect the noise contribution regardless of its relative impact to the noise levels at the time. The aim of this study is to investigate the possibility to use the linear sensitivity indicator as a basis for a non-linear weighting function in the noise exposure cost methodology, to allow the vehicle-specific noise exposure cost to better reflect the relative impact.

Nationwide noise mapping across Sweden's green landscape

This research project presents a mapping of noise levels in green areas across all of Sweden, with a particular emphasis on nature reserves, national parks, and other recreational spaces. Utilising the Nord2000 noise prediction method, our study incorporates the following noise sources: road traffic, railway traffic, wind turbines, and airports. Our analysis includes longer propagation distances than typical noise maps (up to 8 km) to account for distant sources, given the importance of low noise levels in pristine natural environments. Weather conditions play a crucial role in long-range sound propagation; therefore, we have integrated ten years of weather statistics (2013-2022) from the ERA5 climate dataset into our assessment. This mapping effort represents one of the first nationwide noise mapping initiatives with a specific focus on low-exposure natural areas. Our findings not only provide valuable insights for policymakers and stakeholders in managing and preserving the acoustic quality of Sweden's green spaces but also offer a foundation for analysing the potential impact of noise pollution on wildlife and biodiversity within these ecologically sensitive areas. The resulting noise map and relevant weather statistics are publicly released and downloadable. Participants from industry, government, and academia cooperated in this environmental monitoring project.

Mapping the health impacts of transport noise in the densely populated area of the Île-de-France region

The European Noise Directive (END) requires agglomerations of more than 100,000 inhabitants to produce strategic noise maps. In the Ile-de-France region, 14 agglomerations with a total population of 10,5 million inhabitants are concerned. Bruitparif applied the health impact assessment methodology recommended by the WHO to carry out a detailed territorial diagnosis of the issues related to transport noise. For this purpose, population exposure was assessed on the basis of strategic noise maps produced according to the 4th round of the END and the associated risks were calculated using the exposure-response functions published by the WHO in October 2018. The work continued with the valuation of healthy life years lost due to transport noise. Two types of maps have been produced with a 200 m2 grid as well as at the city scale: maps of collective health impacts related to population noise exposure and maps of average individual risk corresponding to the potential impact per individual. The combination of these two types of information has made it possible to highlight significant territorial disparities and to identify the sectors most concerned by the health issues related to noise, a prerequisite for prioritizing public action.

Impact of car electrification on urban noise pollution: a microscopic traffic simulation study

Noise pollution is a major health and well-being concern, being associated with, e.g., sleep disturbance, annoyance, and cardiovascular diseases. Road traffic is, by far, the largest contributor to this noise pollution in urban areas. With the growing electrification of cars in developed countries, it is commonly believed that road traffic noise pollution and the associated problems will disappear shortly in urban areas. However, at high speeds, the difference in noise emissions between internal-combustion-engine and electric vehicles is not significant, and at low speeds, the propulsion noise of electric cars is not negligible. Few works have quantitatively estimated the actual impact of passenger cars electrification on population exposure to noise, especially considering such aspects as the gradual transition towards a fully electric fleet. The present contribution thus aims to assess the evolution of population exposure to noise pollution, using a microscopic traffic simulation on the scale of an entire city, noise mapping, and various indicators, at multiple stages of this transition.

Effect of sound absorption on noise reduction in the automotive industry

Industrial noise is one of the most common physical factors that cause annoyance and damage workers' health in the long term. Precautions should be taken to reduce noise and improve acoustic performance in industrial working environments. This paper aims to analyze the acoustic performance of the automotive industry and contribute to the global outcomes of sustainability and the development of strategies to improve the quality of the working environment through improvement scenarios. For this purpose, the automotive industry in Türkiye was examined as a case study. In-situ acoustic measurements were made in the seat manufacturing unit of an automotive factory and the current situation was transferred to the simulation program. The effects of acoustic improvements on A-weighted sound pressure level and reverberation time at mid-frequencies (500, 1000, 2000 Hz) were investigated through three different scenarios. In the investigations, noise distributions were carried out through noise mapping. The A-weighted sound pressure levels in the automotive industry were reduced by approximately 15 dB. As a result of the study, suggestions for noise control precautions and their effects on the automotive industry seat manufacturing unit are presented.

Noise modeling of UAM around the urban vertiport

The present study aims to investigate the noise distribution around urban vertiport caused by UAM(Multicopter) and helicopter. Noise modelings were carried out using SoundPLAN software at the some vertiports in Seoul, Korea. Sound source model of UAM and helicopter were used as a form of hemisphere. Noise predictions were undertaken with three different operations including depart, level flight and landing. In order to evaluate the noise impact on the buildings around the vertiport, noise levels at the outer wall of nearby buildings were calculated as the three noise units including Leq, Lmax and Lden. Also, noise maps were drawn around the vertiport. As a result, it was found that average noise level of UAM is approximately 12 dB lower than the helicopter noise levels. Regarding the noise frequency distribution, most high noises are made at the mid-frequencies during landing hours while low frequency noise level around 63 Hz was dominant at take-off time.

Comparison of community response to road traffic noise by housing category

In 2023, a socio-acoustic survey on community response to road traffic noise was conducted in residential areas along several arterial roads in Kanagawa Prefecture as part of the Kanagawa University Cross-disciplinary Research Promotion Project. The survey targeted residents living in detached houses and apartment buildings. A questionnaire used for the survey was designed based on new findings from a survey conducted in 2021 using the Image Grid Method. Factors we focused were economic burden due to increased use of air conditioner, harmful impact of noise on family members, and importance of measures reducing noise. Regarding the noise exposure, we estimated Lden using noise maps, which were created for the survey. This paper presented the frequency distribution of the importance of measures reducing noise. In addition, applying multiple logistic regression analysis to individual data, we developed the exposure-response function for economic burden and harmful impact as well as listening disturbance and annoyance. Based on the results obtained, we discussed the importance of measures reducing noise and difference in exposure-response function between housing categories.

Building noise maps in Uruguay: a practical methodology

Uruguay is a small country in Latin America, with around 3400000 inhabitants. Its environmental legislation is still incomplete; for example, there is no national regulation on noise but only departmental Ordinances in each of its 19 Departments. Although it is well-known that they are very good management tools, noise maps are not mandatory in Uruguay. The Research Group on Environmental Noise at Universidad de la República has developed a research project that seeks the best practical methodology to build noise maps through manual measurements. The field work included the determination of the stabilization time of noise measurements, the comparison between long- and short-time measurements, the comparison between measurements taken at 1,20 m and 3,50 m, and the obtention of a national curve of highly annoyed people (%HA) with basis in the field measurements and simultaneous survey carried out on site. In this paper we present the results of these works and the proposed methodology for building noise maps throughout the country.

Impact of traffic simulation parameters on the estimation of noise exposure in an urban environment

Since road traffic is the most impactful noise source in the European cities, the evaluation of citizens' exposure is crucial. Although the noise map accuracy is affected by uncertainties in traffic volume, to perform extensive traffic monitoring is not practical and expensive, even in small cities. Traffic simulation software uses routing algorithms to suggest the fastest path to distribute vehicles from an origin through a network to a desired destination which interacts within the urban environment. Therefore, it could represent an important tool for noise mapping in the critical task to fill the data gaps in traffic volumes, also for implementing action plans using a suitable traffic management approach. However, there is a lack of evidence on how the choice of traffic simulation parameters influences noise estimation. In this work, we design a simulation framework to evaluate the impact of routing algorithms on the estimation of population noise exposure in an urban area. Using an open-source pipeline based on public databases and open-source software SUMO and NoiseModelling, we evaluated the implication on the traffic distribution and resulting noise exposure for a set of traffic model key parameters.

Methodology for determining new CNOSSOS-EU vehicle sound power coefficients using type approval data

CNOSSOS-EU is a standardized framework for strategic noise mapping across the European Union which member states are required to conduct every five years. The framework provides an approach to assess noise from different sources, including road traffic noise. Road traffic noise is primarily caused by vehicles. In CNOSSOS-EU, the vehicle exterior noise is modeled using fixed sound power coefficients. These coefficients were derived from measurements conducted up to 2006. Although significant progress has been made in reducing vehicle exterior noise, the existing model does not account for this technical progress. This paper first reviews the evolution of exterior noise legislation and its impact on vehicle noise levels. It then presents a new procedure for integrating the technical progress into vehicle source modeling in CNOSSOS-EU by incorporating type approval data. For demonstration purposes, this procedure is applied to up-to-date type approval data of M1 vehicles, resulting in a more accurate representation of current noise emissions. This research contributes to the refinement of the CNOSSOS-EU model, aligning it with the current state of technology and providing a more precise basis for environmental noise assessment.

Developing a combined mapping representation of air and noise pollutions

Airparif and Bruitparif, observatories for air and noise pollutions in the Ile-de-France region, have worked together to develop a combined mapping representation of air and noise pollutions. On the one hand, Bruitparif has tested different approaches to propose a noise indicator taking into account the various exposures to road, air and traffic noise, according to the strategic noise maps. On the other hand, Airparif has developed an air quality indicator taking into account the main regulated air pollutants. They have finally put together an original method of mapping representation of the double exposure to noise and air pollutions. Mapping combining air and noise pollutions is an efficient diagnostic tool for municipalities. This makes it possible to identify the areas at stake: those that are preserved from these pollutions and should be protected, and those that are highly exposed and where action must be taken. It offers a wide range of uses, like cross-referencing of air-noise data with the location of establishments receiving vulnerable groups, or making comparison with socio-economic data and health indicators.

Towards better visualizations of urban sound environments: insights from interviews

Urban noise maps and noise visualizations traditionally provide macroscopic representations of noise levels across cities. However, those representations fail at accurately gauging the sound perception associated with these sound environments, as perception highly depends on the sound sources involved. This paper aims at analyzing the need for the representations of sound sources, by identifying the urban stakeholders for whom such representations are assumed to be of importance. Through spoken interviews with various urban stakeholders, we have gained insight into current practices, the strengths and weaknesses of existing tools and the relevance of incorporating sound sources into existing urban sound environment representations. Three distinct use of sound source representations emerged in this study: 1) noise-related complaints for industrials and specialized citizens, 2) soundscape quality assessment for citizens, and 3) guidance for urban planners. Findings also reveal diverse perspectives for the use of visualizations, which should use indicators adapted to the target audience, and enable data accessibility.

Estimation of population exposed to road traffic noise in Kosovo highway using GIS modelling and roadside measurements

New highways have been introduced into Kosovo landscape in recent years. The trajectory of the highways crosses through the fields and in the middle of some previously remote rural settlements. This has changed the environment for these areas and the environmental noise is a major concern. This study aims to estimate the population exposed to high traffic noise levels around the highway routes in Kosovo. GIS has been used to model the highway lines, the terrain and the buildings on site. Roadside traffic noise measurements as well as traffic flow measurements have been conducted to approximate the noise sources. An approximate noise map has been generated for the studied area. The population exposed to daytime and nighttime road traffic noise were estimated. The results show the need for road traffic noise reduction measures and areas where they are most needed.

Ten years of experience with road noise auralisations

For more than a decade, The Danish Road Directorate has used auralisations to communicate the future road noise impact to the public. Auralisations are add-ons to the mandatory noise maps and assessments of noise exposed dwellings and people. Moreover, auralisations are very useful for public presentations like EIA etc. Road noise auralisations and presentations have been made to give the road's neighbours an impression and understanding of the impact, the road will have on the environment. Additionally, auralisations have been shown to be a very powerful tool in terms of explaining general acoustic terms and sound propagation e.g. the influence of wind direction and speed and the efficiency of future noise barriers of various heights. Presentation formats range from webpages to auditory presentations with calibrated headphones and overlaying introducing speak giving exact sound levels for the audience. Even videos and recorded soundscapes from specific locations have been used to create auralisations that are more trustworthy and recognizable for the audience. This presentation gives an overview of different formats of presentation and summarizes our experiences so far with different auralisations suiting the various cases of road projects. The use of simple auralisasions in Dynamic Noise Monitoring Maps will also be touched.