Development of web-based software for environmental impact assessment focusing on road traffic noise.

In the Republic of Korea, Environmental Impact Assessment (EIAs) precedes development projects to predict and analyze potential environmental effects. Generally, EIA noise evaluations utilize 2D noise prediction equations and correction coefficients. This method, however, offers only a sectional noise evaluation and has limitations in complex environments with diverse noise sources. Moreover, the determination of various variables during the EIA process based on subjective human judgment raises concerns about the reliability of the results. Thus, this study aims to develop software accessible via a web environment for user-friendly EIA noise evaluations. This software supports integrated data management and generates a 3D noise prediction model for more precise and realistic analysis of noise impacts, specifically focusing on road-traffic noise at this stage of development. The 3D noise prediction model and noise map generated by the developed software have been validated against through comparison with the results of onsite noise measurements and commercial EIA software, SoundPLAN. This validation aimed to assess the practical utility of the application.

Urban noise exposure assessment based on principal component analysis of points of interest.

Accurate qualitative and quantitative information on the characteristics of traffic noise exposure in densely populated urban areas is an important prerequisite for reasonable traffic noise control. The primary objective of this study is the development and application of a traffic noise exposure evaluation method based on points of interest (POIs). First, an automatic query arithmetic is used to acquire geospatial information, POIs data, building and network information from the webmap. Second, the attribute matrix of preprocessed POIs for the population is constructed. And the population distribution is obtained by principal component analysis (PCA) of POIs and Gaussian decomposition of demographic data. Then, the modified traffic noise line-source model is applied to calculate the noise distribution considering attenuation among buildings based on measured traffic flow parameters. Finally, with the help of the proposed noise evaluation indicators, and considering the noise function requirements (NFRs, which can be divided into four classes according to different area land-use types), traffic noise evaluation is realized. The proposed method is applied to a typical region with four NFR classes. It is concluded that the characteristics of traffic noise exposure are affected by traffic conditions, buildings, NFR classes and population distribution. And the crowds exposed to noise present aggregation effects, which are usually centered around specific buildings. In addition, POI types which people actives related suffer more serious noise exposure, and exposure is overestimated at low requirement regions without considering crowd distribution of the setting scenario.

Decision trees and labeling of low noise pavements as support for noise action plans.

Low noise pavements (LNPs) are a market driven trend to mitigate the high road traffic noise exposure levels. Their improvement towards acoustic efficiency and durability over time is a challenge since these factors can conflict with road primary functions, such as safety. LNPs are not always the most cost-effective solution in health effects prevention. Whilst Green Public Procurement (GPP) highlighted the importance of reducing rolling noise emissions by introducing new regulations for new-layed LNPs, the fixed minimum requirements are not exhaustive. Generally, limits are set following the Close ProXimity method, which is only source oriented. This method does not consider real traffic flows and it is not aimed at evaluating citizens' disturbance. This work presents strategy tools that could assist policymakers in choosing LNPs, when truly effective, over other mitigations. The approach includes a variety of indicators that would allow for comparing different facets of noise assessment. The proposed methodology does not require additional efforts from stakeholders because the measurements required for the estimation of the indicators must already be carried out for both verification of legal limits and GPP. The strategy tools are a decisional tree to support the evaluation of the applicability of a LNP before its approval, and an evaluation flowchart applicable after its laying to evaluate its efficiency. Finally, a first LNP labeling approach, based on the same set of indicators, is proposed. As a case study, these tools are applied to measurements performed before and after the laying of twelve LNPs part of the LIFE NEREiDE project.

Spatial assessment of the attributable burden of disease due to transportation noise in England.

BACKGROUND: Noise pollution from transportation is one of the leading contributors to the environmental disease burden in Europe. We provide a novel assessment of spatial variations of these health impacts within a country, using England as an example. METHODS: We estimated the burden of annoyance (highly annoyed), sleep disturbance (highly sleep disturbed), ischemic heart disease (IHD), stroke, and diabetes attributable to long-term transportation noise exposures in England for the adult population in 2018 down to local authority level (average adult population: 136,000). To derive estimates, we combined literature-informed exposure-response relationships, with population data on noise exposures, disease, and mortalities. Long-term average noise exposures from road, rail and aircraft were sourced from strategic noise mapping, with a lower exposure threshold of 50 dB (decibels) Lden and Lnight. RESULTS: 40 %, 4.5 % and 4.8 % of adults in England were exposed to road, rail, and aircraft noise exceeding 50 dB Lden. We estimated close to a hundred thousand (∼97,000) disability adjusted life years (DALY) lost due to road-traffic, ∼13,000 from railway, and âˆ¼ 17,000 from aircraft noise. This excludes some noise-outcome pairs as there were too few studies available to provide robust exposure-response estimates. Annoyance and sleep disturbance accounted for the majority of the DALYs, followed by strokes, IHD, and diabetes. London, the South East, and North West regions had the greatest number of road-traffic DALYs lost, while 63 % of all aircraft noise DALYs were found in London. The strategic noise mapping did not include all roads, which may still have significant traffic flows. In sensitivity analyses using modelled noise from all roads in London, the DALYs were 1.1x to 2.2x higher. CONCLUSION: Transportation noise exposures contribute to a significant and unequal environmental disease burden in England. Omitting minor roads from the noise exposure modelling leads to underestimation of the disease burden.

Burden of disease due to transportation noise in the Nordic countries.

BACKGROUND: Environmental noise is of increasing concern for public health. Quantification of associated health impacts is important for regulation and preventive strategies. AIM: To estimate the burden of disease (BoD) due to road traffic and railway noise in four Nordic countries and their capitals, in terms of DALYs (Disability-Adjusted Life Years), using comparable input data across countries. METHOD: Road traffic and railway noise exposure was obtained from the noise mapping conducted according to the Environmental Noise Directive (END) as well as nationwide noise exposure assessments for Denmark and Norway. Noise annoyance, sleep disturbance and ischaemic heart disease were included as the main health outcomes, using exposure-response functions from the WHO, 2018 systematic reviews. Additional analyses included stroke and type 2 diabetes. Country-specific DALY rates from the Global Burden of Disease (GBD) study were used as health input data. RESULTS: Comparable exposure data were not available on a national level for the Nordic countries, only for capital cities. The DALY rates for the capitals ranged from 329 to 485 DALYs/100,000 for road traffic noise and 44 to 146 DALY/100,000 for railway noise. Moreover, the DALY estimates for road traffic noise increased with up to 17% upon inclusion of stroke and diabetes. DALY estimates based on nationwide noise data were 51 and 133% higher than the END-based estimates, for Norway and Denmark, respectively. CONCLUSION: Further harmonization of noise exposure data is required for between-country comparisons. Moreover, nationwide noise models indicate that DALY estimates based on END considerably underestimate national BoD due to transportation noise. The health-related burden of traffic noise was comparable to that of air pollution, an established risk factor for disease in the GBD framework. Inclusion of environmental noise as a risk factor in the GBD is strongly encouraged.

Social Inequities in Exposure to Traffic-Related Air and Noise Pollution at Public Schools in Texas.

Although children are particularly vulnerable to the adverse impacts of vehicular pollution and spend significant portions of their time at school, previous studies have not examined or compared school-level social inequities in exposure to both traffic-related air and noise pollution in the same study area. We addressed this gap through a case study in Texas-the second-largest US state based on total population and number of children. Vehicular pollution exposure was measured using: (1) outdoor concentrations of nitrogen dioxide (NO2), a widely used proxy for traffic-related air pollution; and (2) road noise estimates from the US Department of Transportation's National Transportation Noise Mapping Tool. These variables were linked to data on locations and sociodemographic characteristics of children enrolled in Texas public schools. We found children attending schools with the highest exposure to both NO2 and road noise (top 25%) were significantly more likely to be Black, Hispanic, and eligible for free/reduced lunches (socioeconomically deprived). Results from multivariable generalized estimating equations that control for spatial clustering and other relevant factors revealed that schools with greater NO2 exposure were significantly more likely to serve racial/ethnic minority and younger students, while schools with greater exposure to road noise were significantly more likely to serve socioeconomically deprived and older students. These findings underscore the urgent need to reduce both air pollution and noise exposure at school locations, especially in schools attended by higher proportions of socially disadvantaged children that are often additionally burdened with other challenges.

Health impact assessment of road traffic noise exposure based on different densification scenarios in Malmö, Sweden.

While urbanization provides many opportunities to those arriving in thriving urban areas, a greater number of residents necessitates the expansion of housing and infrastructure. This is often achieved through densification, which can lead to increased noise, particularly through increased road traffic. A key challenge of promoting healthy urban planning is to understand potential health effects, especially on the local level. The aim of the present study is, therefore, to estimate and compare the health impacts of road traffic noise exposure for various urban densification scenarios within a neighborhood (Lorensborg) in Malmö, Sweden. The three scenarios include 1) Present-day, representing the study area as it is presently organized; 2) Planned municipal strategy (the city of Malmö's own densification plans) and 3) Health-centred, which involves major structural alterations and reflects an effort prioritize a health-centred approach. Noise was modelled using the Nordic prediction method for road traffic. Health outcomes included noise annoyance, adverse sleep disturbance, ischemic heart disease (IHD) incidence and mortality. Within all scenarios, a large proportion of the study population was exposed above the WHO's health-based guideline value (Lden 53 dB): >80% for Present-day and Planned municipal strategy scenarios, and almost 50% in the Health-centred scenario. Still, densifying Lorensborg (population ≈9,600) according to the Health-centred scenario could prevent 549 cases of highly annoyed, 193 cases of adverse sleep disturbance, 4.7 new cases of IHD (8.9% of total cases), and 1.5 deaths due to IHD (17.8% of IHD mortality) annually. The results demonstrated that it is possible to considerably lower the health impact with a more health-centred densification strategy. Important co-benefits for public and environmental health include air pollution reduction and green space creation, although their health effects were not quantified in the present study. Urban planning initiatives must be more ambitious in order to create healthy, sustainable cities.

Deep Learning-Based Road Traffic Noise Annoyance Assessment.

With the development of urban road traffic, road noise pollution is becoming a public concern. Controlling and reducing the harm caused by traffic noise pollution have been the hot spots of traffic noise management research. The subjective annoyance level of traffic noise has become one of the most important measurements for evaluating road traffic pollution. There are subjective experimental methods and objective prediction methods to assess the annoyance level of traffic noise: the subjective experimental method usually uses social surveys or listening experiments in laboratories to directly assess the subjective annoyance level, which is highly reliable, but often requires a lot of time and effort. The objective method extracts acoustic features and predicts the annoyance level through model mapping. Combining the above two methods, this paper proposes a deep learning model-based objective annoyance evaluation method, which directly constructs the mapping between the noise and annoyance level based on the listening experimental results and realizes the rapid evaluation of the noise annoyance level. The experimental results show that this method has reduced the mean absolute error by 30% more than the regression algorithm and neural network, while its performance is insufficient in the annoyance interval where samples are lacking. To solve this problem, the algorithm adopts transfer learning to further improve the robustness with a 30% mean absolute error reduction and a 5% improvement in the correlation coefficient between the true results and predicted results. Although the model trained on college students' data has some limitations, it is still a useful attempt to apply deep learning to noise assessment.

Analogical Assessment of Train-Induced Vibration and Radiated Noise in a Proposed Theater.

This study presents the analogical assessment of the train-induced vibration and radiated noise in a proposed theater. The theater is to be constructed in a region with crowded metro lines, and the assessment is implemented in an analogical building with comparable structural type and metro condition. Prior to the assessment, the comparability of the analogical building with the theater is validated using the train-induced ground vibration. With the same horizontal distance from the metro line, the train-induced vibration level in the analogical building is 9 dB higher than that in the construction site of the theater. Such results indicate that the lack of soil layers may lead to a dramatic increase in train-induced vibration in the building. In the staircase of the analogical building, the train-induced radiated noise reached 55 dB (A), which is 10 dB (A) higher than the daytime allowable level. As the most important indicator, the noise rating number in the cinema of the analogical building is NR-43, which put forward an enormous challenge on the construction of the theater with a denoise demand of 23 dB. The analogical method applied in this study provides an effective and practical way for the assessment of train-induced vibration and radiated noise in proposed vibration-sensitive buildings. The assessment results that provide necessary reference and support for the anti-vibration design will help guarantee the stage effect of the theater.

Pathways to Environmental Inequality: How Urban Traffic Noise Annoyance Varies across Socioeconomic Subgroups.

The article investigates how socioeconomic background affects noise annoyance caused by residential road traffic in urban areas. It is argued that the effects of socioeconomic variables (migration background, education, and income) on noise annoyance tend to be underestimated because these effects are mainly indirect. We specify three indirect pathways. (1) A "noise exposure path" assumes that less privileged households are exposed to a higher level of noise and therefore experience stronger annoyance. (2) A "housing attributes path" argues that less privileged households can shield themselves less effectively from noise due to unfavorable housing conditions and that this contributes to annoyance. (3) Conversely, an "environmental susceptibility path" proposes that less privileged people are less concerned about the environment and have a lower noise sensitivity, and that this reduces their noise annoyance. Our analyses rest on a study carried out in four European cities (Mainz and Hanover in Germany, Bern and Zurich in Switzerland), and the results support the empirical validity of the three indirect pathways.

Spatial modelling and inequalities of environmental noise in Accra, Ghana.

Noise pollution is a growing environmental health concern in rapidly urbanizing sub-Saharan African (SSA) cities. However, limited city-wide data constitutes a major barrier to investigating health impacts as well as implementing environmental policy in this growing population. As such, in this first of its kind study in West Africa, we measured, modelled and predicted environmental noise across the Greater Accra Metropolitan Area (GAMA) in Ghana, and evaluated inequalities in exposures by socioeconomic factors. Specifically, we measured environmental noise at 146 locations with weekly (n = 136 locations) and yearlong monitoring (n = 10 locations). We combined these data with geospatial and meteorological predictor variables to develop high-resolution land use regression (LUR) models to predict annual average noise levels (LAeq24hr, Lden, Lday, Lnight). The final LUR models were selected with a forward stepwise procedure and performance was evaluated with cross-validation. We spatially joined model predictions with national census data to estimate population levels of, and potential socioeconomic inequalities in, noise levels at the census enumeration-area level. Variables representing road-traffic and vegetation explained the most variation in noise levels at each site. Predicted day-evening-night (Lden) noise levels were highest in the city-center (Accra Metropolis) (median: 64.0 dBA) and near major roads (median: 68.5 dBA). In the Accra Metropolis, almost the entire population lived in areas where predicted Lden and night-time noise (Lnight) surpassed World Health Organization guidelines for road-traffic noise (Lden <53; and Lnight <45). The poorest areas in Accra also had significantly higher median Lden and Lnight compared with the wealthiest ones, with a difference of ∼5 dBA. The models can support environmental epidemiological studies, burden of disease assessments, and policies and interventions that address underlying causes of noise exposure inequalities within Accra.

Impact of road traffic noise on annoyance and preventable mortality in European cities: A health impact assessment.

BACKGROUND: Road traffic is the main source of environmental noise in European cities and one of the main environmental risks to health and wellbeing. In this study we aimed to provide an in-depth assessment of available road traffic noise data and to estimate population exposure and health impacts for cities in Europe. METHODS: We conducted the analysis for 724 cities and 25 greater cities in 25 European countries. We retrieved road traffic strategic noise maps delivered under the Environmental Noise Directive (END) or available from local sources. We assessed noise exposure using the 24 h day-evening-night noise level indicator (Lden) starting at exposure levels of 55 dB Lden - based on data availability - for the adult population aged 20 and over (n = 123,966,346). For the adults exposed to noise levels above 55 dB Lden we estimated the health impacts of compliance with the World Health Organization (WHO) recommendation of 53 dB Lden. Two primary health outcomes were assessed: high noise annoyance and Ischemic Heart Disease (IHD), using mortality from IHD causes as indicator. Exposure Response Functions (ERFs) relating road traffic noise exposure to annoyance and IHD mortality were retrieved from the literature. Uncertainties in input parameters were propagated using Monte Carlo simulations to obtain point estimates and empirical 95% Confidence Intervals (CIs). Lastly, the noise maps were categorized as high, moderate and low quality following a qualitative approach. RESULTS: Strategic noise map data was delivered in three distinct formats (i.e. raster, polygon or polyline) and had distinct noise ranges and levels of categorization. The majority of noise maps (i.e. 83.2%) were considered of moderate or low quality. Based on the data provided, almost 60 million adults were exposed to road traffic noise levels above 55 dB Lden, equating to a median of 42% (Interquartile Range (IQR): 31.8-64.8) of the adult population across the analysed cities. We estimated that approximately 11 million adults were highly annoyed by road traffic noise and that 3608 deaths from IHD (95% CI: 843-6266) could be prevented annually with compliance of the WHO recommendation. The proportion of highly annoyed adults by city had a median value of 7.6% (IQR: 5.6-11.8) across the analysed cities, while the number preventable deaths had a median of 2.2 deaths per 100,000 population (IQR: 1.4-3.1). CONCLUSIONS: Based on the provided strategic noise maps a considerable number of adults in European cities are exposed to road traffic noise levels harmful for health. Efforts to standardize the strategic noise maps and to increase noise and disease data availability at the city level are needed. These would allow for a more accurate and comprehensive assessment of the health impacts and further help local governments to address the adverse health effects of road traffic noise.

Burden of diseases attributed to traffic noise in the metropolis of Tehran in 2017.

Although road traffic noise is the most important source of environmental noise emission in large cities, little is known about health burden. The present study was conducted to estimate the burden of diseases attributed to traffic noise in the metropolis of Tehran in 2017. Using noise maps provided by the municipality of Tehran, we calculated population exposure distribution in term of Ldn and Lnight and the number of DALYs lost due to ischemic heart disease, hypertension, high sleep disturbance, annoyance and stroke endpoints based on the World Health Organization Environmental Noise Guidelines for the European Region. We applied published dose-response functions to estimate the traffic noise burden for high sleep disturbance and annoyance. We estimated 61,284 DALYs or 697 DALYs per 100,000 population attributed to traffic noise in Tehran for the reference year 2017. Highly sleep disturbance with a share of 58.74% of the DALYs was recognized as the most important contributor of disease burden, and noise annoyance with a share of 23.12% was ranked next. Ischemic heart disease (11.71%), stroke (5.12%), and hypertension (1.31%) were ranked third to fourth, respectively, in terms of the burden of disease caused by environmental noise. A considerable fraction of the population of Tehran lives in areas with an environmental noise higher than the standard level. The findings showed that traffic noise pollution is an important environmental risk factor in Tehran imposes the greatest burden on the community, mainly through highly sleep disturbance and noise annoyance endpoints.

Health impact assessment of transportation noise in two Estonian cities.

Transportation noise is a growing public health concern worldwide, especially in urban areas, causing annoyance, sleep disturbance, cardiovascular diseases and other health effects. Recently, European Commission (EC) has developed a mutual methodology for assessing health impacts of transportation noise in European Union using strategic noise mapping. Applying this methodology, our aim was to quantify the health effects of road, rail and aircraft noise in two Estonian cities, Tallinn and Tartu. We also aimed to assess sensitivity of this methodology, while implementing lower threshold values and employing additional health outcomes. The proportion of highly annoyed residents due to road traffic noise was 11.6% in Tallinn, and 9.2% in Tartu; around 2.5% residents in both cities could have high sleeping disturbances. As exposure to railway and aircraft noise was relatively low in both cities, people with high annoyance and high sleep disturbance caused by railway and aircraft noise was below 1%. Ischemic heart disease (IHD) cases attributable to road traffic noise was estimated to be 122.6 in Tallinn and 21.5 in Tartu. Altogether transportation noise was estimated to cause 1807 disability adjusted life years (DALYs) in Tallinn and 370 DALYs in Tartu. The health costs were calculated as €126.5 and €25.9 million annually, respectively in the two cities. When we included higher number of health outcomes (stroke incidence, IHD deaths) and lowered exposure threshold by 5 dB, the annual burden of disease was doubled. As the latest epidemiological studies showed transportation noise having larger number of effects on lower noise levels, the results with the currently applied European Commission health impact assessment (HIA) methodology were rather conservative. Despite of uncertainties associated to applied methodology, transportation noise, especially road traffic noise, is an important environmental risk factor, that leads to considerable loss of healthy life years and causes large health costs in urban areas.

The Burden of Disease Due to Road Traffic Noise in Hesse, Germany.

Road-traffic-noise exposition is widespread in Germany and can have harmful health effects. As guidance for informed decision-making, we estimated the environmental burden of disease attributable to road-traffic noise in Hesse, Germany as disability-adjusted life-years (DALYs). Using detailed road-traffic-noise exposure data provided by the Hessian Agency for Nature Conservation, Environment, and Geology (HLNUG), we calculated the DALYs due to road-traffic noise > 40 dB(A) L24h (unweighted average 24 h noise level) and other noise metrics for endpoints with known dose-response functions and evidence in the literature (NORAH-study on disease risks and WHO reviews): cardiovascular disease, depressive disorders, road-traffic annoyance, and sleep disturbance. We calculated the population-attributable fractions (PAF) for road-noise-related cardiovascular disease (hypertensive heart disease, ischemic heart disease, and stroke) and depressive disorders in the population using published relative risk estimates. We multiplied the PAFs with the Hessian proportion of the 2015 WHO DALY estimates for Germany in people aged ≥ 40 years. For high annoyance and high sleep disturbance, we used published dose-response functions to determine the burden for residents of all ages. For Hesse, we found a total of 26,501 DALYs attributable to road-traffic noise or 435 DALY per 100,000 persons for the reference year, 2015. Further, we estimated that a hypothetic uniform road-traffic-noise reduction of 3 dB would prevent 23% of this burden of disease.

A study on the assessment of traffic noise induced annoyance and awareness levels about the potential health effects among residents living around a noise-sensitive area.

The present cross-sectional study aimed to evaluate the risk factors for traffic noise-induced annoyance and also assess the awareness levels among the exposed population concerning the health impacts caused by traffic noise. Field measurements were made to validate the application of the standard noise models, which were later used to present the acoustical environment and assess the exposure level around a super-speciality hospital surrounded by a residential zone. Results from the noise maps and façade maps revealed that the area was exposed to noise levels exceeding the upper safe limits by more than 10 dB(A). The effect of exposure in the form of annoyance and the awareness level were evaluated using a questionnaire survey in a sample of 565 residents. Attention questions were incorporated in the questionnaire, and the awareness level was evaluated using the mean awareness index score. Respondents living in noisy areas were having a higher risk for annoyance as compared to those living in quiet areas (OR = 4.06; 95% CI = 2.79-5.88). Reporting poor sleep quality, being sensitive to noise, and noise perception at home were the significant risk factors for annoyance. Most of the respondents were classified as having no/little awareness about serious health ailments caused by traffic noise. Lower awareness levels, despite a higher literacy rate and a higher percentage of the young population, imply that there is a need for undertaking mass awareness programmes so that the impacts can be reduced to a minimum, if not eliminated.

Aircraft Noise Distribution as a Fairness Dilemma-A Review of Aircraft Noise through the Lens of Social Justice Research.

Aircraft noise exposure is a health risk and there is evidence that noise annoyance partly mediates the association between noise exposure and stress-related health risks. Thus, approaches to reduce annoyance may be beneficial for health. Annoyance is influenced by manifold non-acoustic factors and perceiving a fair and trustful relationship between the airport and its residents may be one of them. The distribution of aircraft noise exposure can be regarded as a fairness dilemma: while residents living near an airport may seem to have some advantages, the majority of residents living under certain flight routes or in their immediate proximity suffer from the disadvantages of the airport, especially the noise. Moreover, a dilemma exists between the airport's beneficial economic impact for a region and the physical and psychological integrity of residents. Aircraft noise exposure through the lens of social justice research can help to improve our understanding of noise annoyance. Research indicates that the fairness perceptions of the parties involved can be enhanced by (a) improving individual cost-benefit ratios, (b) providing a fair procedure for deciding upon the noise distribution, and (c) implementing fair social interaction with residents. Based on the review of evidence from social justice research, we derive recommendations on how fairness aspects can be integrated into aircraft noise management with the purpose of improving the relationship between the airport and its residents, to reduce annoyance, and to enhance the acceptance of local aviation and the airport as a neighbor.

Comparison of Road Noise Policies across Australia, Europe, and North America.

Developing innovative noise policies that build on international best practices is difficult when policies around the world differ along many dimensions, ranging from different sources covered to different levels of governance involved. This is particularly critical in the context of road traffic, identified as one of the main culprits leading to noise-associated complaints and health issues. In this article, we document the wide range of specifications observed in road traffic policies and propose a methodology to compare noise limits across noise policies. First, we present the responsibilities of administrative governments according to the scope (e.g., emission vs. exposure). Second, we compare noise limits by scope and geographic areas by separating acoustic indicators (overall and event indicators). Third, we convert overall outdoor noise limits into a common basis using the method described by Brink and his associates (2018) and compare them with the World Health Organization (WHO)'s recommendations (2018). Finally, measurement protocols are also compared across outdoor noise policies. This paper shows that road noise is managed at several administrative levels using approaches that are either centralized or decentralized. We also observed disparities in the associated noise limits across geographic areas. The converted outdoor noise limits generally exceeded the WHO's recommendations (2018). Finally, this paper outlines how outdoor measurement protocols vary across geographic areas. However, similarities were identified between state and provincial noise policies within the same country.

Geographic Ecological Momentary Assessment (GEMA) of environmental noise annoyance: the influence of activity context and the daily acoustic environment.

BACKGROUND: Noise annoyance is considered to be the most widespread and recognized health effect of environmental noise. Previous research is mostly based on the static study of residential environmental noise, but few studies have focused on the effects of noise exposure in different activity contexts on real-time annoyance. The two deficiency are that they neglect the influence of activity context besides residence and fail to reflect the difference of time-scale effect of noise influence. METHODS: Using portable noise and air sensors, GPS-equipped mobile phones, questionnaire survey, and geographic ecological momentary assessment (GEMA), this paper measured the environmental noise and real-time noise annoyance of participants at different activity places. Hierarchical logistic regression models were used to examine the effects of environmental noise on people's real-time annoyance. The paper further considered the influence of the geographic context of the activity places and daily acoustic environment on participants' real-time annoyance. Further, a nonlinear regression model was constructed using Random Forest to further examine the nonlinear relationship between environmental noise and real-time annoyance. RESULTS: The results showed that: (1) the average cumulative equivalent sound level during was 55 dB (A) when the participants responded to the EMA surveys; (2) Only the temperature of activity places had an influence on momentary annoyance and the higher the temperature, the more likely participants were annoyed; (3) Participants with higher perception of noise pollution in residential communities were more likely to be annoyed. However, participants with higher daily exposure to noise were less likely to feel annoyed; (4) The threshold value of the effect of noise on real-time annoyance was 58 dB (A) to 78 dB (A). CONCLUSIONS: These findings can guide the development of urban planning and environmental noise standards and also provide a reference for noise barrier requirements for different activity places.

Exposure assessment to road traffic noise levels and health effects in an arid urban area.

Road traffic noise exposures have been recognized as serious environmental health concerns, especially in most developing countries with arid climate conditions, rapid increase in vehicle population, and limited traffic management systems. The excessive noise exposure level is associated with increase in the incidence of cardiovascular diseases and anxiety, including annoyance. This study aimed at determining traffic noise levels in residential areas, including the assessment of its annoyance and health effects based on the people's perception and reportage. To do so, field measurement and traffic noise modeling were carried out in six road points to estimate the current noise levels along various roads close to human inhabitants in Muscat Governorate, Sultanate of Oman. The detailed measured noise levels in urban residential areas across the selected roads showed that noise levels have exceeded the local and international threshold limits at all locations during the entire day. The high sound levels (48.0-56.3 dBA) were observed using the US Federal Highway Administration's Traffic Noise Model (TNM, version 2.5) results, which were in agreement with the observed (56.3-60.4 dBA) data. To assess health implication to residents through interviews (n = 208), annoyance at home was found to be little (32%), moderate (28%), and high (9%) in comparison with workplace settings of 42%, 43%, and 15%, respectively. Nineteen percent of the interviewees had difficulties in sleeping, while 19.8% experienced stress due to road traffic noise exposures. Moreover, a strong association (p < 0.05) was established between the use and objection of noise barriers. The study revealed high noise levels and the prevalence of annoyance and health effects among the exposed population. Therefore, immediate action is required to tackle the current noise levels.