Road traffic noise abatement scenarios in Gothenburg 2015 - 2035

Investigating important and necessary conditions to analyse traffic noise levels at intersections in mid-sized cities

Traffic noise is a major problem for urban residents, especially near intersections. In order to effectively manage and control traffic noise, there is a need for a better understanding of noise-influencing variables at intersections. In this way, the study aims to identify and distinguish the important and necessary conditions corresponding to the particular traffic noise level. Using 342 h of field data from 19 intersections in Kanpur, the current research has used the Partial Least Square-Structural Equation Modelling (PLS-SEM) and Necessary Condition Analysis (NCA). The study determines that traffic volume, honking, speed, and median width are important factors. Traffic volume and honking are positively affecting traffic noise level, while speed and median width have a negative effect. Further investigation reveals that only traffic volume and honking are necessary to achieve a particular traffic noise level. Policymakers can use these findings to manage and control traffic noise at intersections.

Contributions of residential traffic noise to depression and mental wellbeing in Hong Kong: A prospective cohort study

Prior studies on the association between traffic noise and mental health have been mostly conducted in settings with lower population densities. However, evidence is lacking in high population-density settings where traffic noise is more pervasive and varies by topography and the vertical elevation of the residential unit. This study aimed to assess the mental health impact of residential traffic noise in one of the world's most urbanised populations. Data were analysed from 13,401 participants aged ≥15 years in a prospective cohort in Hong Kong from 2009 to 2014. Residential traffic noise level was estimated using 3D-geocoding and validated models that accounted for sound propagation in a highly vertical landscape. The 24-h day-night exposure to traffic noise, denoted as Ldn, was estimated with a 10-dB(A) penalty for night hours. Probable depression and mental wellbeing were assessed using the Patient Health Questionnaire-9 and the Short Form Health Questionnaire SF-12v2, respectively. Mixed effect regressions with random intercepts were used to examine the association between traffic noise and mental health outcomes. Residential road traffic noise (for each increment of 10 A-weighted decibels [dB(A)] 24-h average exposure) was associated with probable depression (odds ratio (OR) = 1.17, 95% CI: 1.05, 1.31), and poorer mental wellbeing (mean difference = -0.19, 95% CI: 0.31, -0.06), adjusting for sociodemographics, smoking, body mass index, self-reported health, proximity to green space, and neighbourhood characteristics (average household income, population density, and Gini coefficient). The results were robust to further adjustment for air pollution. In stratified analyses, residential traffic noise was associated with probable depression and poorer mental wellbeing among students and individuals aged 15-34 years. Residential traffic noise was associated with probable depression and poorer mental wellbeing in a highly urbanised setting. As traffic noise is increasing in urban settings, the public health impact of noise pollution could be substantial.

The co-benefits of electric mobility in reducing traffic noise and chemical air pollution: Insights from a transit-oriented city

Traffic noise is a growing threat to the urban population. Prolonged exposure to traffic noise has been linked to negative health consequences such as annoyance, sleep disturbances and cardiovascular diseases. While electric vehicles are known to have lower noise profiles, the impacts of electric mobility on traffic noise, especially for electrified heavy-duty vehicles, have not been thoroughly examined. This study aims to examine the impacts of both electric light-duty vehicles and electric buses on traffic noise levels in a highly urbanized city. Traffic noise along the source line and pedestrian network was first estimated and mapped to illustrate its spatiotemporal variations. Then, scenario analysis was used to compare the impacts. Population potentially benefiting from reduced traffic noise in the neighbourhoods and the associated health impacts were also estimated. Results indicate that electric buses have a greater potential to reduce traffic noise, with a maximum reduction of 4.4 dBA during daytime in the urban cores. With all bus fleet electrified, around 60% of the population can benefit from a reduction of 1 dBA at the street environment, 15.3% for 1-2 dBA, and 4.3% for more than 2 dBA. The estimated reduction of preventable deaths and preventable cases of diseases per 100,000 population are 4.15 and 112.99 respectively. The findings shed important insights into prioritizing bus routes to be electrified in urban areas for maximizing health co-benefits.

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 (L_den 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.

Effects of noise on pedestrians in urban environments where road traffic is the main source of sound

Research combining the measurement of objective variables with surveys of people's perception of noise on city streets is useful in terms of understanding the impact of urban noise on the population and improving the environment. Although previous investigations have analysed the factors that may influence the noise annoyance of citizens, it is usually considered as a global aspect. This paper presents research based on in situ surveys and objective variables (urban, meteorological and noise indicators) to evaluate some specific effects of noise on pedestrians in urban environments where road traffic is the main source of sound. The results show significant relationships of the effects of noise and perceptions of how noisy urban environments are with variables such as building height, road category and temperature, with correlation coefficients ranging from 0.37 to 0.64. Significant correlations between these subjective variables and the acoustic variables were also found, with explanations of variability that reached values of up to 50 %. A multivariate analysis revealed that both urban variables (especially the category of street) and environmental variables can be an alternative or a complement to models predicting the effects and perception of environmental noise based only on acoustic variables.

Integrated Evaluation Method of the Health-Related Physical Environment in Urbanizing Areas: A Case Study From a University Campus in China

Environmental deterioration in urbanizing areas increases the risks of sudden death as well as chronic, infectious, and psychological diseases. Quantifying health-related physical environment can assess the health risk of urban residents. This study uses an integrated evaluation method to simulate the health-related physical environment in the four dimensions of acoustic, wind, thermal, and landscape. According to the case study of one university campus in an urbanizing area in China, results show that (1) areas with unqualified equivalent A sound levels are generally the sports area, green square 1 and laboratory areas, and residents who stay in these areas for a long time suffer the risks of hearing loss and mental stress. (2) The windless area ratio of teaching area 1 and dormitory area 4 is larger than 20%, and respiratory health risks increase because these areas relate to relatively wind discomfort. (3) The high-temperature zone ratio of sports area and green square 2 is larger than 50%, and heatstroke risks increase since these areas relate with low thermal comfort. (4) The overall landscape perception level of dormitories and dining areas is lower than that of the teaching area, and it can cause anxiety and irritability. (5) The sports area has the lowest average overall score of the health-related physical environment among all functional areas, followed by laboratory areas. These findings indicate that the proposed model and method can be valuable tools for the pre-evaluation and optimization of urban planning. It can reduce the health risks of residents in urbanizing areas and can benefit residents' health and urban sustainable development.

Variability of traffic noise pollution levels as a function of city size variables

Noise levels measured in 27 cities with different areas (from 0.6 km² to 59.27 km²) and populations (from approximately 2000 to 70,000 inhabitants) were compared with respect to five different urban characteristics (population, area, total street length, density, and linear density). Comparisons were conducted for both overall city noise levels and noise registered on five types of roads with different functionality using the Categorisation Method. The results showed that four of the five cities' characteristics presented a significant correlation with the noise levels (all except for density). The calculated correlations were better for noise levels in the different categories than the overall noise values, with higher explained variability on the streets with more traffic. Therefore, the road categorisation method can be used not only to assess the noise variations within cities, but also to better explain the effect of noise on the analysed city characteristics. The results of the calculated relationships enable the estimation of noise levels both currently and in future urban developments of noise values on different types of streets.

Algorithm for Reducing Truck Noise on Via Baltica Transport Corridors in Lithuania

The section of Via Baltica going through the territory of the Republic of Lithuania is the most traffic intensive land logistics corridor in the country. The annual transportation volume has been increasing on this road; thus, the reduction of pollution caused by vehicles has become important. If gas emissions are regulated, and carriers have to pay pollution taxes, this does not apply to noise levels. The article presents the traffic intensity in this logistics corridor, measurements of the noise level at the characteristic points, its relation to the number of vehicles passing through it and an expert evaluation of proposed methods for noise energy reduction. Environmental noise is an unwanted or harmful sound that propagates in terms of both duration and geographical coverage. Noise is associated with many human activities, but road, rail and air traffic noises have the greatest impact. Due to irrationally arranged transport network, the transit flow of freight transport crosses residential areas of the city, places of rest and recreation of the population, causing high noise levels in adjacent areas. This is the biggest problem for the urban environment. Environmental noise affects many Europeans and is therefore considered by society to be one of the biggest environmental problems. This article presents an assessment of a new traffic noise algorithm. The presented expert survey on noise energy reduction allows choosing the most appropriate method for reducing noise energy in Via Baltica transport logistics corridor. Based on the expert survey, a hierarchical table for noise energy reduction was compiled. It will allow assessing the validity of individual noise energy reduction solutions. It has become relevant for improving infrastructure of other transport corridors and choosing the most appropriate solutions to reduce vehicle noise pollution. A further application of this model can be focused on economic evaluation, forecasting of expected benefits and so on.

Evaluation of exposure to road traffic noise: Effects of microphone height and urban configuration

Noise pollution is a major environmental problem due to its impact on human health and implications for other spheres of society. Since road traffic is the main source of noise pollution, the use of measurement methodologies to accurately determine the environmental noise levels to which the façades of buildings in cities are exposed is an important issue. This paper presents an experimental study in urban environments that uses different configurations to evaluate the influence of the position of the microphone and the parking lanes on the levels of road traffic noise to which the population is exposed. In urban settings in which sound waves propagate without obstacles between the lanes of traffic and the receivers, broadband results for the differences between noise levels measured by microphones placed at heights of 4.0 and 1.5 m showed a significant increase with an increase in the distance between the microphone and sound source of between -0.8 and 0.9 dBA over a range from 2 to 8 m. This difference between the two microphones was greater at points where a lane of parked vehicles was located between the road traffic lanes and the receivers were placed near the façades of building. At the same heights, the broadband difference in sound levels ranged from 2.7 to 4.5 dBA. This acoustic shielding effect due to the presence of parked vehicles started to be relevant in the 250 Hz band and increased progressively with frequency. Taking into account these experimental results and the recommendations in the European Noise Directive, it would be important to apply corrections to sound indicators for road traffic noise that are related to the height of the microphone. Making a distinction between urban configurations with and without lines of parked vehicles between the microphone and the road traffic lanes would be advisable.

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.

Evaluation of urban inland waterway traffic noise using a modified Nord 2000 prediction model

This study developed a prediction model for estimating urban inland waterway traffic noise emission level. The model based on the Scandinavian Nord 2000 method, which was modified by adding two categories of traffic flow, comprising light and heavy vessels, as well as vessel average speed to the calculating equations. Meanwhile, the influences of the water surface and embankment were also considered in the established model. Model verification was conducted using the data surveyed at the 30 sampling points of Danjinlicaohe Channel in Jiangsu Province of China. A high correlation was found between the predicted and measured noise values L_Aeq (Pearson correlation coefficient = 0.949, p < 0.01). And the mean difference between the predicted and measured noise values was 0.16 ± 1.28 dBA. The results showed that the proposed model had higher accuracy than the unmodified Nord 2000 method and can be applied for predicting vessel noise exposure level on inland waterway of China.

Burden of disease from transportation noise and motor vehicle crashes: Analysis of data from Houston, Texas

BACKGROUND

Transportation systems have an essential role in satisfying individuals' needs for mobility and accessibility. Yet, they have been linked to several adverse health impacts, with a large, but modifiable, burden of disease. Among the several transportation-related health risk factors, this study focused on transportation-related noise as an emerging exposure whose burden of disease remains partially recognized. We compared premature deaths potentially attributable to transportation-related noise with deaths from motor vehicle crashes, a well-researched and widely recognized transportation risk factor.

METHOD

We employed a standard burden of disease assessment framework to quantify premature cardiovascular diseases mortality attributable to transportation-related (road and aviation) noise at the census tract level (n = 592) in Houston, Texas. The results were compared to motor vehicle crash fatalities, which are routinely observed and collected in the study area. We also investigated the distribution of premature deaths across the city and explored the relationship between household median income and premature deaths attributable to transportation-related noise.

RESULTS

We estimated 302 (95% CI: 185-427) premature deaths (adults 30-75 years old) attributable to transportation-related noise in Houston, compared to 330 fatalities from motor vehicle crashes (adults younger than 75 years old). Transportation-related noise and motor vehicle crashes were responsible for 1.7% and 1.9% of all-cause premature deaths in Houston, respectively. Households with lower median income had a higher risk of adverse exposure and premature deaths potentially attributable to transportation-related noise. A larger number of premature deaths was associated with living in the central business district and the vicinity of highways and airports.

CONCLUSION

This study highlighted the significant contribution of transportation-related noise and motor vehicle crashes to premature deaths in the city of Houston. The analogy between the estimated premature deaths attributable to transportation-related noise and motor vehicle crashes showed that the health impacts of transportation-related noise were as significant as motor vehicle crashes. The estimated premature death rate attributable to transportation-related noise was also comparable to the death rate caused by suicide, influenza, or pneumonia in the US. There is an urgent need for imposing policies to reduce transportation noise emissions and human exposures and to equip health impact assessment tools with a noise burden of disease analysis function.

Stabilization of a p-u Sensor Mounted on a Vehicle for Measuring the Acoustic Impedance of Road Surfaces

The knowledge of the acoustic impedance of a material allows for the calculation of its acoustic absorption. Impedance can also be linked to structural and physical proprieties of materials. However, while the impedance of pavement samples in laboratory conditions can usually be measured with high accuracy using devices such as the impedance tube, complete in-situ evaluation results are less accurate than the laboratory results and is so time consuming that a full scale implementation of in-situ evaluations is practically impossible. Such a system could provide information on the homogeneity and the correct laying of an installation, which is proven to be directly linked to its acoustic emission properties. The present work studies the development of a measurement instrument which can be fastened through holding elements to a moving laboratory (i.e., a vehicle). This device overcomes the issues that afflict traditional in-situ measurements, such as the impossibility to perform a continuous spatial characterization of a given pavement in order to yield a direct evaluation of the surface’s quality. The instrumentation has been uncoupled from the vehicle’s frame with a system including a Proportional Integral Derivative (PID) controller, studied to maintain the system at a fixed distance from the ground and to reduce damping. The stabilization of this device and the measurement system itself are evaluated and compared to the traditional one.

Environmental Noise around Hospital Areas: A Case Study

Due to the particular characteristics of hospitals, these buildings are highly sensitive to environmental noise. However, they are usually located close or within urban agglomerations. Hence, hospitals are, in many cases, exposed to high levels of environmental noise. A study of one of the main hospitals in the Extremadura region (Spain) is presented here to allow a global assessment of the acoustic impact of outdoor sound sources. Both long- and short-term measurements were carried out, and a software model was developed. The measured values exceed the World Health Organisation reference value of 50 dBA for daytime and evening, and are even higher than the 55 dBA limit at which severe annoyance is generated. Taking into account the results obtained, the noise impact on this hospital is primarily influenced by three sound sources: road traffic, cooling towers of the hospital and the emergency helicopter. Their relative importance depends on the facade under consideration. It can therefore be concluded that the overall situation of the hospital needs to be improved. Thus, a series of solutions are proposed for a possible action plan based on interventions regarding the main sound sources and the location of the most sensitive areas to environmental noise.