Modeling of road traffic noise and estimated human exposure in Fulton County,Georgia, USA

Environmental noise is a major source of public complaints. Noise in the community causes physical and socio-economic effects and has been shown to be related to adverse health impacts. Noise, however, has not been actively researched in the United States compared with the European Union countries in recent years. In this research, we aimed at modeling road traffic noise and analyzing human exposure in Fulton County, Georgia, United States. We modeled road traffic noise levels using the United States Department of Transportation Federal Highway Administration Traffic Noise Model implemented in SoundPLAN®. After analyzing noise levels with raster, vector and façade maps, we estimated human exposure to high noise levels. Accurate digital elevation models and building heights were derived from Light Detection And Ranging survey datasets and building footprint boundaries. Traffic datasets were collected from the Georgia Department of Transportation and the Atlanta Regional Commission. Noise level simulation was performed with 62 computers in a distributed computing environment. Finally, the noise-exposed population was calculated using geographic information system techniques. Results show that 48% of the total county population [N = 870,166 residents] is potentially exposed to 55 dB(A) or higher noise levels during daytime. About 9% of the population is potentially exposed to 67 dB(A) or higher noises. At nighttime, 32% of the population is expected to be exposed to noise levels higher than 50 dB(A). This research shows that large-scale traffic noise estimation is possible with the help of various organizations. We believe that this research is a significant stepping stone for analyzing community health associated with noise exposures in the United States.     

Noise Impact and Improvement on Indoors Acoustic Comfort for the Building Adjacent to Heavy Traffic Road

A good acoustic environment is absolutely essential to maintaining a high level satisfaction and moral health among residents. Noise and other boresome sounds come from both in- door and outdoor sources. For the residential buildings adjacent to heavy traffic roads, outdoors traffic noise is the main source that affects indoor acoustic quality and health. Ventilation and outdoor noise prevention become a pair of contradictions for the residents in China nowadays for those buildings adjacent to heavy traffic roads. It is investigated that traffic noise emission is mainly con- stituted by the motors of trucks, buses and motorcycles as well as brake. In this paper, two methods of traffic noise reduction on the indoor sound environment and comfort are carried out to study and compare the residential buildings adjacent to heavy traffic roadway in a city. One is to install noise barriers on the two sides of the roadway, which consist of sound-proof glass and plas- tic materials. The effect of sound-insulation of this method is heavily dependent on the relative distance between the noise bar- rier and indoors. A reduction of sound with an average pressure level of 2–15dB is achieved on the places behind and under the noise barrier. However, for the equivalent of noise barrier height, the noise reduction effect is little. As for the places of higher than the noise barrier, the traffic noise will be even strengthened by 3–7dB. Noise increment can be seen at the points of distance farther than 15m and height more than noise barrier; the noise reduction effect is not satisfactory or even worsened. In addition, not every location is appropriate to install the noise barrier along the heavy traffic roads. The other method of noise reduction for the buildings adjacent to heavy traffic is to install the airproof and soundproof windows, which is the conversion from natural venti- lation to mechanical ventilation. A reduction of sound with an average pressure level of 5dB to 17dB can be achieved compared with common glass windows, if adopting sound proof glass win- dows. These two methods are helpful to isolate high frequency noise but not for low frequency noise. For those frequency noises, installing thick and cotton curtain and porous carpet can only decrease 2.4–4.5dB, which hardly contributes to indoor sound comfort, so further study is demanded to cut down traffic noise, especially to cut down the low frequency noise.     

Analysis of transportation carbon emissions and its potential for reduction in China

The transportation industry is an essential sector for carbon emissions mitigation.This paper firstly used the LMDI(Logarithmic Mean Divisia Index)decomposition method to establish factors decomposition model on China’s transportation carbon emission.Then,a quantitative analysis was performed to study the factors influencing China’s transportation carbon emissions from 1991 to 2008,which are identified as transportation energy efficiency,transportation structure and transportation development.The results showed that:(1)The impact of transportation development on transportation carbon emissions showed pulling function.Its contribution value to carbon emissions remained at high growth since 1991 and showed an exponential growth trend.(2)The impact of transportation structure on transportation carbon emissions showed promoting function in general,but its role in promoting carbon emissions decreased year by year.And with the continuous optimization of transportation structure,the promoting effect decreased gradually and showed the inversed"U"trend.(3)The impact of transportation energy efficiency on transportation carbon emissions showed a function of inhibition before pulling.In order to predict the potential of carbon emission reduction,three scenarios were set.Analysis of the scenarios showed that if greater intensity emission reduction measures are taken,the carbon emissions will reduce by 31.01 million tons by 2015 and by 48.81 million tons by 2020.     

Populations potentially exposed to traffic-related air pollution in seven world cities

Traffic-related air pollution (TRAP) likely exerts a large burden of disease globally, and in many places, traffic is increasing dramatically. The impact, however, of urban form on the portion of population potentially exposed to TRAP remains poorly understood. In this study, we estimate portions of population potentially exposed to TRAP across seven global cities of various urban forms. Data on population distributions and road networks were collected from the best available sources in each city and from remote sensing analysis. Using spatial mapping techniques, we first overlaid road buffers onto population data to estimate the portions of population potentially exposed for four plausible impact zones. Based on a most likely scenario with impacts from highways up to 300 meters and major roadways up to 50 meters, we identified that the portions of population potentially exposed for the seven cities ranged from 23 to 96%. High-income North American cities had the lowest potential exposure portions, while those in Europe had the highest. Second, we adjusted exposure zone concentration levels based on a literature suggested multiplier for each city using corresponding background concentrations. Though Beijing and Mexico City did not have the highest portion of population exposure, those in their exposure zones had the highest levels of exposure. For all seven cities, the portion of population potentially exposed was positively correlated with roadway density and, to a lesser extent, with population density. These analyses suggest that urban form may influence the portion of population exposed to TRAP and vehicle emissions and other factors may influence the exposure levels. Greater understanding of urban form and other factors influencing potential exposure to TRAP may help inform interventions that protect public health.     

Estimating human exposure to transport noise in central Dublin, Ireland

This paper reports on research conducted to determine estimates of the extent of environmental noise exposure from road transport on residents and workers in central Dublin, Ireland. The Harmonoise calculation method is used to calculate noise values for the study area while a Geographical Information System (GIS) is utilised as a platform upon which levels of noise exposure are estimated. Residential exposure is determined for L(den) and L(night) while worker exposure is determined for L(den). In order to analyse the potential of traffic management as a noise abatement measure, traffic was redirected from the main residential areas to alternative road links and the revised exposure levels were determined. The results show that the extent of noise exposure in Dublin is considerable, and in relative terms, it is worse for the night-time period. In addition, the results suggest also that traffic management measures have the potential to lead to significant reductions in the level of noise exposure provided that careful consideration is given to the impact of traffic flows on residential populations.     

Disturbance caused by various fluctuating single noises and combined community noises

Three experiments were conducted to investigate factors influencing the (rated) disturbance caused by various noises to subjects when they were reading: (a) comparison of disturbances from various noises at 70 dB(A) L_eq; (b) comparison of exposure-response relationships between road traffic, aircraft, and train noises; and (c) the effect of road traffic background noise on the total disturbance caused by combined noise (aircraft or train noise combined with road traffic noise). From the three experiments, the following conclusions were drawn: (1) High-level components such as peak level contributed to the disturbance, since the noise was more disturbing with the increase of peak level. (2) Although the general pattern of the exposure-response relationships for aircraft and train noises was similar, the disturbance due to road traffic noise increased with L_eq level more rapidly than for aircraft and train noise. Considering that the peak level of aircraft or train noise was always higher than that of road traffic noise at equal L_eq levels, the contribution of the high-level components to the disturbance appeared to be level-dependent. (3) The background noise level did not affect the total disturbance. Because the high-level components of combined noises were almost the same, this finding was consistent with conclusions drawn in (1) and (2).     

Annoyance due to aircraft noise has increased over the years—Results of the HYENA study

In the HYENA study (HYpertension and Exposure to Noise near Airports) noise annoyances due to aircraft and road traffic noise were assessed in subjects that lived in the vicinity of 6 major European airports using the 11-point ICBEN scale (International Commission on Biological Effects of Noise). A distinction was made between the annoyance during the day and during the night. L_den and L_night were considered as indicators of noise exposure. Pooled data analyses showed clear exposure–response relationships between the noise level and the noise annoyance for both exposures. The exposure–response curves for road noise were congruent with the EU standard curves used for predicting the number of highly noise annoyed subjects in European communities. Annoyance ratings due to aircraft noise, however, were higher than predicted by the EU standard curves. The data supports other findings suggesting that the people's attitude towards aircraft noise has changed over the years, and that the EU standard curve for aircraft noise should be modified.     

Transportation noise and exposed population of an urban area in the Republic of Korea

Using noise prediction models, we explored the transportation noise levels of Youngdeungpo-gu, an urbanized area of Seoul Metropolitan City in the Republic of Korea. In addition, we estimated the population exposed to transportation noise levels and determined how many people are vulnerable to noise levels that would cause serious annoyance and sleep disturbance. Compared with the World Health Organization [WHO] recommended levels, the daytime and nighttime transportation noise levels were still high enough to have the two psychosocial effects on people when considering the recommended levels of the World Health Organization (WHO; 55 decibels [dB[A]] and 40 dB[A] for daytime and nighttime, respectively). Particularly, nighttime transportation noise was discovered to be harmful to a wider area and more people than daytime noise. Approximately 91% of the Youngdeungpo-gu area experienced nighttime transportation noise levels exceeding those recommended by WHO. It was estimated that as much as 80% of the people in the study area were exposed to transportation noise levels >40 dB[A] during nighttime. Taking this into account, there is an urgent need to control and reduce transportation noise levels in Seoul, to protect residents against the potential ill health effects caused by urban transportation.     

Residential exposure to traffic noise and risk of incident atrial fibrillation: A cohort study

BackgroundStudies have found long-term exposure to traffic noise to be associated with higher risk for hypertension, ischemic heart disease and stroke. We aimed to investigate the novel hypothesis that traffic noise increases the risk of atrial fibrillation (A-fib).MethodsIn a population-based cohort of 57,053 people aged 50–64 years at enrolment in 1993–1997, we identified 2692 cases of first-ever hospital admission of A-fib from enrolment to end of follow-up in 2011 using a nationwide registry. The mean follow-up time was 14.7 years. Present and historical residential addresses were identified for all cohort members from 1987 to 2011. For all addresses, exposure to road traffic and railway noise was estimated using the Nordic prediction method and exposure to air pollution was estimated using a validated dispersion model. We used Cox proportional hazard model for the analyses with adjustment for lifestyle, socioeconomic position and air pollution.ResultsA 10 dB higher 5-year time-weighted mean exposure to road traffic noise was associated with a 6% higher risk of A-fib (incidence rate ratio (IRR): 1.06; 95% confidence interval (95% CI): 1.00–1.12) in models adjusted for factors related to lifestyle and socioeconomic position. The association followed a monotonic exposure–response relationship. In analyses with adjustment for air pollution, NO_x or NO₂, there were no statistically significant associations between exposure to road traffic noise and risk of A-fib; IRR: 1.04; (95% CI: 0.96–1.11) and IRR: 1.01; (95% CI: 0.94–1.09), respectively. Exposure to railway noise was not associated with A-fib.ConclusionExposure to residential road traffic noise may be associated with higher risk of A-fib, though associations were difficult to separate from exposure to air pollution.     

Road traffic noise, sensitivity, annoyance and self-reported health--a structural equation model exercise

The proposed effect of road traffic noise on hypertension and ischemic heart disease finds mixed empirical support. One problem with many studies is that the directions of the causal relationships are not identified. This is often the case when cross-sectional data and multivariate regression models are utilised. The aim of the study was to explore the relationship between road traffic noise and health. More specifically the relationships between noise complaints, noise sensitivity and subjectively reported hypertension and heart problems were investigated. 1842 respondents in Oslo, Norway were interviewed about their experience of the local environment and their subjective health complaints. The interviews were conducted as part of two surveys. Individual measures of air pollution (NO(2)) and noise (Lden) were calculated. The data were analysed using Structural Equation Models. Only sensitivity to noise is related to hypertension and chest pain. No relationships between noise exposure and health complaints were identified. Rather than noise being the causal agent leading to health problems, the results suggest that the noise-health relationships in these studies may be spurious. It is conceivable that individual vulnerability is reflected both in ill health and in being sensitive to noise. The benefit of including more contextual variables in a model of noise-health relationships is supported.     

Strategic environmental noise mapping: Methodological issues concerning the implementation of the EU Environmental Noise Directive and their policy implications

This paper explores methodological issues and policy implications concerning the implementation of the EU Environmental Noise Directive (END) across Member States. Methodologically, the paper focuses on two key thematic issues relevant to the Directive: (1) calculation methods and (2) mapping methods. For (1), the paper focuses, in particular, on how differing calculation methods influence noise prediction results as well as the value of the EU noise indicator L_den and its associated implications for comparability of noise data across EU states. With regard to (2), emphasis is placed on identifying the issues affecting strategic noise mapping, estimating population exposure, noise action planning and dissemination of noise mapping results to the general public. The implication of these issues for future environmental noise policy is also examined.     

Investigating the relationship between air pollution, health and social deprivation in Leeds, UK

This study examines the relationship between air pollution, social deprivation and health in the city of Leeds, UK under a baseline and three distance-based road user charging (RUC) scenarios set at 2 pence, 10 pence and 20 pence/km. Through application of a series of linked models of traffic, emission and pollutant dispersion, air quality was modelled in response to RUC scenarios. The pollutant modelled were NO(2), PM(10), CO, benzene and 1,3-butadiene, though results of NO(2) are used in this study. The RUC scenarios were compared with the 'base' scenario, all set for the year 2005. The RUC initiatives result in the differences in ambient concentrations of NO(2). The study correlates NO(2) concentrations with derived indices of social deprivation and health. The study concludes that positive but weak relationship exists between air quality and social deprivation, and indicates that deprived population groups are disproportionately exposed to higher NO(2) levels. The relationship between air quality and health status of the population is weak. There is a strong relationship between social deprivation and health status of the population. The study concludes that RUC scenarios result in reducing disparity between affluent and deprived populations.     

Traffic noise, work noise and cardiovascular risk factors: The Caerphilly and Speedwell collaborative heart disease studies

As part of two large heart surveys, associations between traffic noise exposure and cardiovascular risk factors were studied. The Caerphilly sample (small town, total sample) consisted of 2512 men aged 45 to 59 years and the Speedwell sample (suburb of a major city, random sample) of 2030 men of same age group. Both studies have a prospective design; cross-sectional results are presented here. Acoustic measurements were carried out in both areas. Among the possible risk factors for ischaemic heart disease studied were blood pressure, blood coagulation, blood lipids and other biochemical factors. Statistically significant noise effects were detected for systolic blood pressure, total cholesterol, HDL cholesterol, total triglycerides, blood viscosity, platelet count and glucose level, although not all of these were consistent with noise being a risk factor for heart disease. In a subsample, the additional influence of work noise as determined by noise dosimetry was studied in 255 men, taking the use of ear protection into account. The associations between traffic noise and risk factors were more pronounced in men who also were exposed to high work noise levels.     

Increased catecholamine levels in urine in subjects exposed to road traffic noise: the role of stress hormones in noise research

The nocturnal excretion of catecholamines in urine was studied in 30-45-year-old women whose bedroom and/or living room were facing streets of varying traffic volume. The traffic volume of the streets was used as an indicator of noise exposure; adrenaline and noradrenaline concentrations were assessed as indicators of the outcome of the physiological stress. Significant associations between traffic volume and noradrenaline concentrations in urine were found with regard to the exposure of the bedroom (not the living room), indicating a higher chronic physiological arousal in noise-exposed subjects as compared to less exposed. Subjective measures of disturbance due to traffic noise were positively correlated with the noradrenaline level. However, this was only found in subjects where closing the window could not reduce the perceived disturbance, which points to the effectiveness of individual coping mechanisms. Stress hormones are useful indicators to study associations, mechanisms, and interactions between noise, health outcomes, and effect modifiers in epidemiological noise research.     

Integrated health impact assessment of travel behaviour: Model exploration and application to a fuel price increase

Transportation policy measures often aim to change travel behaviour towards more efficient transport. While these policy measures do not necessarily target health, these could have an indirect health effect.We evaluate the health impact of a policy resulting in an increase of car fuel prices by 20% on active travel, outdoor air pollution and risk of road traffic injury. An integrated modelling chain is proposed to evaluate the health impact of this policy measure. An activity-based transport model estimated movements of people, providing whereabouts and travelled kilometres. An emission- and dispersion model provided air quality levels (elemental carbon) and a road safety model provided the number of fatal and non-fatal traffic victims. We used kilometres travelled while walking or cycling to estimate the time in active travel. Differences in health effects between the current and fuel price scenario were expressed in Disability Adjusted Life Years (DALY).A 20% fuel price increase leads to an overall gain of 1650 (1010–2330) DALY. Prevented deaths lead to a total of 1450 (890–2040) Years Life Gained (YLG), with better air quality accounting for 530 (180–880) YLG, fewer road traffic injuries for 750 (590–910) YLG and active travel for 170 (120–250) YLG. Concerning morbidity, mostly road safety led to 200 (120–290) fewer Years Lived with Disability (YLD), while air quality improvement only had a minor effect on cardiovascular hospital admissions. Air quality improvement and increased active travel mainly had an impact at older age, while traffic safety mainly affected younger and middle-aged people.This modelling approach illustrates the feasibility of a comprehensive health impact assessment of changes in travel behaviour. Our results suggest that more is needed than a policy rising car fuel prices by 20% to achieve substantial health gains. While the activity-based model gives an answer on what the effect of a proposed policy is, the focus on health may make policy integration more tangible. The model can therefore add to identifying win–win situations for both transport and health.     

Parameters of well-being and subjective health and their relationship with residential traffic noise exposure--a representative evaluation in Switzerland

In the present paper, the associations between residential traffic noise exposure from the noise sources--road, rail and aircraft--and self-reported indicators of health and well-being are investigated in a representative sample of the Swiss population. The study is based on record linkage of the Swiss GIS Noise Database (SonBase) and the Swiss Household Panel (SHP), a large panel survey with more than 10,000 respondents all over the country. A range of exposure-effect relationships of noise exposure and parameters of health and well-being such as self-reported health status, satisfaction with health, sleep disturbances, the intensity of the wish to move from the current residence as well as the awareness of "noise problems" at the place of living were investigated. Both unadjusted as well as models that controlled for age, sex, socioeconomic status, degree of urbanization at the place of residence, and personal living conditions were developed. A contribution of residential noise exposure as regards subjective estimates of health cannot been ruled out, but must be put into perspective as the effects of exposure measures were of rather small magnitude, especially compared to well-established determinants of health. Against the background of the explanatory power of classic health predictors, the present analyses allow one to gage the contribution of residential noise exposure on subjective health outcomes from a more general, integral point of view.     

Road-traffic noise and factors influencing noise annoyance in an urban population

Noise annoyance is influenced by sound-related factors: type of noise, noise level and frequency, and person-related factors—physiological, psychological, and social factors. Prior to implementation of the Directive 2002/49/EC of the European Parliament and of the Council in Serbia, there was a need for the first comprehensive study on noise annoyance in Serbian urban population. The aim of this study was to determine principal factors for high noise annoyance in an adult urban population and to assess their predictive value. A cross-sectional study was performed on 3097 adult residents of a downtown municipality in Belgrade (1217 men and 1880 women), aged 18–96 years. Equivalent noise levels [Leq (dBA)] were measured during day, evening and night in all streets of the municipality. Noise annoyance was estimated using self-reported annoyance scale. Noise annoyance showed strong correlation with noise levels, personal characteristics and some housing conditions. Dose–response relationship was found between the percentage of highly annoyed residents and Lden. Logistic regression model identified increased risk for a high level of noise annoyance with regard to: orientation of living room/bedroom toward the street (Odds Ratio = 2.60; 95% Confidence Interval = 2.04–3.31), duration of stay at apartment during the day [OR = 1.04, 95%CI = 1.02–1.06 (per hour)], noise sensitivity [OR = 1.04, 95%CI = 1.03–1.04 (per scale unit)], and nighttime road-traffic noise level [OR = 1.03, 95%CI = 1.02–1.04 (per decibel)].     

安徽省公路交通与经济发展水平测度及协调性研究

在中国经济发展“新常态”和“长江经济带”战略的宏观背景下，对公路交通与经济发展水平的测度及时空格局进行分析，能够为区域协调均衡发展提供较好的理论和实践指导。以安徽省16个地级市为实证，选择2005、2010、2015年3个时间节点，构建综合评价指标体系，运用熵值法、变异系数、协调指数等方法，分析公路交通和经济发展水平的时空格局和协调发展程度。结果表明：（1）安徽省经济发展水平变异系数较大，公路交通变异系数较小，二者区域内部差异明显；（2）安徽省公路交通发展水平逐年提升，在空间上呈现由“Z”型向“V”型转变继而转向“Z”型的分布格局；经济发展水平整体提升，局部波动，在空间上表征出典型的以合芜马为核心的“核心-边缘”分布特征；（3）公路交通与经济发展水平协调程度整体由协调向失调转变，在不同的时间序列上形成了不同的城市发展主导类型，以协同型和交通滞后型为主。 关键词： 公路交通；经济发展；时空格局；协调性；安徽省     

Exposure to long-term air pollution and road traffic noise in relation to cholesterol: A cross-sectional study

BackgroundExposure to traffic noise and air pollution have both been associated with cardiovascular disease, though the mechanisms behind are not yet clear.ObjectivesWe aimed to investigate whether the two exposures were associated with levels of cholesterol in a cross-sectional design.MethodsIn 1993–1997, 39,863 participants aged 50–64 year and living in the Greater Copenhagen area were enrolled in a population-based cohort study. For each participant, non-fasting total cholesterol was determined in whole blood samples on the day of enrolment. Residential addresses 5-years preceding enrolment were identified in a national register and road traffic noise (L_den) were modeled for all addresses. For air pollution, nitrogen dioxide (NO₂) was modeled at all addresses using a dispersion model and PM_2.5 was modeled at all enrolment addresses using a land-use regression model. Analyses were done using linear regression with adjustment for potential confounders as well as mutual adjustment for the three exposures.ResultsBaseline residential exposure to the interquartile range of road traffic noise, NO₂ and PM_2.5 was associated with a 0.58 mg/dl (95% confidence interval: − 0.09; 1.25), a 0.68 mg/dl (0.22; 1.16) and a 0.78 mg/dl (0.22; 1.34) higher level of total cholesterol in single pollutant models, respectively. In two pollutant models with adjustment for noise in air pollution models and vice versa, the association between air pollution and cholesterol remained for both air pollution variables (NO₂: 0.72 (0.11; 1.34); PM_2.5: 0.70 (0.12; 1.28) mg/dl), whereas there was no association for noise (− 0.08 mg/dl). In three-pollutant models (NO₂, PM_2.5 and road traffic noise), estimates for NO₂ and PM_2.5 were slightly diminished (NO₂: 0.58 (− 0.05; 1.22); PM_2.5: 0.57 (− 0.02; 1.17) mg/dl).ConclusionsAir pollution and possibly also road traffic noise may be associated with slightly higher levels of cholesterol, though associations for the two exposures were difficult to separate.     

Comparative study of the effects of infrasound and low-frequency sound with those of audible sound on sleep

In order to compare the effects of infrasound and low-frequency sound on sleep with those of audible sound, healthy students were exposed to two kinds of sound, (a) infrasound and low-frequency sound (10, 20, 40, and 60 Hz), and (b) synthesized traffic noise with peak sound pressure level in low-frequency range (sound composed of low and audible frequency), throughout their sleep with the recording of the students' EEG. The effects were evaluated by the “reaction rate”. Concerning sound (a), the sound pressure level which causes the reactions of over 50% for the first time was used as the threshold sound pressure level signifying the occurrence of sleep disturbance. The threshold sound pressure levels of 10 and 20 Hz could not be evaluated. The threshold sound pressure levels of 40 and 63 Hz were 95 and 90 dB, respectively. With both sounds, the reaction rate was the highest in sleep stage 1 and the lowest in sleep stage 3+4. The pattern of sleep was little affected by sound (a). On the other hand, it was considerably affected by sound (b). These results suggest that audible sound has more harmful effects on sleep, compared with infrasound and low-frequency sound.