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.     

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 fa?ade 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.     

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.     

Associations between maternal exposure to air pollution and traffic noise and newborn's size at birth: A cohort study

BackgroundMaternal exposure to air pollution and traffic noise has been suggested to impair fetal growth, but studies have reported inconsistent findings.ObjectiveTo investigate associations between residential air pollution and traffic noise during pregnancy and newborn's size at birth.MethodsFrom a national birth cohort we identified 75,166 live-born singletons born at term with information on the children's size at birth. Residential address history from conception until birth was collected and air pollution (NO₂ and NO_x) and road traffic noise was modeled at all addresses. Associations between exposures and indicators of newborn's size at birth: birth weight, placental weight and head and abdominal circumference were analyzed by linear and logistic regression, and adjusted for potential confounders.ResultsIn mutually adjusted models we found a 10 μg/m³ higher time-weighted mean exposure to NO₂ during pregnancy to be associated with a 0.35 mm smaller head circumference (95% confidence interval (CI): 95% CI: − 0.57; − 0.12); a 0.50 mm smaller abdominal circumference (95% CI: − 0.80; − 0.20) and a 5.02 g higher placental weight (95% CI: 2.93; 7.11). No associations were found between air pollution and birth weight. Exposure to residential road traffic noise was weakly associated with reduced head circumference, whereas none of the other newborn's size indicators were associated with noise, neither before nor after adjustment for air pollution.ConclusionsThis study indicates that air pollution may result in a small reduction in offspring's birth head and abdominal circumference, but not birth weight, whereas traffic noise seems not to affect newborn's size at birth.     

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.     

Lower placental telomere length may be attributed to maternal residential traffic exposure; a twin study

BackgroundHigh variation in telomere length between individuals is already present before birth and is as wide among newborns as in adults. Environmental exposures likely have an impact on this observation, but remain largely unidentified. We hypothesize that placental telomere length in twins is associated with residential traffic exposure, an important environmental source of free radicals that might accelerate aging. Next, we intend to unravel the nature-nurture contribution to placental telomere length by estimating the heritability of placental telomere length.MethodsWe measured the telomere length in placental tissues of 211 twins in the East Flanders Prospective Twin Survey. Maternal traffic exposure was determined using a geographic information system. Additionally, we estimated the relative importance of genetic and environmental sources of variance.ResultsIn this twin study, a variation in telomere length in the placental tissue was mainly determined by the common environment. Maternal residential proximity to a major road was associated with placental telomere length: a doubling in the distance to the nearest major road was associated with a 5.32% (95% CI: 1.90 to 8.86%; p = 0.003) longer placental telomere length at birth. In addition, an interquartile increase (22%) in maternal residential surrounding greenness (5 km buffer) was associated with an increase of 3.62% (95% CI: 0.20 to 7.15%; p = 0.04) in placental telomere length.ConclusionsIn conclusion, we showed that maternal residential proximity to traffic and lower residential surrounding greenness is associated with shorter placental telomere length at birth. This may explain a significant proportion of air pollution-related adverse health outcomes starting from early life, since shortened telomeres accelerate the progression of many diseases.     

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).     

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.     

Exposure to hydrocarbon concentrations while commuting or exercising in Dublin

In Ireland, several studies have monitored the air pollution due to traffic in both urban and rural environments. However, few studies have attempted to quantify the relative exposure to traffic derived HC pollutants between different modes of commuter transport. In this study, the difference in pollution exposure between bus and cycling commuters on a route in Dublin was compared by sampling for five vehicle related hydrocarbons: benzene, 1,3-butadiene, acetylene, ethane and ethylene. Samples were collected during both morning and afternoon rush hour periods using a fixed speed pump to gain representative concentrations across the whole journey. Journey times were also measured, as were typical breathing rates in order to calculate the overall dose of pollutant inhaled on the journey. Results clearly picked up significantly higher pollutant concentrations in the bus compared to cycling and also revealed elevated concentrations on the congested side of the road compared to the side moving against the traffic. However, when respiration rates and travel times were taken into account to reveal the mass of pollutants inhaled over the course of a journey, the pattern was reversed, showing slightly enhanced levels of hydrocarbons for the cyclist compared to the bus passenger. In addition, the concentrations of these compounds (excluding ethane), were ascertained at playing pitches in the vicinity of a heavily trafficked suburban motorway and in Dublin city centre. Although the concentrations were relatively low at all sites, when breathing rates were taken into consideration, the average inhaled weights of pollutants were, on occasion, higher than those average values observed for both bus and bicycle commuters.     

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.     

Residential proximity to traffic and female pubertal development

BackgroundTraffic-related air pollution (TRAP) has been linked with several adverse health outcomes, including preterm birth and low birth weight, which are both related to onset of puberty. No studies to date have investigated the association between TRAP and altered pubertal timing.ObjectiveDetermine the association between residential proximity to traffic, as a marker of long-term TRAP exposure, and age at pubertal onset in a longitudinal study of girls.MethodsWe analyzed data for 437 girls at the CYGNET study site of the Breast Cancer and Environment Research Program. TRAP exposure was assessed using several measures of residential proximity to traffic based on address at study entry. Using accelerated failure time models, we calculated time ratios (TRs) and their corresponding 95% confidence intervals (CIs) for specified traffic metrics and pubertal onset, defined as stage 2 or higher for breast or pubic hair development (respectively, B2 + and PH2 +). Models were adjusted for race/ethnicity, household income, and cotinine levels.ResultsAt baseline, 71% of girls lived within 150 m of a major road. The median age of onset was 10.3 years for B2 + and 10.9 years for PH2 +. Living within 150 m downwind of a major road was associated with earlier onset of PH2 + (TR 0.96, 95% CI 0.93, 0.99). Girls in the highest quintile of either distance-weighted traffic density, annual average daily traffic, and/or traffic density also reached PH2 + earlier than girls in the lowest quintiles.ConclusionsIn this first study to assess the association between residential proximity to traffic and pubertal onset we found girls with higher exposure reached one pubertal milestone several months earlier than low exposed girls, even after consideration of likely confounders. Results should be expanded in larger epidemiological studies, and with measured levels of air pollutants.     

Reduced exposure to air pollution on the boardwalk in Dublin, Ireland. Measurement and prediction

This paper outlines an air pollution study carried out on Dublin city's recently completed boardwalk along the side of and overhanging the River Liffey. Air quality samples were taken along the length of the boardwalk to investigate whether pedestrians using the boardwalk would have a lower air pollution exposure than those using the adjoining footpath along the road. The results of the study show significant reductions in pedestrian exposure to both traffic derived particulates and hydrocarbons along the boardwalk as opposed to the footpath. Computational fluid dynamics was also used to model the outcome of these field measurements and shows the importance of the boundary wall between the footpath and boardwalk in reducing air pollution exposure for the pedestrian, the results of which are also presented herein.     

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.     

Urinary methyl tert-butyl ether and benzene as biomarkers of exposure to urban traffic

Methyl tert-butyl ether (MTBE) and benzene are added to gasoline to improve the combustion process and are found in the urban environment as a consequence of vehicular traffic. Herein we evaluate urinary MTBE (MTBE-U) and benzene (BEN-U) as biomarkers of exposure to urban traffic. Milan urban policemen (130 total) were investigated in May, July, October, and December for a total of 171 work shifts. Personal exposure to airborne benzene and carbon monoxide (CO), and atmospheric data, were measured during the work shift, while personal characteristics were collected by a questionnaire. A time/activity diary was completed by each subject during the work shift. Spot urine samples were obtained for the determination of MTBE-U and BEN-U. Median personal exposure to CO and airborne benzene were 3.3 mg/m(3) and 9.6 μg/m(3), respectively; median urinary levels in end-of-shift (ES) samples were 147 ng/L (MTBE-U) and 207 ng/L (BEN-U). The time spent on traffic duty at crossing was about 40% of work time. Multiple linear regression models, taking into account within-subject correlations, were applied to investigate the role of urban pollution, atmospheric conditions, job variables and personal characteristics on the level of biomarkers. MTBE-U was influenced by the month of sampling and positively correlated to the time spent in traffic guarding, CO exposure and atmospheric pressure, while negatively correlated to wind speed (R(2) for total model 0.63, P<0.001). BEN-U was influenced by the month and smoking habit, and positively correlated to urinary creatinine; moreover, an interaction between CO and smoking was found (R(2)=0.62, P<0.001). These results suggest that MTBE-U is a reliable marker for assessing urban traffic exposure, while BEN-U is determined mainly by personal characteristics.     

Car free cities: Pathway to healthy urban living

BackgroundMany cities across the world are beginning to shift their mobility solution away from the private cars and towards more environmentally friendly and citizen-focused means. Hamburg, Oslo, Helsinki, and Madrid have recently announced their plans to become (partly) private car free cities. Other cities like Paris, Milan, Chengdu, Masdar, Dublin, Brussels, Copenhagen, Bogota, and Hyderabad have measures that aim at reducing motorized traffic including implementing car free days, investing in cycling infrastructure and pedestrianization, restricting parking spaces and considerable increases in public transport provision. Such plans and measures are particularly implemented with the declared aim of reducing greenhouse gas emissions. These reductions are also likely to benefit public health.AimsWe aimed to describe the plans for private car free cities and its likely effects on public health.MethodsWe reviewed the grey and scientific literature on plans for private car free cities, restricted car use, related exposures and health.ResultsAn increasing number of cities are planning to become (partly) private car free. They mainly focus on the reduction of private car use in city centers. The likely effects of such policies are significant reductions in traffic-related air pollution, noise, and temperature in city centers. For example, up to a 40% reduction in NO₂ levels has been reported on car free days. These reductions are likely to lead to a reduction in premature mortality and morbidity. Furthermore the reduction in the number of cars, and therefore a reduction in the need for parking places and road space, provides opportunities to increase green space and green networks in cities, which in turn can lead to many beneficial health effects. All these measures are likely to lead to higher levels of active mobility and physical activity which may improve public health the most and also provide more opportunities for people to interact with each other in public space. Furthermore, such initiatives, if undertaken at a sufficiently large scale can result in positive distal effects and climate change mitigation through CO₂ reductions. The potential negative effects which may arise due to motorized traffic detouring around car free zone into their destinations also need further evaluation and the areas in which car free zones are introduced need to be given sufficient attention so as not to become an additional way to exacerbate socioeconomic divides. The extent and magnitude of all the above effects is still unclear and needs further research, including full chain health impact assessment modeling to quantify the potential health benefits of such schemes, and exposure and epidemiological studies to measure any changes when such interventions take place.ConclusionsThe introduction of private car free cities is likely to have direct and indirect health benefits, but the exact magnitude and potential conflicting effects are as yet unclear. This paper has overviewed the expected health impacts, which can be useful to underpin policies to reduce car use in cities.     

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.     

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.     

Testing of the European Union exposure-response relationships and annoyance equivalents model for annoyance due to transportation noises: The need of revised exposure-response relationships and annoyance equivalents model

An in situ survey was performed in 8 French cities in 2012 to study the annoyance due to combined transportation noises. As the European Commission recommends to use the exposure–response relationships suggested by Miedema and Oudshoorn [Environmental Health Perspective, 2001] to predict annoyance due to single transportation noise, these exposure–response relationships were tested using the annoyance due to each transportation noise measured during the French survey. These relationships only enabled a good prediction in terms of the percentages of people highly annoyed by road traffic noise. For the percentages of people annoyed and a little annoyed by road traffic noise, the quality of prediction is weak. For aircraft and railway noises, prediction of annoyance is not satisfactory either. As a consequence, the annoyance equivalents model of Miedema [The Journal of the Acoustical Society of America, 2004], based on these exposure-response relationships did not enable a good prediction of annoyance due to combined transportation noises. Local exposure-response relationships were derived, following the whole computation suggested by Miedema and Oudshoorn [Environmental Health Perspective, 2001]. They led to a better calculation of annoyance due to each transportation noise in the French cities. A new version of the annoyance equivalents model was proposed using these new exposure-response relationships. This model enabled a better prediction of the total annoyance due to the combined transportation noises. These results encourage therefore to improve the annoyance prediction for noise in isolation with local or revised exposure-response relationships, which will also contribute to improve annoyance modeling for combined noises. With this aim in mind, a methodology is proposed to consider noise sensitivity in exposure-response relationships and in the annoyance equivalents model. The results showed that taking into account such variable did not enable to enhance both exposure-response relationships and the annoyance equivalents model.     

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.     

Levels and major sources of PM2.5 and PM10 in Bangkok Metropolitan Region

This research was the first long-term attempt to concurrently measure and identify major sources of both PM(10) and PM(2.5) in Bangkok Metropolitan Region (BMR). Ambient PM(10) and PM(2.5) were evaluated at four monitoring stations and analyzed for elemental compositions, water-soluble ions, and total carbon during February 2002-January 2003. Fifteen chemical elements, four water-soluble ions, and total carbon were analyzed to assist major source identification by a receptor model approach, known as chemical mass balance. PM(10) and PM(2.5) were significantly different (p<0.05) at all sites and 24 h averages were high at traffic location while two separated residential sites were similar. Seasonal difference of PM(10) and PM(2.5) concentrations was distinct between dry and wet seasons. Major source of PM(10) at the traffic site indicated that automobile emissions and biomass burning-related sources contributed approximately 33% each. Automobiles contributed approximately 39 and 22% of PM(10) mass at two residential sites while biomass burning contributed about 36 and 28%. PM(10) from re-suspended soil and cooking sources accounted for 10 to 15% at a residential site. Major sources of PM(2.5) at traffic site were automobile and biomass burning, contributing approximately 32 and 26%, respectively. Biomass burning was the major source of PM(2.5) mass concentrations at residential sites. Meat cooking also accounted for 31% of PM(2.5) mass at a low impact site. Automobile, biomass burning, and road dust were less significant, contributed 10, 6, and 5%, respectively. Major sources identification at some location had difficulty to achieve performance criteria due to limited source profiles. Improved in characterize other sources profiles will help local authority to better air quality.