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.     

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.     

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.     

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.     

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.     

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.     

Spatial variations in the associations of term birth weight with ambient air pollution in Georgia,USA

Birth weight is an important indicator of overall infant health and a strong predictor of infant morbidity and mortality, and low birth weight (LBW) is a leading cause of infant mortality in the United States. Numerous studies have examined the associations of birth weight with ambient air pollution, but the results were inconsistent. In this study, a spatial statistical technique, geographically weighted regression (GWR) is applied to explore the spatial variations in the associations of birth weight with concentrations of ozone (O₃) and fine particulate matter (PM_2.5) in the State of Georgia, USA adjusted for gestational age, parity, and six other socioeconomic, behavioral, and land use factors. The results show considerable spatial variations in the associations of birth weight with both pollutants. Significant positive, non-significant, and significant negative relationships between birth weight and concentrations of each air pollutant are all found in different parts of the study area, and the different types of the relationships are affected by the socioeconomic and urban characteristics of the communities where the births are located. The significant negative relationships between birth weight and O₃ indicate that O₃ is a significant risk factor of LBW and these associations are primarily located in less-urbanized communities. On the other hand, PM_2.5 is a significant risk factor of LBW in the more-urbanized communities with higher family income and education attainment. These findings suggest that environmental and health policies should be adjusted to address the different effects of air pollutants on birth outcomes across different types of communities to more effectively and efficiently improve birth outcomes.     

Weekend–weekday aerosols and geographic variability in cloud-to-ground lightning for the urban region of Atlanta, Georgia, USA

We characterized the differences in warm-season weekday and weekend aerosol conditions and cloud-to-ground (CG) flashes (1995–2008) for an 80,000 square kilometer region around Atlanta, Georgia, a city of 5.5 million in the humid subtropics of the southeastern United States. An integration of distance-based multivariate techniques (hierarchical agglomerative clustering, multiresponse permutation procedures, fuzzy kappa statistics, and Mantel tests) indicated a greater concentration of CG flash activity within a 100 km radius around Atlanta under weekday aerosol concentrations. On weekends, these effects contracted toward the city. This minimized any weekly anthropogenic cycle over the more densely populated urban center even though this location had a higher flash density, a higher percentage of days with flashes, and stronger peak currents over the course of a week compared to the surrounding region. The sharper contrasts in weekday and weekend lightning regime developed outside the perimeter of the city over nonurban land uses. Here, lightning on weekend and weekdays differed more in its density, frequency, polarity, and peak current. Across the full extent of the study region, weekday peak currents were stronger and flash days more frequent, suggesting that weekly CG lightning signals have a regional component not tied to a single city source. We integrate these findings in a conceptual model that illustrates the dependency of weekly anthropogenic weather signals on spatial and temporal extent.     

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.     

Recreational swimmers' exposure to Vibrio vulnificus and Vibrio parahaemolyticus in the Chesapeake Bay,Maryland, USA

Vibrio vulnificus and Vibrio parahaemolyticus are ubiquitous in the marine–estuarine environment, but the magnitude of human non-ingestion exposure to these waterborne pathogens is largely unknown. We evaluated the magnitude of dermal exposure to V. vulnificus and V. parahaemolyticus among swimmers recreating in Vibrio-populated waters by conducting swim studies at four swimming locations in the Chesapeake Bay in 2009 and 2011. Volunteers (n = 31) swam for set time periods, and surface water (n = 25) and handwash (n = 250) samples were collected. Samples were analyzed for Vibrio concentrations using quantitative PCR. Linear and logistic regressions were used to evaluate factors associated with recreational exposures. Mean surface water V. vulnificus and V. parahaemolyticus concentrations were 1128 CFU mL^− 1 (95% confidence interval (CI): 665.6, 1591.4) and 18 CFU mL^− 1 (95% CI: 9.8, 26.1), respectively, across all sampling locations. Mean Vibrio concentrations in handwash samples (V. vulnificus, 180 CFU cm^− 2 (95% CI: 136.6, 222.5); V. parahaemolyticus, 3 CFU cm^− 2 (95% CI: 2.4, 3.7)) were significantly associated with Vibrio concentrations in surface water (V. vulnificus, p < 0.01; V. parahaemolyticus, p < 0.01), but not with salinity or temperature (V. vulnificus, p = 0.52, p = 0.17; V. parahaemolyticus, p = 0.82, p = 0.06). Handwashing reduced V. vulnificus and V. parahaemolyticus on subjects' hands by approximately one log (93.9%, 89.4%, respectively). It can be concluded that when Chesapeake Bay surface waters are characterized by elevated concentrations of Vibrio, swimmers and individuals working in those waters could experience significant dermal exposures to V. vulnificus and V. parahaemolyticus, increasing their risk of infection.     

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.     

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.     

Chlorinated paraffins in indoor air and dust: concentrations, congener patterns, and human exposure

Chlorinated paraffins (CPs) are large production volume chemicals used in a wide variety of commercial applications. They are ubiquitous in the environment and humans. Human exposure via the indoor environment has, however, been barely investigated. In the present study 44 indoor air and six dust samples from apartments in Stockholm, Sweden, were analyzed for CPs, and indoor air concentrations are reported for the first time. The sumCP concentration (short chain CPs (SCCPs) and medium chain CPs (MCCPs)) in air ranged from <5-210 ng m(-3) as quantified by gas chromatography coupled to electron ionization tandem mass spectrometry (GC/EI-MS/MS). Congener group patterns were studied using GC with electron capture negative ionization MS (GC/ECNI-MS). The air samples were dominated by the more volatile SCCPs compared to MCCPs. SumCPs were quantified by GC/EI-MS/MS in the dust samples at low μg g(-1) levels, with a chromatographic pattern suggesting the prevalence of longer chain CPs compared to air. The median exposure to sumCPs via the indoor environment was estimated to be ~1 μg day(-1) for both adults and toddlers. Adult exposure was dominated by inhalation, while dust ingestion was suggested to be more important for toddlers. Comparing these results to literature data on dietary intake indicates that human exposure to CPs from the indoor environment is not negligible.     

Recent advances in the study of human performance in noise

Recent research associated with three major types of effect of noise on human performance is discussed: 1) Loud noise influences information processing by inducing verbal strategies which may persist after the noise has been turned off, and if verbal strategies are already in use, noise encourages their more fervent adoption. 2) Loud noise also elevates the person's state of arousal. Its effects are qualitatively similar to the effects of fatigue due to mental work and, in some ways, to the effects of wakefulness over the day. 3) Irrelevant speech interferes with reading and memory. The effects appear to be independent of intensity and, for memory at least, independent of the meaning of the speech. Speech appears to have privileged access to (and hence opportunities to disrupt) high-level processing mechanisms essential to efficiency in children's reading and to performance in the modern office environment. Arising from an analysis of these findings, a number of emerging research issues are discussed.     

Air flow and concentration fields at urban road intersections for improved understanding of personal exposure

This paper reviews the state of knowledge on modelling air flow and concentration fields at road intersections. The first part covers the available literature from the past two decades on experimental (both field and wind tunnel) and modelling activities in order to provide insight into the physical basis of flow behaviour at a typical cross-street intersection. This is followed by a review of associated investigations of the impact of traffic-generated localised turbulence on the concentration fields due to emissions from vehicles. There is a discussion on the role of adequate characterisation of vehicle-induced turbulence in making predictions using hybrid models, combining the merits of conventional approaches with information obtained from more detailed modelling. This concludes that, despite advancements in computational techniques, there are crucial knowledge gaps affecting the parameterisations used in current models for individual exposure. This is specifically relevant to the growing impetus on walking and cycling activities on urban roads in the context of current drives for sustainable transport and healthy living. Due to inherently longer travel times involved during such trips, compared to automotive transport, pedestrians and cyclists are subjected to higher levels of exposure to emissions. Current modelling tools seem to under-predict this exposure because of limitations in their design and in the empirical parameters employed.     

The use of ambient air quality modeling to estimate individual and population exposure for human health research: a case study of ozone in the Northern Georgia Region of the United States

Ambient monitors are commonly used to estimate exposure for epidemiological studies, and air quality modeling is infrequently applied. However air quality modeling systems have the potential to alleviate some, although not all, of the limitations of monitoring networks. To investigate this application, exposure estimates were generated for a case study high ozone episode in the Northern Georgia Region of the United States based on measurements and concentration estimates from an air quality modeling system. Hourly estimates for 2268 4-km by 4-km gridcells were generated in a domain that includes only eight ozone monitors. Individual and population-based ozone exposures were estimated using multiple approaches, including area-weighted average of modeled estimates, nearest monitor, and spatial interpolation by inverse distance weighting and kriging. Results based on concentration fields from the air quality modeling system revealed spatial heterogeneity that was obscured by approaches based on the monitoring network. With some techniques, such as spatial interpolation, monitoring data alone was insufficient to estimate exposure for certain areas, especially for rural populations. For locations far from ozone monitors, the estimates from the nearest monitor approach tended to overestimate exposure, compared to modeled estimates. Counties in which one or more monitors were present had statistically higher population density and modeled ozone estimates than did counties without monitors (p-value <0.05). This work demonstrates the use of air quality modeling to generate higher spatial and temporal resolution exposure estimates, and compares the advantages of this approach to traditional methods that use monitoring data alone. The air quality modeling method faces its own limitations, such as the need to thoroughly evaluate concentration estimates and the use of ambient levels rather than personal exposure.     

Coupling fishery dynamics,human health and social learning in a model of fish-borne pollution exposure

Pollution-induced illnesses are caused by toxicants that result from human activity and are often entirely preventable. However, where industrial priorities have undermined responsible governance, exposed populations must reduce their exposure by resorting to voluntary protective measures and demanding emissions abatement. This paper presents a coupled human–environment system model that represents the effects of water pollution on the health and livelihood of a fishing community. The model is motivated by an incident from 1949 to 1968 in Minamata, Japan, where methylmercury effluent from a local factory poisoned fish populations and humans who ate them. We model the critical role of risk perception in driving both social learning and the protective feedbacks against pollution exposure. These feedbacks are undermined in the presence of social misperceptions such as stigmatization of the injured. Through numerical simulation and scenario analysis, we compare our model results with historical datasets from Minamata, and find that the conditions for an ongoing pollution epidemic are highly unlikely without social misperception. We also find trade-offs between human health outcomes, the viability of the polluting industry and the survival of the fishery. We conclude that an understanding of human–environment interactions and misperception effects is highly relevant to the resolution of contemporary pollution problems, and merits further study.     

Use of pooled samples to assess human exposure to parabens,benzophenone-3 and triclosan in Queensland,Australia

Parabens, benzophenone-3 and triclosan are common ingredients used as preservatives, ultraviolet radiation filters and antimicrobial agents, respectively. Human exposure occurs through consumption of processed food and use of cosmetics and consumer products. The aim of this study was to provide a preliminary characterisation of exposure to selected personal care product chemicals in the general Australian population. De-identified urine specimens stratified by age and sex were obtained from a community-based pathology laboratory and pooled (n = 24 pools of 100). Concentrations of free and total (sum of free plus conjugated) species of methyl, ethyl, propyl and butyl paraben, benzophenone-3 and triclosan were quantified using isotope dilution tandem mass spectrometry; with geometric means 232, 33.5, 60.6, 4.32, 61.5 and 87.7 ng/mL, respectively. Age was inversely associated with paraben concentration, and females had concentrations approximately two times higher than males. Total paraben and benzophenone-3 concentrations are significantly higher than reported worldwide, and the average triclosan concentration was more than one order of magnitude higher than in many other populations. This study provides the first data on exposure of the general Australian population to a range of common personal care product chemical ingredients, which appears to be prevalent and warrants further investigation.     

Environmental impact and human exposure to PCBs in Guiyu, an electronic waste recycling site in China

PCB levels in fish (collected from local rivers), atmosphere and human milk samples have been studied to determine the exposure levels of PCBs for local residents and e-waste workers in Guiyu, a major electronic waste scrapping center in China. The source appointment and correlation analyses showed that homologue composition of PCBs in 7 species of fish were consistent and similar to commercial PCBs Aroclor 1248. PCB levels in air surrounding the open burning site were significantly higher than those in residential area. Inhalation exposure contributed 27% and 93% to the total body loadings (the sum of dietary and inhalation exposure) of the local residents, and e-waste workers engaged in open burning respectively. Total PCB concentrations in human milk ranged from N.D. to 57.6 ng/g lipid, with an average of 9.50 ng/g lipid. The present results indicated that commercial PCBs derived from e-waste recycling are major sources of PCBs accumulating in different environmental media, leading to the accumulation of high chlorinated biphenyls in human beings.