Traffic Pollutant Concentrations Research Articles

Short-term exposure to traffic-related air pollution and STEMI events: Insights into STEMI onset and related cardiac impairment

AimsEvidence on the impacts of traffic-related air pollution (TRAP) on ST-segment elevation myocardial infarction (STEMI) events is limited. We aimed to assess the acute effects of TRAP exposure on the clinical onset of STEMI and related cardiac impairments. Methods and resultsWe recruited patients who were admitted for STEMI and underwent primary percutaneous coronary intervention at Peking University Third Hospital between 2014 and 2020. Indicators relevant to cardiac impairments were measured. Concomitantly, hourly concentrations of traffic pollutants were monitored throughout the study period, including fine particulate matter, black carbon (BC), particles in size ranges of 5–560 nm, oxides of nitrogen (NOX), nitrogen dioxide, and carbon monoxide. The mean (SD) age of participants was 62.4 (12.5) years. Daily average (range) concentrations of ambient BC and NOX were 3.9 (0.1–25.0) μg/m3 and 90.8 (16.6–371.7) μg/m3. Significant increases in STEMI risks of 5.9% (95% CI: 0.1, 12.0) to 21.9% (95% CI: 6.0, 40.2) were associated with interquartile range increases in exposure to TRAP within a few hours. These changes were accompanied by significant elevations in cardiac troponin T levels of 6.9% (95% CI: 0.2, 14.1) to 41.7% (95% CI: 21.2, 65.6), as well as reductions in left ventricular ejection fraction of 1.5% (95% CI: 0.1, 2.9) to 3.7% (95% CI: 0.8, 6.4). Furthermore, the associations were attenuated in participants living in areas with higher residential greenness levels. ConclusionsOur findings extend current understanding that short-term exposure to higher levels of traffic pollution was associated with increased STEMI risks and exacerbated cardiac impairments, and provide evidence on traffic pollution control priority for protecting vulnerable populations who are at greater risks of cardiovascular events.

Concentration of air pollutants as toxic matter in urban and rural areas of Ahvaz

The aim of this study is to survey the concentrations of air pollutants in rural and urban areas in Ahvaz city during two seasons. We used ANOVA to determine the differences between the areas. Paired t-test was used to compare the concentrations of the air pollutants in cold season and hot season. The concentration of the air pollutants in cold season was higher than warm season except for O3. Mobile vehicles represent the major source of air pollution in many areas, and the concentrations of traffic pollutants are greater near urban areas. The trend of changes in PM concentration in cold and warm seasons depends on dust storms occurrence.

Influence of roadside hedgerows on air quality in urban street canyons

Understanding pollutant dispersion in the urban environment is an important aspect of providing solutions to reduce personal exposure to vehicle emissions. To this end, the dispersion of gaseous traffic pollutants in urban street canyons with roadside hedges was investigated. The study was performed in an atmospheric boundary layer wind tunnel using a reduced-scale (M = 1:150) canyon model with a street-width-to-building-height ratio of W/H = 2 and a street-length-to-building-height ratio of L/H = 10. Various hedge configurations of differing height, permeability and longitudinal segmentation (continuous over street length L or discontinuous with clearings) were investigated. Two arrangements were examined: (i) two eccentric hedgerows sidewise of the main traffic lanes and (ii) one central hedgerow between the main traffic lanes. In addition, selected configurations of low boundary walls, i.e. solid barriers, were examined. For a perpendicular approach wind and in the presence of continuous hedgerows, improvements in air quality in the center area of the street canyon were found in comparison to the hedge-free reference scenario. The pollutant reductions were greater for the central hedge arrangements than for the sidewise arrangements. Area-averaged reductions between 46 and 61% were observed at pedestrian head height level on the leeward side in front of the building for the centrally arranged hedges and between 18 and 39% for the two hedges arranged sidewise. Corresponding area-averaged reductions ranging from 39 to 55% and from 1 to 20% were found at the bottom of the building facades on the leeward side. Improvements were also found in the areas at the lateral canyon ends next to the crossings for the central hedge arrangements. For the sidewise arrangements, increases in traffic pollutants were generally observed. However, since the concentrations in the end areas were considerably lower compared to those in the center area, an overall improvement remained for the street canyon. The configuration of a sidewise arranged discontinuous hedgerow resulted in general in area-averaged increases in concentrations in the range of 3–19%. For a parallel approach wind, reduced concentrations of up to 30% at the facades and up to 60% at pedestrian level were measured with a sidewise continuous hedgerow arrangement. It is concluded that continuous hedgerows can effectively be employed to control concentrations of traffic pollutants in urban street canyons. They can advantageously affect the air quality at street level and can be a significant remedy to the pedestrians’ and residents’ exposure in the most polluted center area of a street canyon.

Impact of trees on pollutant dispersion in street canyons: A numerical study of the annual average effects in Antwerp, Belgium

Effects of vegetation on pollutant dispersion receive increased attention in attempts to reduce air pollutant concentration levels in the urban environment. In this study, we examine the influence of vegetation on the concentrations of traffic pollutants in urban street canyons using numerical simulations with the CFD code OpenFOAM. This CFD approach is validated against literature wind tunnel data of traffic pollutant dispersion in street canyons. The impact of trees is simulated for a variety of vegetation types and the full range of approaching wind directions at 15° interval. All these results are combined using meteo statistics, including effects of seasonal leaf loss, to determine the annual average effect of trees in street canyons. This analysis is performed for two pollutants, elemental carbon (EC) and PM10, using background concentrations and emission strengths for the city of Antwerp, Belgium. The results show that due to the presence of trees the annual average pollutant concentrations increase with about 8% (range of 1% to 13%) for EC and with about 1.4% (range of 0.2 to 2.6%) for PM10. The study indicates that this annual effect is considerably smaller than earlier estimates which are generally based on a specific set of governing conditions (1 wind direction, full leafed trees and peak hour traffic emissions).

Influence of avenue-trees on air quality at the urban neighborhood scale. Part II: Traffic pollutant concentrations at pedestrian level

Flow and dispersion of traffic-emitted pollutants were studied in a generic urban neighborhood for various avenue-tree layouts by employing 3D steady RANS simulations with the realizable k-ε turbulence model. In comparison to the tree-free situation quantitative and qualitative changes with flow reversal in the wind field were observed. Low to moderate increases (<13.2%) in the neighborhood-averaged pollutant concentration were found at pedestrian level. An approximately 1% increase in the neighborhood-averaged concentration was obtained with each percent of the street canyon volumes being occupied by vegetation for occupation fractions between 4 and 14%. The overall pattern of concentration changes relative to the tree-free situation was similar for all avenue-tree layouts. However, pronounced locally restricted decreases or increases in concentration (−87 to +1378%) occurred. The results indicate the necessity to account for existing or planned avenue-trees in neighborhood scale dispersion studies. Their consideration is prerequisite for reliable urban air quality assessment.

A vegetation modeling concept for Building and Environmental Aerodynamics wind tunnel tests and its application in pollutant dispersion studies

A new vegetation modeling concept for Building and Environmental Aerodynamics wind tunnel investigations was developed. The modeling concept is based on fluid dynamical similarity aspects and allows the small-scale modeling of various kinds of vegetation, e.g. field crops, shrubs, hedges, single trees and forest stands. The applicability of the modeling concept was validated in wind tunnel pollutant dispersion studies. Avenue trees in urban street canyons were modeled and their implications on traffic pollutant dispersion were investigated. The dispersion experiments proved the modeling concept to be practicable for wind tunnel studies and suggested to provide reliable concentration results. Unfavorable effects of trees on pollutant dispersion and natural ventilation in street canyons were revealed. Increased traffic pollutant concentrations were found in comparison to the tree-free reference case.

Traffic-Related Air Pollution and QT Interval: Modification by Diabetes, Obesity, and Oxidative Stress Gene Polymorphisms in the Normative Aging Study

BackgroundAcute exposure to ambient air pollution has been associated with acute changes in cardiac outcomes, often within hours of exposure.ObjectivesWe examined the effects of air pollutants on heart-rate–corrected QT interval (QTc), an electrocardiographic marker of ventricular repolarization, and whether these associations were modified by participant characteristics and genetic polymorphisms related to oxidative stress.MethodsWe studied repeated measurements of QTc on 580 men from the Veterans Affairs Normative Aging Study (NAS) using mixed-effects models with random intercepts. We fitted a quadratic constrained distributed lag model to estimate the cumulative effect on QTc of ambient air pollutants including fine particulate matter ≤ 2.5 μm in aerodynamic diameter (PM2.5), ozone (O3), black carbon (BC), nitrogen dioxide (NO2), carbon monoxide (CO), and sulfur dioxide (SO2) concentrations during the 10 hr before the visit. We genotyped polymorphisms related to oxidative stress and analyzed pollution–susceptibility score interactions using the genetic susceptibility score (GSS) method.ResultsAmbient traffic pollutant concentrations were related to longer QTc. An interquartile range (IQR) change in BC cumulative during the 10 hr before the visit was associated with increased QTc [1.89 msec change; 95% confidence interval (CI), −0.16 to 3.93]. We found a similar association with QTc for an IQR change in 1-hr BC that occurred 4 hr before the visit (2.54 msec change; 95% CI, 0.28–4.80). We found increased QTc for IQR changes in NO2 and CO, but the change was statistically insignificant. In contrast, we found no association between QTc and PM2.5, SO2, and O3. The association between QTc and BC was stronger among participants who were obese, who had diabetes, who were nonsmokers, or who had higher GSSs.ConclusionsTraffic-related pollutants may increase QTc among persons with diabetes, persons who are obese, and nonsmoking elderly individuals; the number of genetic variants related to oxidative stress increases this effect.

Model for Predicting Roadside Concentrations of Traffic Pollutants

An analytical model is presented to estimate traffic pollutant concentrations based on an artificial neural network (ANN) approach. The model can analyze the highly nonlinear relationship between the traffic flow attributes, meteorological conditions, road spatial characteristics, and the traffic pollutant concentrations. This study analyzes the multiple factors that affect the pollutant concentration and establishes the model structure using the ANN technique. Collected data for the pollutant concentrations as functions of variant factors was used to train the ANN model. A method was developed to automatically measure the traffic flow attributes, such as traffic flow, vehicle speed, and flow composition from video data. The results indicate that the model can reliably forecast CO 2 concentrations along the roads.

TRAFFIC-RELATED AIR POLLUTION AND CHILDREN’S RESPIRATORY HEALTH: DEVELOPING AND REFINING ESTIMATES OF RESIDENTIAL EXPOSURE

ISEE-521 Introduction: Several epidemiological studies have found associations between residential proximity to busy roads and adverse health effects. We recently conducted a school-based, cross-sectional study to examine respiratory health among children (8 to 11 years) living and attending schools at varying distances from high-traffic roads. Air pollutants, including particulate matter (PM10, PM2.5), black carbon (BC), and nitrogen oxides (NOX, NO,), were measured at each of ten schools. We found associations between traffic pollutants (especially BC, NOX, and NO {NOX- NO2}) and asthma and bronchitis episodes in the past 12 months, using a two-stage hierarchical model. In our analysis to date, we used pollutant levels measured at the school sites as estimates of the children’s exposure to traffic emissions. To refine exposure estimates, we obtained additional within-neighborhood measurements of NOX and NO2. We report here on the development of new measures of residential traffic exposure based on geographic information systems (GIS) technology. These metrics will then be compared with observed traffic pollutant concentrations. Methods: We utilize information on both school or residential address and traffic data using geographic information systems (GIS) technology to calculate various traffic metrics, including closest traffic volume within a given buffer radius, maximum traffic volume, and distance-weighted traffic density. Second, we develop a model incorporating prevailing wind direction and distance. Third, we present results of a spatial regression model similar to that developed by Brauer et al. (Epidemiology 2003; 14:228-39). This model uses information on several factors, such as local traffic density, distance to the highway and traffic counts, to explain the variation in school and neighborhood NOx/NO2 concentrations that were collected. Our last exposure measure is based on self-reported assessment of traffic from our intake questionnaires. Results: The GIS-based traffic metrics and spatial regression models will be presented and compared with previous results obtained using school-based or residential exposure measurements. Ultimately, these measures will be used to further explore associations between both bronchitis and asthma symptoms. Discussion: Different metrics of exposure to traffic pollutants can be used to explore exposure misclassification. By reducing measurement error, we will be able to elucidate more clearly the relationships of traffic to respiratory health outcomes. The results will help determine the relative importance of different approaches to refining exposure estimates and, in so doing, will provide methodological guidance for future traffic studies. Information generated from this study will be useful for both ambient air quality standard-setting and pollution control strategies.

Traffic-related air pollution near busy roads: the East Bay Children's Respiratory Health Study.

Recent studies, primarily in Europe, have reported associations between respiratory symptoms and residential proximity to traffic; however, few have measured traffic pollutants or provided information about local air quality. We conducted a school-based, cross-sectional study in the San Francisco Bay Area in 2001. Information on current bronchitis symptoms and asthma, home environment, and demographics was obtained by parental questionnaire (n = 1,109). Concentrations of traffic pollutants (particulate matter, black carbon, total nitrogen oxides [NO(X)], and nitrogen dioxide [NO(2)]) were measured at 10 school sites during several seasons. Although pollutant concentrations were relatively low, we observed differences in concentrations between schools nearby versus those more distant (or upwind) from major roads. Using a two-stage multiple-logistic regression model, we found associations between respiratory symptoms and traffic-related pollutants. Among those living at their current residence for at least 1 year, the adjusted odds ratio for asthma in relationship to an interquartile difference in NO(X) was 1.07 (95% confidence interval, 1.00-1.14). Thus, we found spatial variability in traffic pollutants and associated differences in respiratory symptoms in a region with good air quality. Our findings support the hypothesis that traffic-related pollution is associated with respiratory symptoms in children.

Traffic pollution inventories and modeling in metropolitan Dhaka, Bangladesh

Several monitoring and surveys on ambient concentration of oxides of nitrogen (NO x ), lead (Pb), particulate matter (PM), carbon monoxide (CO) and black smoke have been carried out by the author, Bangladesh Atomic Energy Commission (BAEC), Department of Civil Engineering, Bangladesh University of Engineering and Technology (BUET), and Department of Environment (DOE), Bangladesh Government at different street intersections of metropolitan Dhaka. In addition, all traffic pollutant concentrations at 82 street intersections were estimated using the Gaussian Plume Model. The surveys and the analysis were undertaken primarily to provide an independent check on the pollutant concentration and to determine if there is any violation of the international compliance. The study covers, for the first time in its type, wide areas of road intersections and surveyed concentration of oxides of nitrogen. It has been observed that the concentration of NO x , black smoke, lead, and PM violate both the national and international standards in metropolitan Dhaka. In addition, the concentration of CO is found relatively higher during the noon buildups.