A study of air pollutants and acute asthma exacerbations in urban areas: status report

A study to try to better understand the interactions between various air contaminants and acute asthma exacerbations is described. The study evaluates temporal associations between a panel of air contaminants and acute asthmatic exacerbations as measured by emergency room visits for asthma in communities in the Bronx and Manhattan in New York City (NYC). In addition, ambient levels of various air pollutants in two NYC communities are being compared. Almost 2 years of daily data have been collected for most of the air contaminants to be investigated. The air contaminants measured include gaseous compounds (ozone, sulfur dioxide, nitrogen oxides, aldehydes, nitrous acid, nitric acid, hydrochloric acid and ammonia), particulate matter components (metals, elemental and organic carbon, sulfate, hydrogen ion, pollen, mold spores and particle mass and number).     

Associations and lags between air pollution and acute respiratory visits in an ambulatory care setting: 25-month results from the aerosol research and inhalation epidemiological study

Particulate matter (PM) has been associated with adverse respiratory outcomes in numerous studies that utilized data from emergency room visits, hospital admissions, and mortality records. This study is unique in its investigation of associations of air pollution measures, including components of PM, with health outcomes in an ambulatory-care setting. Visit data were collected from Kaiser Permanente, a not-for-profit health maintenance organization in the metropolitan Atlanta, GA, area. Kaiser Permanente collaborated on the Aerosol Research Inhalation Epidemiological Study (ARIES), which provided detailed information on the characteristics of air pollutants. The Kaiser Permanente study was a time-series investigation of the possible associations between daily levels of suspended PM, inorganic gases, and polar volatile organic compounds and ambulatory care acute visit rates during the 25-month period from August 1, 1998, to August 31, 2000. For this interim analysis, the a priori 0-2 days lagged moving average, as well as the 3-5 days and 6-8 days lagged moving averages, of air quality measures were investigated. Single-pollutant Poisson general linear modeling was used to model daily visit counts for asthma and upper and lower respiratory infections (URI and LRI) by selected air quality metrics, controlling for temporal trends and meteorological variables. Most of the statistically significant positive associations were for the 3-5 days lagged air quality metrics with child asthma and LRI.     

Prediction of Traffic Noise: A Screening Technique

Abstract

Traffic noise is ubiquitous in many communities and is an important environmental concern, especially for persons located near major roadways. Several different methods are available to estimate noise levels resulting from roadway traffic. These include computational, graphical, and computer modeling techniques.

The prediction methodology presented here is a simplified technique that can be used for estimating noise resulting from traffic and for screening traffic noise impacts. This Traffic Noise Screening (TNS) approach consists of a series of traffic noise level prediction graphs developed for different roadway configurations. The graphs are based on the results from using the Federal Highway Administration (FHWA) STAMINA2.0 computerized noise prediction model for various scenarios. Data inputs to the TNS approach include roadway geometries, traffic volumes, vehicle travel speed, and centerline distance to the receptors.

The TNS graphs allow easy estimation of traffic noise levels for use in predicting traffic-related noise impacts. This TNS approach is not intended as a substitute for detailed modeling, such as with STAMINA2.0, but as a screening tool to aid in determining when detailed modeling may be necessary. If screening results indicate that noise estimates are significant, or if the scenario is rather complex, then additional, more detailed modeling can be performed.     

Spatial and temporal variations and mobile source emissions of polycyclic aromatic hydrocarbons in Quito, Ecuador

Motor vehicles are a major source of air pollution in Quito, Ecuador; however, little work has been done to characterize spatial and temporal variations in traffic-related pollutants, or to measure pollutants in vehicle emissions. We measured PAH continuously for one year at two residential sites in Quito, and PAH and traffic patterns for one week near a busy roadway. Morning rush-hour traffic and temperature inversions caused daily PAH maxima between 06:00 and 08:00. SO₂, NO_x, CO, and PM_2.5 behaved similarly. At the residential sites PAH levels during inversions were 2-3-fold higher than during the afternoon, and 10-16-fold higher than 02:00-03:00 when levels were lowest. In contrast, at the near-roadway site, PAH concentrations were 3-6-fold higher than at the residential sites, and the effects of inversions were less pronounced. Cars and buses accounted for >95% of PAH at the near-roadway site. Near-roadway PAH concentrations were comparable to other polluted cities.     

Distance-weighted traffic density in proximity to a home is a risk factor for leukemia and other childhood cancers

Occupational exposure to elevated concentrations of benzene is a known cause of leukemia in adults. Concentrations of benzene from motor vehicle exhaust could be elevated along highly trafficked streets. Several studies have reported significant associations between proximity to highly trafficked streets and the occurrence of childhood cancers and childhood leukemia. These associations may be due to chronic exposure to benzene or other carcinogenic components of vehicle exhaust from these nearby streets or to some other factor (e.g., noise, increased light exposure, or some unaccounted--for socioeconomic variable). We used data for homes studied in an earlier childhood cancer study conducted in Denver, CO, in the 1980s. No air pollution measurements were made in the original study. We identified the highest trafficked street near each study home and obtained the traffic density in 1979 and 1990. Traffic density was weighted for the distance from the street to the home using 3 different widths of Gaussian curves to approximate the decay of the emissions into the surrounding neighborhoods. The associations between the 750-ft-wide distance-weighted traffic density metrics and all childhood cancers and childhood leukemia are strongest in the highest traffic density category (> or = 20,000 vehicles per day [VPD]). The odds ratio is 5.90 (95% confidence interval [CI] 1.69-20.56) for all cancers and 8.28 (95% CI 2.09-32.80) for leukemia. The results are suggestive of an association between proximal high traffic streets with traffic counts > or = 20,000 VPD and childhood cancer, including leukemia.     

A land use regression model for predicting ambient volatile organic compound concentrations in Toronto,Canada

More than 25 studies have employed land use regression (LUR) models to estimate nitrogen oxides and to a lesser extent particulate matter indicators, but these methods have been less commonly applied to ambient concentrations of volatile organic compounds (VOCs). Some VOCs have high plausibility as sources of health effects and others are specific indicators of motor vehicle exhaust. We used LUR models to estimate spatial variability of VOCs in Toronto, Canada. Benzene, n-hexane and total hydrocarbons (THC) were measured from July 25 to August 9, 2006 at 50 locations using the TraceAir organic vapor monitors. Nitrogen dioxide (NO₂) was also sampled to assess its spatial pattern agreement with VOC exposures. Buffers for land use, population density, traffic density, physical geography, and remote sensing measures of greenness and surface brightness were also tested. The remote sensing measures have the highest correlations with VOCs and NO₂ levels (i.e., explains >36% of the variance). Our regression models explain 66–68% of the variance in the spatial distribution of VOCs, compared to 81% for the NO₂ model. The ranks of agreement between various VOCs range from 48 to 63% and increases substantially – up to 75% – for the top and bottom quartile groups. Agreements between NO₂ and VOCs are much smaller with an average rank of 36%. Future epidemiologic studies may therefore benefit from using VOCs as potential toxic agents for traffic-related pollutants.     

Predicting residential indoor concentrations of nitrogen dioxide,fine particulate matter,and elemental carbon using questionnaire and geographic information system based data

Previous studies have identified associations between traffic-related air pollution and adverse health effects. Most have used measurements from a few central ambient monitors and/or some measure of traffic as indicators of exposure, disregarding spatial variability and factors influencing personal exposure-ambient concentration relationships. This study seeks to utilize publicly available data (i.e., central site monitors, geographic information system, and property assessment data) and questionnaire responses to predict residential indoor concentrations of traffic-related air pollutants for lower socioeconomic status (SES) urban households.As part of a prospective birth cohort study in urban Boston, we collected indoor and outdoor 3–4 day samples of nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5) in 43 low SES residences across multiple seasons from 2003 to 2005. Elemental carbon (EC) concentrations were determined via reflectance analysis. Multiple traffic indicators were derived using Massachusetts Highway Department data and traffic counts collected outside sampling homes. Home characteristics and occupant behaviors were collected via a standardized questionnaire. Additional housing information was collected through property tax records, and ambient concentrations were collected from a centrally located ambient monitor.The contributions of ambient concentrations, local traffic and indoor sources to indoor concentrations were quantified with regression analyses. PM_2.5 was influenced less by local traffic but had significant indoor sources, while EC was associated with traffic and NO₂ with both traffic and indoor sources. Comparing models based on covariate selection using p-values or a Bayesian approach yielded similar results, with traffic density within a 50 m buffer of a home and distance from a truck route as important contributors to indoor levels of NO₂ and EC, respectively. The Bayesian approach also highlighted the uncertanity in the models. We conclude that by utilizing public databases and focused questionnaire data we can identify important predictors of indoor concentrations for multiple air pollutants in a high-risk population.     

Air pollution and hospital visits for acute upper and lower respiratory infections among children in Ningbo,China: A time-series analysis

Acute upper and lower respiratory infections are main causes of mortality and morbidity in children. Air pollution has been recognized as an important contributor to development and exacerbation of respiratory infections. However, few studies are available in China. In this study, we investigated the short-term effect of air pollution on hospital visits for acute upper and lower respiratory infections among children under 15 years in Ningbo, China. Poisson generalized models were used to estimate the associations between air pollution and hospital visits for acute upper and lower respiratory infections adjusted for temporal, seasonal, and meteorological effects. We found that four pollutants (PM_2.5, PM₁₀, NO₂, and SO₂) were significantly associated with hospital visits for acute upper and lower respiratory infections. The effect estimates for acute upper respiratory infections tended to be higher (PM_2.5 ER = 3.46, 95% CI 2.18, 4.76; PM₁₀ ER = 2.81, 95% CI 1.93, 3.69; NO₂ ER = 11.27, 95% CI 8.70, 13.89; SO₂ ER = 15.17, 95% CI 11.29, 19.19). Significant associations for gaseous pollutants (NO₂ and SO₂) were observed after adjustment for particular matter. Stronger associations were observed among older children and in the cold period. Our study suggested that short-term exposure to outdoor air pollution was associated with hospital visits for acute upper and lower respiratory infections in Ningbo.     

Health effects of ozone focusing on childhood asthma: What is now known – a review from an epidemiological point of view

Protecting the health of children and the environment is an essential objective for the health policies of any modern society, being also crucial for a sustainable development, according to the World Health Organization. Evaluating the risk of developing childhood asthma is one of the four priority issues identified by the European Commission, according to the European Union Environment and Health Action Plan.Accordingly, this review aimed to update information concerning the effects of exposure to ozone on childhood asthma, thus helping in the development of strategies for further research. Studies have been demonstrating strong associations between the exposure to ozone and asthma. However, the complexity of exposure patterns, the changes in the vulnerability of children at various stages of development, and the practical limitations of research, lead to a still incomplete understanding of the ozone impact on the health of children. Difficulties on the interpretation of epidemiological studies to evaluate chronic effects are mainly due to an absence of studies designed specifically to address this question and to inherent limitations in characterizing exposure. The more rigorous studies provided new evidences for chronic effects of ozone on small airway function and possibly on asthma, but substantial uncertainties remain.     

Predicting Airborne Particle Levels Aboard Washington State School Buses

School buses contribute substantially to childhood air pollution exposures yet they are rarely quantified in epidemiology studies. This paper characterizes fine particulate matter (PM(2.5)) aboard school buses as part of a larger study examining the respiratory health impacts of emission-reducing retrofits.To assess onboard concentrations, continuous PM(2.5) data were collected during 85 trips aboard 43 school buses during normal driving routines, and aboard hybrid lead vehicles traveling in front of the monitored buses during 46 trips. Ordinary and partial least square regression models for PM(2.5) onboard buses were created with and without control for roadway concentrations, which were also modeled. Predictors examined included ambient PM(2.5) levels, ambient weather, and bus and route characteristics.Concentrations aboard school buses (21 mug/m(3)) were four and two-times higher than ambient and roadway levels, respectively. Differences in PM(2.5) levels between the buses and lead vehicles indicated an average of 7 mug/m(3) originating from the bus's own emission sources. While roadway concentrations were dominated by ambient PM(2.5), bus concentrations were influenced by bus age, diesel oxidative catalysts, and roadway concentrations. Cross validation confirmed the roadway models but the bus models were less robust.These results confirm that children are exposed to air pollution from the bus and other roadway traffic while riding school buses. In-cabin air pollution is higher than roadway concentrations and is likely influenced by bus characteristics.     

Developing a high-resolution vehicular emission inventory by integrating an emission model and a traffic model: Part 2--A case study in Beijing

A grid-based, bottom-up method has been proposed by combining a vehicle emission model and a travel demand model to develop a high-resolution vehicular emission inventory for Chinese cities. Beijing is used as a case study in which the focus is on fuel consumption and emissions from hot-stabilized activities of light-duty gasoline vehicles (LGVs) in 2005. The total quantity of emissions, emission intensity, and spatial distribution of emissions at 1- by 1-km resolution are presented and compared with results from other inventory methods commonly used in China. The results show that the total daily fuel consumption and vehicular emissions of carbon dioxide, carbon monoxide, hydrocarbons, and oxides of nitrogen from LGVs in the Beijing urban area in 2005 were 1.95 x 10(7) L, 4.28 x 10(4) t, 1.97 x 10(3) t, 0.28 x 10(3) t, and 0.14 x 10(3) t, respectively. Vehicular fuel consumption and emissions show spatial variations that are consistent with the traffic characteristics. The grid-based inventory developed in this study reflects the influence of traffic conditions on vehicle emissions at the microscale and may be applied to evaluate the effectiveness of traffic-related measures on emission control in China.     

Influence of angular exposure and proximity to vehicular traffic on the diversity of epiphytic lichens and the bioaccumulation of traffic-related elements

This study investigated the influence of angular exposure and distance from vehicular traffic on the diversity of epiphytic lichens and the bioaccumulation of traffic-related elements in a town of central Italy. An Index of Lichen Diversity (ILD) was calculated on the street-facing and the opposite side of road-lining trees and in a urban park 250 m away, and the content of selected trace elements (Al, Ba, Ce, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Sb, V, and Zn) was determined in samples of the lichen Punctelia borreri (Sm.) Krog growing on tree bark, both on the exposed and opposite sides. ILD increases with distance from traffic emissions. However, at the site with vehicle traffic, non-nitrophilous lichens decreased while nitrophilous ones increased. The concentration of the traffic-related elements Ba, Cr, Cu, Mn, Sb, and Zn accumulated in thalli of P. borreri was higher on roadside trees than in trees from the urban park. ILD was not affected by the angular exposure to the road and the bioaccumulation of traffic-related elements was similar in lichens from the side of the bole exposed to traffic emissions and particulate resuspension and from the opposite side. The angular exposure in respect to the traffic source does not influence trace element accumulation. These results are important when using lichens for biomonitoring purposes, both for planning future studies and for the reliability of the interpretation of past surveys that do not report information about the angular exposure of the collected lichen material.     

Developing a High-Resolution Vehicular Emission Inventory by Integrating an Emission Model and a Traffic Model: Part 2—A Case Study in Beijing

Abstract

A grid-based, bottom-up method has been proposed by combining a vehicle emission model and a travel demand model to develop a high-resolution vehicular emission inventory for Chinese cities. Beijing is used as a case study in which the focus is on fuel consumption and emissions from hot-stabilized activities of light-duty gasoline vehicles (LGVs) in 2005. The total quantity of emissions, emission intensity, and spatial distribution of emissions at 1- by 1-km resolution are presented and compared with results from other inventory methods commonly used in China. The results show that the total daily fuel consumption and vehicular emissions of carbon dioxide, carbon monoxide, hydrocarbons, and oxides of nitrogen from LGVs in the Beijing urban area in 2005 were 1.95 × 10⁷ L, 4.28 × 10⁴ t, 1.97 × 10³ t, 0.28 × 10³ t, and 0.14 × 10³ t, respectively. Vehicular fuel consumption and emissions show spatial variations that are consistent with the traffic characteristics. The grid-based inventory developed in this study reflects the influence of traffic conditions on vehicle emissions at the microscale and may be applied to evaluate the effectiveness of traffic-related measures on emission control in China.     

Statistical and diagnostic evaluation of the ADMS-Urban model compared with an urban air quality monitoring network

The present study examines the behaviour of the ADMS-Urban air quality forecasting model in predicting dispersion of traffic-related pollutants in urban areas. The study has been carried out in Ravenna (NE Italy), a medium-sized town where pollution produced by vehicle traffic accounts for most of the emissions. ADMS-Urban performances have been assessed through statistical analysis, by comparing carbon monoxide concentrations (vehicle traffic tracing pollutant) estimated by the model with concentrations measured by stations of the air quality monitoring network. Although the correspondence of values estimated by ADMS-Urban with measured values turns out to be satisfactory, the study shows that the model tends to produce an underestimated value compared with the actual situation, and identifies a corrective method that makes it possible to improve the relevant performances. Furthermore, the diagnostic analysis highlights that the model performances depend upon some meteorological parameters.     

Development of a distance-to-roadway proximity metric to compare near-road pollutant levels to a central site monitor

The primary objective of the Detroit Exposure and Aerosol Research Study (DEARS) was to compare air pollutant concentrations measured at various neighborhoods, or exposure monitoring areas (EMAs), throughout a major metropolitan area to levels measured at a central site or community monitor. One of the EMAs was located near a busy freeway (annual average daily traffic (AADT) of ～130,000) so that impacts of mobile sources could be examined. Air pollution concentrations from the roadway-proximate sites were compared to the central site monitor. The volatile organic compounds (VOCs) selected (benzene, toluene, ethylbenzene, m,p- and o-xylene, 1,3 butadiene, 1,3,5-trimethylbenzene and 4-ethyltoluene) are typically associated with mobile sources. Gradients were also evident that demonstrated the amplification of pollutant levels near the roadway compared to the community monitor. A novel distance-to-roadway proximity metric was developed to plot the measurements and model these gradients. Effective distance represents the actual distance an air parcel travels from the middle of a roadway to a site and varies as a function of wind direction, whereas perpendicular distance is a fixed distance oriented normal to the roadway. Perpendicular distance is often used as a proxy for exposures to traffic emissions in epidemiological studies.Elevated concentrations of all the compounds were found for both a summer and winter season. Effective distance was found to be a statistically significant (p < 0.05) univariate predictor for concentrations of toluene, ethylbenzene, m,p-xylene and o-xylene for summer 2005. For each of these pollutants, effective distance yielded lower p-values than the corresponding perpendicular distance models, and model fit improved. Results demonstrate that this near-road EMA had elevated levels of traffic-related VOCs compared to the community monitor, and that effective distance was a more accurate predictor of the degree to which they were elevated as a function of distance. Effective distance produced a range of distance-to-roadway values for a single site based on wind direction, thus increasing the number and range of values that could be used to plot and predict relative differences in pollutant concentrations between two sites.     

Long-term personal exposure to PM2.5, soot and NOx in children attending schools located near busy roads,a validation study

Several studies have investigated the health of children attending schools located near busy roads. In this study, we have measured personal exposure to traffic-related pollutants in children to validate exposure classification based on school location. Personal exposure to PM_2.5, soot, NO_x and NO₂ was measured during four 48-h periods. The study involved 54 children attending four different schools, two of which were located within 100 m of a major road (one ring road and one freeway) and the other two were located at a background location in the city of Utrecht, The Netherlands. Outdoor monitoring was conducted at all school sites, during the personal measurements. A questionnaire was administered on time activity patterns and indoor sources at home. The outdoor concentration of soot was 74% higher at the freeway school compared to its matched background school. Personal exposure to soot was 30% higher. For NO_x the outdoor concentration was 52% higher at the freeway school compared to its background school. The personal concentration of NO_x was 37% higher for children attending the freeway school. Differences were smaller and insignificant for PM_2.5 and NO₂. No elevated personal exposure to air pollutants was found for the children attending the school near the ring road. We conclude that the school's proximity to a freeway can be used as a valid estimate of exposure in epidemiological studies on the effects of the traffic-related air pollutants soot and NO_x in children.     

Developing a high-resolution vehicular emission inventory by integrating an emission model and a traffic model: Part 1--Modeling fuel consumption and emissions based on speed and vehicle-specific power

To improve the accuracy and applicability of vehicular emission models, this study proposes a speed and vehicle-specific power (VSP) modeling method to estimate vehicular emissions and fuel consumption using data gathered by a portable emissions monitoring system (PEMS). The PEMS data were categorized into discrete speed-VSP bins on the basis of the characteristics of vehicle driving conditions and emissions in Chinese cities. Speed-VSP modal average rates of emissions (or fuel consumption) and the time spent in the corresponding speed-VSP bins were then used to calculate the total trip emissions (or fuel consumption) and emission factors (or fuel economy) under specific average link speeds. The model approach was validated by comparing it against measured data with prediction errors within 20% for trip emissions and link-speed-based emission factors. This analysis is based on the data of light-duty gasoline vehicles in China; however, this research approach could be generalized to other vehicle fleets in other countries. This modeling method could also be coupled with traffic demand models to establish high-resolution emissions inventories and evaluate the impacts of traffic-related emission control measures.     

The impact of transportation control measures on emission reductions during the 2008 Olympic Games in Beijing,China

Traffic congestion and air pollution were two major challenges for the planners of the 2008 Olympic Games in Beijing. The Beijing municipal government implemented a package of temporary transportation control measures during the event. In this paper, we report the results of a recent research project that investigated the effects of these measures on urban motor vehicle emissions in Beijing. Bottom–up methodology has been used to develop grid-based emission inventories with micro-scale vehicle activities and speed-dependent emission factors. The urban traffic emissions of volatile organic compounds (VOC), carbon monoxide (CO), nitrogen oxides (NO_x) and particulate matter with an aerodynamic diameter of 10 μm or less (PM₁₀) during the 2008 Olympics were reduced by 55.5%, 56.8%, 45.7% and 51.6%, respectively, as compared to the grid-based emission inventory before the Olympics. Emission intensity was derived from curbside air quality monitoring at the North 4th Ring Road site, located about 7 km from the National Stadium. Comparison between the emission intensity before and during the 2008 Olympics shows a reduction of 44.5% and 49.0% in daily CO and NO_x emission from motor vehicles. The results suggest that reasonable traffic system improvement strategies along with vehicle technology improvements can contribute to controlling total motor vehicle emissions in Beijing after the Olympic Games.     

Application of a microscale emission factor model for particulate matter to calculate vehicle-generated contributions to fine particulate emissions

This paper discusses the evaluation and application of a new generation of particulate matter (PM) emission factor model (MicroFacPM). MicroFacPM that was evaluated in Tuscarora Mountain Tunnel, Pennsylvania Turnpike, PA shows good agreement between measured and modeled emissions. MicroFacPM application is presented to the vehicle traffic on the main approach road to the Ambassador Bridge, which is one of the most important international border entry points in North America, connecting Detroit, MI, with Windsor, Ontario, Canada. An increase in border security has forced heavy-duty diesel vehicles to line up for several kilometers through the city of Windsor causing concern about elevated concentrations of ambient PM. MicroFacPM has been developed to model vehicle-generated PM (fine [PM2.5] and coarse < or = 10 microm [PM10]) from the on-road vehicle fleet, which in this case includes traffic at very low speeds (10 km/h). The Windsor case study gives vehicle generated PM2.5 sources and their breakdown by vehicle age and class. It shows that the primary sources of vehicle-generated PM2.5 emissions are the late-model heavy-duty diesel vehicles. We also applied CALINE4 and AERMOD in conjunction with MicroFacPM, using Canadian traffic and climate conditions, to describe the vehicle-generated PM2.5 dispersion near this roadway during the month of May in 2003.     

Synthesis of Harvard Environmental Protection Agency (EPA) Center studies on traffic-related particulate pollution and cardiovascular outcomes in the Greater Boston Area

The association between particulate pollution and cardiovascular morbidity and mortality is well established. While the cardiovascular effects of nationally regulated criteria pollutants (e.g., fine particulate matter [PM_2.5] and nitrogen dioxide) have been well documented, there are fewer studies on particulate pollutants that are more specific for traffic, such as black carbon (BC) and particle number (PN). In this paper, we synthesized studies conducted in the Greater Boston Area on cardiovascular health effects of traffic exposure, specifically defined by BC or PN exposure or proximity to major roadways. Large cohort studies demonstrate that exposure to traffic-related particles adversely affect cardiac autonomic function, increase systemic cytokine-mediated inflammation and pro-thrombotic activity, and elevate the risk of hypertension and ischemic stroke. Key patterns emerged when directly comparing studies with overlapping exposure metrics and population cohorts. Most notably, cardiovascular risk estimates of PN and BC exposures were larger in magnitude or more often statistically significant compared to those of PM_2.5 exposures. Across multiple exposure metrics (e.g., short-term vs. long-term; observed vs. modeled) and different population cohorts (e.g., elderly, individuals with co-morbidities, young healthy individuals), there is compelling evidence that BC and PN represent traffic-related particles that are especially harmful to cardiovascular health. Further research is needed to validate these findings in other geographic locations, characterize exposure errors associated with using monitored and modeled traffic pollutant levels, and elucidate pathophysiological mechanisms underlying the cardiovascular effects of traffic-related particulate pollutants.

Implications: Traffic emissions are an important source of particles harmful to cardiovascular health. Traffic-related particles, specifically BC and PN, adversely affect cardiac autonomic function, increase systemic inflammation and thrombotic activity, elevate BP, and increase the risk of ischemic stroke. There is evidence that BC and PN are associated with greater cardiovascular risk compared to PM_2.5. Further research is needed to elucidate other health effects of traffic-related particles and assess the feasibility of regulating BC and PN or their regional and local sources.