Concentrations Of Traffic-related Air Pollutants Research Articles

Interaction between neighborhood walkability and traffic-related air pollution on hypertension and diabetes: The CANHEART cohort

BackgroundLiving in unwalkable neighborhoods has been associated with heightened risk for diabetes and hypertension. However, highly walkable environments may have higher concentrations of traffic-related air pollution, which may contribute to increased cardiovascular disease risk. We therefore aimed to assess how walkability and traffic-related air pollution jointly affect risk for hypertension and diabetes. MethodsWe used a cross-sectional, population-based sample of individuals aged 40–74 years residing in selected large urban centres in Ontario, Canada on January 1, 2008, assembled from administrative databases. Walkability and traffic-related air pollution (NO2) were assessed using validated tools and linked to individuals based on neighborhood of residence. Logistic regression was used to estimate adjusted associations between exposures and diagnoses of hypertension or diabetes accounting for potential confounders. ResultsOverall, 2,496,458 individuals were included in our analyses. Low walkability was associated with higher odds of hypertension (lowest vs. highest quintile OR = 1.34, 95% CI: 1.32, 1.37) and diabetes (lowest vs. highest quintile OR = 1.25, 95% CI: 1.22, 1.29), while NO2 exhibited similar trends (hypertension: OR = 1.09 per 10 p.p.b., 95% CI: 1.08, 1.10; diabetes: OR = 1.16, 95% CI: 1.14, 1.17). Significant interactions were identified between walkability and NO2 on risk for hypertension (p < 0.0001 and diabetes (p < 0.0001). At higher levels of pollution (40 p.p.b.), differences in the probability of hypertension (lowest vs. highest walkability quintile: 0.26 vs. 0.25) or diabetes (lowest vs. highest walkability quintile: 0.15 vs. 0.15) between highly walkable and unwalkable neighborhoods were diminished, compared to differences observed at lower levels of pollution (5 p.p.b.) (hypertension, lowest vs. highest walkability quintile: 0.21 vs. 0.13; diabetes, lowest vs. highest walkability quintile: 0.09 vs. 0.06). ConclusionsWalkability and traffic-related air pollution interact to jointly predict risk for hypertension and diabetes. Although walkable neighborhoods appear to have beneficial effects, they may accentuate the harmful effects of air pollution on cardiovascular risk factors.

Study the effectiveness of different actions and policies in improving urban air quality: Dammam City as a case study

ABSTRACTTraffic-related air pollution abatement will remain a challenge because of increasing demand for transportation. This study was aiming to assess the effectiveness of different actions and policies in improving urban air quality. Levels of five air pollutants were simultaneously measured at three locations with different human activities for continuous six years starting from 2010 to 2015 at Dammam City in Saudi Arabia. Data of road traffic policies and administrative actions was obtained from several governmental authorities. Levels of the five pollutants were gradually reduced from year to year with different percents and trends. As for PM10 and VOCs, levels of the industrial and commercial areas were still higher than their recommended air quality guidelines (AQGs) (150 μg/m3 and 0.24 ppm respectively). The traffic management policies and administrative actions appear to be effective to produce significant decreases in traffic-related air pollution concentrations and improve the air quality of urban areas.

Regional and traffic-related air pollutants are associated with higher consumption of fast food and trans fat among adolescents

Air pollution exposures are novel contributors to the growing childhood obesity epidemic. One possible mechanism linking air pollution exposures and obesity is through changes in food consumption patterns. The aim of this study was to examine the longitudinal association between childhood exposure to air pollutants and changes in diet among adolescents. School-age children were enrolled in the Southern California Children's Health Study during 1993-1994 (n=3100) and were followed for 4-8 y. Community-level regional air pollutants [e.g., nitrogen dioxide (NO2), elemental carbon (EC), and fine particles with aerodynamic diameter <2.5 µm (PM2.5)] were measured at central monitoring stations. Line dispersion modeling was used to estimate concentrations of traffic-related air pollutants based on nitrogen oxides (NOx) at participants' residential addresses. In addition, self-reported diet information was collected annually using a structured youth/adolescent food-frequency questionnaire during 1997-2001. Generalized linear mixed-effects models were used in the association analyses. Higher exposures to regional and traffic-related air pollutants were associated with intake of a high-trans-fat diet, after adjusting for confounders including socioeconomic status and access to fast food in the community. A 2-SD (12.2 parts per billion) increase in regional NO2 exposure was associated with a 34% increased risk of consuming a high-trans-fat diet compared with a low-trans-fat diet (OR: 1.34; 95% CI:1.05, 1.72). In addition, higher exposures to acid vapor, EC, PM2.5, and non-freeway NOx were all associated with higher consumption of dietary trans fat (all P<0.04). Notably, higher exposures to regional NO2, acid vapor, and EC were also associated with a higher consumption of fast food (all P<0.05). Childhood exposures to regional and traffic-related air pollutants were associated with increased consumption by adolescents of trans fat and fast foods. Our results indicate that air pollution exposures may contribute to obesogenic behaviors. This study was registered at clinicaltrials.gov as NCT03379298.

Sensitivity analysis of the near-road dispersion model RLINE - An evaluation at Detroit, Michigan

The development of accurate and appropriate exposure metrics for health effect studies of traffic-related air pollutants (TRAPs) remains challenging and important given that traffic has become the dominant urban exposure source and that exposure estimates can affect estimates of associated health risk. Exposure estimates obtained using dispersion models can overcome many of the limitations of monitoring data, and such estimates have been used in several recent health studies. This study examines the sensitivity of exposure estimates produced by dispersion models to meteorological, emission and traffic allocation inputs, focusing on applications to health studies examining near-road exposures to TRAP. Daily average concentrations of CO and NOx predicted using the Research Line source model (RLINE) and a spatially and temporally resolved mobile source emissions inventory are compared to ambient measurements at near-road monitoring sites in Detroit, MI, and are used to assess the potential for exposure measurement error in cohort and population-based studies. Sensitivity of exposure estimates is assessed by comparing nominal and alternative model inputs using statistical performance evaluation metrics and three sets of receptors. The analysis shows considerable sensitivity to meteorological inputs; generally the best performance was obtained using data specific to each monitoring site. An updated emission factor database provided some improvement, particularly at near-road sites, while the use of site-specific diurnal traffic allocations did not improve performance compared to simpler default profiles. Overall, this study highlights the need for appropriate inputs, especially meteorological inputs, to dispersion models aimed at estimating near-road concentrations of TRAPs. It also highlights the potential for systematic biases that might affect analyses that use concentration predictions as exposure measures in health studies.

NO 2 but Not PM 2.5 at the Home Address is Associated with Concern over Health Effects of Air Pollution

Background People living in urban areas in Europe are exposed to elevated concentrations of traffic-related air pollution. The lower the air pollution levels, the better for your health; so people exposed to higher concentrations should be worried more about air pollution. But are they? The aim of this analysis was to examine associations between concern over health effects of air pollution and personal and environmental factors. Methods In 7 European cities, >12,000 participants over 18 years were opportunistically recruited to complete an online questionnaire on travel and physical activity behaviour, perceptions and attitudes, and sociodemographics. The following question was assessed on a 5-point scale: “Are you worried that air pollution in the neighbourhood of either your home or work can lead to health problems?”. Mixed effects logistic regression was used to model concern over health effects of air pollution (worried (level 4–5) versus not-worried (level 1–3); city as random effect). Variables were forced into the model when they proved to be significant in bivariate analyses (significance level 0.05). Variables were chosen based on previous studies, and most variables were self-reported. Physical activity was expressed as MET minutes per week, derived from the GPAQ questionnaire. Distance from the home to the nearest major road was derived in GIS, and air pollution at the home address was determined using the West-European PM 2.5 and NO 2 land use regression models from de Hoogh et al. (2016). Results Fifty-seven percent of participants were worried over health effects of air pollution with large differences across cities (Antwerp 77%; Barcelona 81%; London 64%; Oerebro 12%; Rome 72%; Vienna 43%; Zurich 34%). Linking mean modelled air pollution directly to mean level of concern per city, gave a good correlation for NO 2 (r²=0.75), and a lower correlation for PM 2.5 (r²=0.49). In bivariate analyses, city, sex, level of education, self-reported health status, having children in the household, distance to the nearest major road, level of physical activity, and NO 2 and PM 2.5 at the home address were significantly linked to concern over health effects of air pollution. In the mixed effects logistic regression model sex, self-reported health status, having children in the household, level of physical activity, and NO 2 at the home address remained significant. Conclusions Being male, having a worse self-reported health, having children in the household, being more physically active, and higher NO 2 at the home address were associated with higher concern over health effects of air pollution.

Is Neighborhood Green Space Protective Against Associations Between Child Asthma, Neighborhood Traffic Volume and Area Safety? Multilevel Analysis of 4,447 Australian Children

Background Evidence on the association between green space and child asthma is equivocal. The aim of this paper was to determine the extent that higher quantities of green space buffer associations between child asthma and traffic volume (air pollution surrogate) and/or a perceived lack of area safety. Methods Multilevel models were used to analyze affirmative asthma cases in nationally representative cross-sectional data from 4,447 children aged 6-7 years old in Australia. Case-finding of affirmative asthma was based upon a triangulation of affirmative responses to three questions on doctor-diagnosed asthma, asthma-related medications and illness with wheezing lasting for at least 1 week within 12 months prior to the survey. Buffering was tested via interactions between green space quantity and (i) parent-reported traffic volume or (ii) perceived lack of area safety. Results Asthma prevalence was lower in areas with more green space for participants considered to be exposed to heavy traffic and also regardless of area safety. Among participants considered to be exposed to high traffic volumes and areas with 0% to 20% green space quantity, the odds of affirmative asthma were 1.88 (95%CI 1.38 to 2.56). However, those odds dropped to 0.31 (95%CI 0.12 to 0.82) for participants living in areas with over 40% green space coverage, despite also being in proximity of heavy traffic. No association between affirmative asthma and green space coverage was observed for participants not exposed to heavy traffic, nor for the area safety variable. Conclusions Protecting existing and investing in new green space may help to promote child respiratory health through the buffering of traffic-related air pollution concentrations.

Association Between Air Pollution and Coronary Artery Calcification Within Six Metropolitan Areas in the USA (the Multi-Ethnic Study of Atherosclerosis and Air Pollution): A Longitudinal Cohort Study

Background Long-term exposure to fi ne particulate matter less than 2·5 μm in diameter (PM2·5) and traffi c-related air pollutant concentrations are associated with cardiovascular risk. The disease process underlying these associations remains uncertain. We aim to assess association between long-term exposure to ambient air pollution and progression of coronary artery calcium and common carotid artery intima-media thickness. Methods In this prospective 10-year cohort study, we repeatedly measured coronary artery calcium by CT in 6795 participants aged 45–84 years enrolled in the Multi-Ethnic Study of Atherosclerosis and Air P ollution (MESA Air) in six metropolitan areas in the USA. Repeated scans were done for nearly all participants between 2002 and 2005, for a subset of participants between 2005 and 2007, and for half of all participants between 2010 and 2012. Common carotid artery intima-media thickness was measured by ultrasound in all participants at baseline and in 2010–12 for 3459 participants. Residence-specifi c spatio-temporal pollution concentration models, incorporating communityspecifi c measurements, agency monitoring data, and geographical predictors, estimated concentrations of PM2·5 and nitrogen oxides (NOX) between 1999 and 2012. The primary aim was to examine the association between both progression of coronary artery calcium and mean carotid artery intima-media thickness and long-term exposure to ambient air pollutant concentrations (PM2·5, NOX, and black carbon) between examinations and within the six metropolitan areas, adjusting for baseline age, sex, ethnicity, socioeconomic characteristics, cardiovascular risk factors, site, and CT scanner technology. Findings In this population, coronary calcium increased on average by 24 Agatston units per year (SD 58), and intimamedia thickness by 12 μm per year (10), before adjusting for risk factors or air pollutant exposures. Participantspecifi c pollutant concentrations averaged over the years 2000–10 ranged from 9·2–22·6 μg PM2·5/m³ and 7·2–139·2 parts per billion (ppb) NOX. For each 5 μg PM2·5/m³ increase, coronary calcium progressed by 4·1 Agatston units per year (95% CI 1·4–6·8) and for each 40 ppb NOX coronary calcium progressed by 4·8 Agatston units per year (0·9–8·7). Pollutant exposures were not associated with intima-media thickness change. The estimate for the eff ect of a 5 μg/m³ higher long-term exposure to PM2·5 in intima-media thickness was –0·9 μm per year (95% CI –3·0 to 1·3). For 40 ppb higher NOX, the estimate was 0·2 μm per year (–1·9 to 2·4). Interpretation Increased concentrations of PM2·5 and traffi c-related air pollution within metropolitan areas, in ranges commonly encountered worldwide, are associated with progression in coronary calcifi cation, consistent with acceleration of atherosclerosis. This study supports the case for global eff orts of pollution reduction in prevention of cardiovascular diseases.

Did a vehicle emission inspection program lead to lower cardiovascular mortality in the Greater Vancouver region?

Introduction: The AirCare vehicle inspection program began in 1992 to control tailpipe emissions within the Greater Vancouver area, Canada, and ended in 2014. Since 1992, there have been regional declines in concentrations of traffic-related air pollution (TRAP) and cardiovascular mortality. Some of the declines in TRAP can be attributed to the AirCare program. While higher level of TRAP has been associated with higher rate of cardiovascular mortality, it is possible that some of the declines in cardiovascular mortality in the region is the effect of the AirCare program. This study is aimed to quantify such an effect, which is challenging to separate from the secular trend of mortality resulting from other complex factors. Methods: A time-slice analysis was applied to estimate the effect of each AirCare phase compared with the previous phase, both unadjusted and with adjustment for cardiovascular mortality secular trends observed in Victoria and Calgary, two most comparable cities in Canada without similar programs. A time-series analysis was applied to estimate the effect of every 100 failed cars on cardiovascular mortality in a distributed lag framework. Results: Time-slice analyses showed that the AirCare effects were sensitive to choice of the control population. Time-series analyses showed a 2.9% (95%CI 1.0%, 4.9%) decrease in daily cardiovascular mortality for each 100 cars that failed, when the lagged effect was distributed over one year. Results suggest that the AirCare program reduced cardiovascular mortality in the region by 2,000-11,000 deaths over its lifetime. Conclusions: Evaluation of an air quality intervention implemented over 22 years is statistically challenging. Our results suggest that the AirCare program contributes to the reduction of cardiovascular mortality in the Greater Vancouver area, and provide evidence for other regions considering implementation or extension of similar programs.

A novel mobile monitoring approach to characterize spatial and temporal variation in traffic-related air pollutants in an urban community

Air concentrations of traffic-related air pollutants (TRAPs) vary in space and time within urban communities, presenting challenges for estimating human exposure and potential health effects. Conventional stationary monitoring stations/networks cannot effectively capture spatial characteristics. Alternatively, mobile monitoring approaches became popular to measure TRAPs along roadways or roadsides. However, these linear mobile monitoring approaches cannot thoroughly distinguish spatial variability from temporal variations in monitored TRAP concentrations. In this study, we used a novel mobile monitoring approach to simultaneously characterize spatial/temporal variations in roadside concentrations of TRAPs in urban settings. We evaluated the effectiveness of this mobile monitoring approach by performing concurrent measurements along two parallel paths perpendicular to a major roadway and/or along heavily trafficked roads at very narrow scale (one block away each other) within short time period (<30 min) in an urban community. Based on traffic and particulate matter (PM) source information, we selected 4 neighborhoods to study. The sampling activities utilized real-time monitors, including battery-operated PM2.5 monitor (SidePak), condensation particle counter (CPC 3007), black carbon (BC) monitor (Micro-Aethalometer), carbon monoxide (CO) monitor (Langan T15), and portable temperature/humidity data logger (HOBO U12), and a GPS-based tracker (Trackstick). Sampling was conducted for ∼3 h in the morning (7:30–10:30) in 7 separate days in March/April and 6 days in May/June 2012. Two simultaneous samplings were made at 5 spatially-distributed locations on parallel roads, usually distant one block each other, in each neighborhood. The 5-min averaged BC concentrations (AVG ± SD, [range]) were 2.53 ± 2.47 [0.09–16.3] μg/m3, particle number concentrations (PNC) were 33,330 ± 23,451 [2512–159,130] particles/cm3, PM2.5 mass concentrations were 8.87 ± 7.65 [0.27–46.5] μg/m3, and CO concentrations were 1.22 ± 0.60 [0.22–6.29] ppm in the community. The traffic-related air pollutants, BC and PNC, but not PM2.5 or CO, varied spatially depending on proximity to local stationary/mobile sources. Seasonal differences were observed for all four TRAPs, significantly higher in colder months than in warmer months. The coefficients of variation (CVs) in concurrent measurements from two parallel routes were calculated around 0.21 ± 0.17, and variations were attributed by meteorological variation (25%), temporal variability (19%), concentration level (6%), and spatial variability (2%), respectively. Overall study findings suggest this mobile monitoring approach could effectively capture and distinguish spatial/temporal characteristics in TRAP concentrations for communities impacted by heavy motor vehicle traffic and mixed urban air pollution sources.

Association between air pollution and coronary artery calcification within six metropolitan areas in the USA (the Multi-Ethnic Study of Atherosclerosis and Air Pollution): a longitudinal cohort study

Long-term exposure to fine particulate matter less than 2.5 μm in diameter (PM2.5) and traffic-related air pollutant concentrations are associated with cardiovascular risk. The disease process underlying these associations remains uncertain. We aim to assess association between long-term exposure to ambient air pollution and progression of coronary artery calcium and common carotid artery intima-media thickness. In this prospective 10-year cohort study, we repeatedly measured coronary artery calcium by CT in 6795 participants aged 45-84 years enrolled in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) in six metropolitan areas in the USA. Repeated scans were done for nearly all participants between 2002 and 2005, for a subset of participants between 2005 and 2007, and for half of all participants between 2010 and 2012. Common carotid artery intima-media thickness was measured by ultrasound in all participants at baseline and in 2010-12 for 3459 participants. Residence-specific spatio-temporal pollution concentration models, incorporating community-specific measurements, agency monitoring data, and geographical predictors, estimated concentrations of PM2.5 and nitrogen oxides (NOX) between 1999 and 2012. The primary aim was to examine the association between both progression of coronary artery calcium and mean carotid artery intima-media thickness and long-term exposure to ambient air pollutant concentrations (PM2.5, NOX, and black carbon) between examinations and within the six metropolitan areas, adjusting for baseline age, sex, ethnicity, socioeconomic characteristics, cardiovascular risk factors, site, and CT scanner technology. In this population, coronary calcium increased on average by 24 Agatston units per year (SD 58), and intima-media thickness by 12 μm per year (10), before adjusting for risk factors or air pollutant exposures. Participant-specific pollutant concentrations averaged over the years 2000-10 ranged from 9.2-22.6 μg PM2.5/m(3) and 7.2-139.2 parts per billion (ppb) NOX. For each 5 μg PM2.5/m(3) increase, coronary calcium progressed by 4.1 Agatston units per year (95% CI 1.4-6.8) and for each 40 ppb NOX coronary calcium progressed by 4.8 Agatston units per year (0.9-8.7). Pollutant exposures were not associated with intima-media thickness change. The estimate for the effect of a 5 μg/m(3) higher long-term exposure to PM2.5 in intima-media thickness was -0.9 μm per year (95% CI -3.0 to 1.3). For 40 ppb higher NOX, the estimate was 0.2 μm per year (-1.9 to 2.4). Increased concentrations of PM2.5 and traffic-related air pollution within metropolitan areas, in ranges commonly encountered worldwide, are associated with progression in coronary calcification, consistent with acceleration of atherosclerosis. This study supports the case for global efforts of pollution reduction in prevention of cardiovascular diseases. US Environmental Protection Agency and US National Institutes of Health.

Temporal and spatial variation in allocating annual traffic activity across an urban region and implications for air quality assessments

Patterns of traffic activity, including changes in the volume and speed of vehicles, vary over time and across urban areas and can substantially affect vehicle emissions of air pollutants. Time-resolved activity at the street scale typically is derived using temporal allocation factors (TAFs) that allow the development of emissions inventories needed to predict concentrations of traffic-related air pollutants. This study examines the spatial and temporal variation of TAFs, and characterizes prediction errors resulting from their use. Methods are presented to estimate TAFs and their spatial and temporal variability and used to analyze total, commercial and non-commercial traffic in the Detroit, Michigan, U.S. metropolitan area. The variability of total volume estimates, quantified by the coefficient of variation (COV) representing the percentage departure from expected hourly volume, was 21%, 33%, 24% and 33% for weekdays, Saturdays, Sundays and holidays, respectively. Prediction errors mostly resulted from hour-to-hour variability on weekdays and Saturdays, and from day-to-day variability on Sundays and holidays. Spatial variability was limited across the study roads, most of which were large freeways. Commercial traffic had different temporal patterns and greater variability than non-commercial vehicle traffic, e.g., the weekday variability of hourly commercial volume was 28%. The results indicate that TAFs for a metropolitan region can provide reasonably accurate estimates of hourly vehicle volume on major roads. While vehicle volume is only one of many factors that govern on-road emission rates, air quality analyses would be strengthened by incorporating information regarding the uncertainty and variability of traffic activity.

Can changing the timing of outdoor air intake reduce indoor concentrations of traffic-related pollutants in schools?

Traffic emissions have been associated with a wide range of adverse health effects. Many schools are situated close to major roads, and as children spend much of their day in school, methods to reduce traffic-related air pollutant concentrations in the school environment are warranted. One promising method to reduce pollutant concentrations in schools is to alter the timing of the ventilation so that high ventilation time periods do not correspond to rush hour traffic. Health Canada, in collaboration with the Ottawa-Carleton District School Board, tested the effect of this action by collecting traffic-related air pollution data from four schools in Ottawa, Canada, during October and November 2013. A baseline and intervention period was assessed in each school. There were statistically significant (P<0.05) reductions in concentrations of most of the pollutants measured at the two late-start (9 AM start) schools, after adjusting for outdoor concentrations and the absolute indoor-outdoor temperature difference. The intervention at the early-start (8 AM start) schools did not have significant reductions in pollutant concentrations. Based on these findings, changing the timing of the ventilation may be a cost-effective mechanism of reducing traffic-related pollutants in late-start schools located near major roads.

Temporal variation of traffic on highways and the development of accurate temporal allocation factors for air pollution analyses

Traffic activity encompasses the number, mix, speed and acceleration of vehicles on roadways. The temporal pattern and variation of traffic activity reflects vehicle use, congestion and safety issues, and it represents a major influence on emissions and concentrations of traffic-related air pollutants. Accurate characterization of vehicle flows is critical in analyzing and modeling urban and local-scale pollutants, especially in near-road environments and traffic corridors. This study describes methods to improve the characterization of temporal variation of traffic activity. Annual, monthly, daily and hourly temporal allocation factors (TAFs), which describe the expected temporal variation in traffic activity, were developed using four years of hourly traffic activity data recorded at 14 continuous counting stations across the Detroit, Michigan, U.S. region. Five sites also provided vehicle classification. TAF-based models provide a simple means to apportion annual average estimates of traffic volume to hourly estimates. The analysis shows the need to separate TAFs for total and commercial vehicles, and weekdays, Saturdays, Sundays and observed holidays. Using either site-specific or urban-wide TAFs, nearly all of the variation in historical traffic activity at the street scale could be explained; unexplained variation was attributed to adverse weather, traffic accidents and construction. The methods and results presented in this paper can improve air quality dispersion modeling of mobile sources, and can be used to evaluate and model temporal variation in ambient air quality monitoring data and exposure estimates.

Risk of bronchi obstruction among non-smokers—Review of environmental factors affecting bronchoconstriction

In order to find relationship between exposure to traffic and traffic-related air pollutants, pulmonary function tests and a detailed questionnaire were conducted among 3997 selected inhabitants of Warsaw (Poland) and 988 residents of rural areas. Advanced statistical analyses (including GRM models, correspondence analysis and parametrical tests) have been completed.Statistically significant differences between average percentages of predicted values of pulmonary function parameters were found. Among urban area inhabitants the values of FEV1, MEF50 and FEV1/FVC were statistically significant (p<0.05) lower compared with the residents of rural areas (in the non-smoking group this differences were strong (p<0.001)). General linear regression models indicated that residence in the vicinity of urban busy roads fosters a decrease of spirometric parameters. Physical activity however has a positive effect on pulmonary function (exemplified by FEV1) and allows to reduce part of the negative health effects of traffic-related emissions.The results of the presented study demonstrate that long-term residence under the influence of heavy traffic and high concentrations of traffic-related air pollutants reduces respiratory function parameters, which may result in increased bronchial hyperresponsiveness.

Spatial and temporal differences in traffic-related air pollution in three urban neighborhoods near an interstate highway

Relatively few studies have characterized differences in intra- and inter-neighborhood traffic-related air pollutant (TRAP) concentrations and distance-decay gradients in neighborhoods along an urban highway for the purposes of exposure assessment. The goal of this work was to determine the extent to which intra- and inter-neighborhood differences in TRAP concentrations can be explained by traffic and meteorology in three pairs of neighborhoods along Interstate 93 (I-93) in the metropolitan Boston area (USA). We measured distance-decay gradients of seven TRAPs (PNC, pPAH, NO, NOX, BC, CO, PM2.5) in near-highway (<400 m) and background areas (>1 km) in Somerville, Dorchester/South Boston, Chinatown and Malden to determine whether (1) spatial patterns in concentrations and inter-pollutant correlations differ between neighborhoods, and (2) variation within and between neighborhoods can be explained by traffic and meteorology. The neighborhoods ranged in area from 0.5 to 2.3 km2. Mobile monitoring was performed over the course of one year in each pair of neighborhoods (one pair of neighborhoods per year in three successive years; 35–47 days of monitoring in each neighborhood). Pollutant levels generally increased with highway proximity, consistent with I-93 being a major source of TRAP; however, the slope and extent of the distance-decay gradients varied by neighborhood as well as by pollutant, season and time of day. Spearman correlations among pollutants differed between neighborhoods (e.g., ρ = 0.35–0.80 between PNC and NOX and ρ = 0.11–0.60 between PNC and BC) and were generally lower in Dorchester/South Boston than in the other neighborhoods. We found that the generalizability of near-road gradients and near-highway/urban background contrasts was limited for near-highway neighborhoods in a metropolitan area with substantial local street traffic. Our findings illustrate the importance of measuring gradients of multiple pollutants under different ambient conditions in individual near-highway neighborhoods for health studies involving inter-neighborhood comparisons.

Spatial resolution requirements for traffic-related air pollutant exposure evaluations

Vehicle emissions represent one of the most important air pollution sources in most urban areas, and elevated concentrations of pollutants found near major roads have been associated with many adverse health impacts. To understand these impacts, exposure estimates should reflect the spatial and temporal patterns observed for traffic-related air pollutants. This paper evaluates the spatial resolution and zonal systems required to estimate accurately intraurban and near-road exposures of traffic-related air pollutants. The analyses use the detailed information assembled for a large (800 km2) area centered on Detroit, Michigan, USA. Concentrations of nitrogen oxides (NOx) due to vehicle emissions were estimated using hourly traffic volumes and speeds on 9700 links representing all but minor roads in the city, the MOVES2010 emission model, the RLINE dispersion model, local meteorological data, a temporal resolution of 1 h, and spatial resolution as low as 10 m. Model estimates were joined with the corresponding shape files to estimate residential exposures for 700,000 individuals at property parcel, census block, census tract, and ZIP code levels. We evaluate joining methods, the spatial resolution needed to meet specific error criteria, and the extent of exposure misclassification. To portray traffic-related air pollutant exposure, raster or inverse distance-weighted interpolations are superior to nearest neighbor approaches, and interpolations between receptors and points of interest should not exceed about 40 m near major roads, and 100 m at larger distances. For census tracts and ZIP codes, average exposures are overestimated since few individuals live very near major roads, the range of concentrations is compressed, most exposures are misclassified, and high concentrations near roads are entirely omitted. While smaller zones improve performance considerably, even block-level data can misclassify many individuals. To estimate exposures and impacts of traffic-related pollutants accurately, data should be geocoded or estimated at the most-resolved spatial level; census tract and larger zones have little if any ability to represent intraurban variation in traffic-related air pollutant concentrations. These results are based on one of the most comprehensive intraurban modeling studies in the literature and results are robust. Additional recommendations address the value of dispersion models to portray spatial and temporal variation of air pollutants in epidemiology and other studies; techniques to improve accuracy and reduce the computational burden in urban scale modeling; the necessary spatial resolution for health surveillance, demographic, and pollution data; and the consequences of low resolution data in terms of exposure misclassification.

Long-term exposure to traffic-related air pollution and progression of carotid artery atherosclerosis: a prospective cohort study

ObjectivesEpidemiological studies have demonstrated associations between long-term exposure to traffic-related air pollution and coronary heart disease (CHD). Atherosclerosis is the principal pathological process responsible for CHD events, but effects of...

Residential Traffic Exposure and Childhood Leukemia

Exposure to elevated concentrations of traffic-related air pollutants in the near-road environment is associated with numerous adverse human health effects, including childhood cancer, which has been increasing since 1975. Results of individual epidemiologic studies have been inconsistent. Therefore, a meta-analysis was performed to examine the association between residential traffic exposure and childhood cancer. Studies published between January 1980 and July 2011 were retrieved from a systematic search of 18 bibliographic databases. Nine studies meeting the inclusion criteria were identified. Weighted summary ORs were calculated using a random effects model for outcomes with four or more studies. Subgroup and sensitivity analyses were performed. Childhood leukemia was positively associated (summary OR=1.53, 95% CI=1.12, 2.10) with residential traffic exposure among seven studies using a postnatal exposure window (e.g., childhood period or diagnosis address) and there was no association (summary OR=0.92, 95% CI=0.78, 1.09) among four studies using a prenatal exposure window (e.g., pregnancy period or birth address). There were too few studies to analyze other childhood cancer outcomes. Current evidence suggests that childhood leukemia is associated with residential traffic exposure during the postnatal period, but not during the prenatal period. Additional well-designed epidemiologic studies that use complete residential history to estimate traffic exposure, examine leukemia subtypes, and control for potential confounding factors are needed to confirm these findings. As many people reside near busy roads, especially in urban areas, precautionary public health messages and interventions designed to reduce population exposure to traffic might be warranted.

Implementation of a low emission zone and evaluation of effects on air quality by long-term monitoring

A regulation was implemented on 9/1/2009, excluding Euro 0, I and II heavy duty vehicles from entering Amsterdam's Low Emission Zone (LEZA). The current study investigated whether and to what extent this regulation had an effect on air quality. Data for a period starting two years before the regulation up to 31 December 2010 were obtained from two monitoring sites within the LEZA, one located in a street frequently used by heavy-duty vehicles, and one at an urban background location. The difference in concentrations of NO2, NOx, PM10 and soot, between the two sites was attributed to traffic. Soot was measured by two proxies, Elemental Carbon (EC) and Absorbance that showed a significant mutual correlation. The traffic contribution concentrations measured were adjusted for wind direction, wind speed, type of day (weekday/weekend) and traffic intensity. Since the implementation of the LEZA, the traffic contribution concentrations compared to the roadside site concentrations were decreased by 4.9% (95%-CI: 3.0–6.9%) for NO2, 5.9% (95%-CI: 3.7–6.4%) for NOx, 5.8% (95%-CI: 3.3–8.4%) for PM10, 7.7% (95%-CI: 2.3–13.0%) for Absorbance and 12.9% (95%-CI: 5.2–20.5%) for EC. The current study demonstrated significant decreases in traffic-related air pollution concentrations in the vicinity of a roadside monitoring station after the implementation of a low emission zone in Amsterdam.

Modeling the Concentrations of On-Road Air Pollutants in Southern California

High concentrations of air pollutants on roadways, relative to ambient concentrations, contribute significantly to total personal exposure. Estimation of these exposures requires measurements or prediction of roadway concentrations. Our study develops, compares, and evaluates linear regression and nonlinear generalized additive models (GAMs) to estimate on-road concentrations of four key air pollutants, particle-bound polycyclic aromatic hydrocarbons (PB-PAH), particle number count (PNC), nitrogen oxides (NOx), and particulate matter with diameter <2.5 μm (PM2.5) using traffic, meteorology, and elevation variables. Critical predictors included wind speed and direction for all the pollutants, traffic-related variables for PB-PAH, PNC, and NOx, and air temperatures and relative humidity for PM2.5. GAMs explained 50%, 55%, 46%, and 71% of the variance for log or square-root transformed concentrations of PB-PAH, PNC, NOx, and PM2.5, respectively, an improvement of 5% to over 15% over the linear models. Accounting for temporal autocorrelation in the GAMs further improved the prediction, explaining 57-89% of the variance. We concluded that traffic and meteorological data are good predictors in estimating on-road traffic-related air pollutant concentrations and GAMs perform better for nonlinear variables, such as meteorological parameters.