Roadway Concentrations Research Articles

Spatiotemporal Modeling of Oxidative Potential of Ambient Particulate Matter Using Chemical Transport Model-Derived Emission Sources

Multiple epidemiologic studies have found associations between the oxidative potential (OP) of fine particulate matter (PM2.5) and adverse cardiorespiratory outcomes, supporting the hypothesis that PM may be capable of inducing oxidative stress. However, limited observational data on OP restrict the scope of exposure and epidemiologic analyses. Here, an advanced PM2.5 emission source impact analysis is used with limited OP observations to develop and apply a model capable of simulating daily OP over a wide spatial domain, specifically across the eastern United States. OP of ambient water-soluble PM2.5 was measured using an accellular dithiothreitol (DTT) assay at four locations across the southeastern United States from June 2012-July 2013. PM2.5 source apportionment was performed during the same time period across the eastern United States using CMAQ-DDM with advanced data assimilation techniques to minimize biases. These sources were related to ambient OP measurements using multivariate linear regression with backward selection. The resulting model was applied to estimate spatio-temporal trends in ambient OP across the eastern United States. Regression analyses show that vehicles and fires significantly contribute to OP, supporting previous findings. Higher OP is generally seen in the winter than the summer and in urban areas compared to rural areas. The intraurban spatial distribution driven by vehicle impacts was briefly investigated, showing a high spatial correlation with RLINE modeled primary roadway concentrations. The CMAQ-DDM modeling approach may be useful for health studies utilizing exposure data across a large study domain (e.g. multiple cities), can integrate a broad range of OP measurements, and can help to identify sources of PM with high OP for regulatory purposes. While this work was supported in part by a grant from the US EPA, this abstract does not necessarily reflect EPA policy.

Multi-pollutant mobile platform measurements of air pollutants adjacent to a major roadway

A mobile monitoring platform developed at the University of Washington Center for Clean Air Research (CCAR) measured 10 pollutant metrics (10 s measurements at an average speed of 22 km/h) in two neighborhoods bordering a major interstate in Albuquerque, NM, USA from April 18–24 2012. 5 days of data sharing a common downwind orientation with respect to the roadway were analyzed. The aggregate results show a three-fold increase in black carbon (BC) concentrations within 10 m of the edge of roadway, in addition to elevated nanoparticle concentration and particulate matter with aerodynamic diameter <1 μm (PN1) concentrations. A 30% reduction in ozone concentration near the roadway was observed, anti-correlated with an increase in the oxides of nitrogen (NOx). In this study, the pollutants measured have been expanded to include polycyclic aromatic hydrocarbons (PAH), particle size distribution (0.25–32 μm), and ultra-violet absorbing particulate matter (UVPM). The raster sampling scheme combined with spatial and temporal measurement alignment provide a measure of variability in the near roadway concentrations, and allow us to use a principal component analysis to identify multi-pollutant features and analyze their roadway influences.

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.

Linking in-vehicle ultrafine particle exposures to on-road concentrations

For traffic-related pollutants like ultrafine particles (UFP), a significant fraction of overall exposure occurs within or close to the transit microenvironment. Therefore, understanding exposure to these pollutants in such microenvironments is crucial to accurately assessing overall UFP exposure. The aim of this study was to develop models for predicting in-cabin UFP concentrations if roadway concentrations are known, quantifying the effect of vehicle characteristics, ventilation settings, driving conditions and air exchange rates (AER). Particle concentrations and AER were measured in 43 and 73 vehicles, respectively, under various ventilation settings and driving speeds. Multiple linear regression (MLR) and generalized estimating equation (GEE) regression models were used to identify and quantify the factors that determine inside-to-outside (I/O) UFP ratios and AERs across a full range of vehicle types and ages. AER was the most significant determinant of UFP I/O ratios, and was most strongly influenced by ventilation setting (recirculation or outside air intake). Further inclusion of ventilation fan speed, vehicle age or mileage, and driving speed explained greater than 79% of the variability in measured UFP I/O ratios.

Near roadway concentrations of organic source markers

Concentrations of elemental carbon (EC), organic carbon (OC), and 33 organic source markers (12 alkanes, 18 polycyclic aromatic hydrocarbons and ketones, and 3 hopanes) are reported near a highway in Raleigh, NC with an annual average daily traffic count of approximately 125,000 vehicles. Daily samples (24-h) were collected at two locations, one approximately 10 m and the other 275 m perpendicular from the road. Concentrations of OC were similar between near (mean = 7.6 μg m −3) and far (8.0 μg m −3) locations, but concentrations of most organic species at the near site were between 1.5 and 2 times higher than those at the far site.

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 squares 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. Average concentrations aboard school buses (21 μg 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 μg 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.

Characteristics of cabin air quality in school buses in Central Texas

This study assessed in-cabin concentrations of diesel-associated air pollutants in six school buses with diesel engines during a typical route in suburban Austin, Texas. Air exchange rates measured by SF 6 decay were 2.60–4.55 h −1. In-cabin concentrations of all pollutants measured exhibited substantial variability across the range of tests even between buses of similar age, mileage, and engine type. In-cabin NO x concentrations ranged from 44.7 to 148 ppb and were 1.3–10 times higher than roadway NO x concentrations. Mean in-cabin PM 2.5 concentrations were 7–20 μg m −3 and were generally lower than roadway levels. In-cabin concentrations exhibited higher variability during cruising mode than frequent stops. Mean in-cabin ultrafine PM number concentrations were 6100–32,000 particles cm −3 and were generally lower than roadway levels. Comparison of median concentrations indicated that in-cabin ultrafine PM number concentrations were higher than or approximately the same as the roadway concentrations, which implied that, by excluding the bias caused by local traffic, ultrafine PM levels were higher in the bus cabin than outside of the bus. Cabin pollutant concentrations on three buses were measured prior to and following the phased installation of a Donaldson Spiracle Crankcase Filtration System and a Diesel Oxidation Catalyst. Following installation of the Spiracle, the Diesel Oxidation Catalyst provided negligible or small additional reductions of in-cabin pollutant levels. In-cabin concentration decreases with the Spiracle alone ranged from 24 to 37% for NO x and 26 to 62% and 6.6 to 43% for PM 2.5 and ultrafine PM, respectively. Comparison of the ranges of PM 2.5 and ultrafine PM variations between repetitive tests suggested that retrofit installation could not always be conclusively linked to the decrease of pollutant levels in the bus cabin.

Concentrations of volatile organic compounds in the passenger side and the back seat of automobiles.

The in-vehicle volatile organic compound (VOC) concentrations during commutes have previously been measured in only one single interior sampling location, considering a sample collected in the single interior location as representative of overall VOC concentrations within an automobile. The present study evaluated if the potential differences in VOC concentrations occur in the automobiles' interior during idling and commuting under different driving conditions associated with the use of air cleaning devices (ACDs) and interior fan. The experiments were conducted under the low ventilation condition with the windows and the vent closed and the fan off. The difference of VOC concentrations between passenger side and back seat during idling was small. The variability of VOC concentrations with location inside automobiles while commuting was not significant at p < 0.05, regardless of the use of ACDs and/or the interior fan, while inter-vehicle variability was significant at p < 0.05. In addition, currently available ACDs equipped with activated carbon filters in Korea were ineffective at removing VOCs from the interior of automobiles. The concentrations of the two lightest ones of the target compounds, benzene and toluene, were significantly higher inside two vehicles than in the roadway air at p < 0.05, while the in-vehicle and roadway concentrations of the other target compounds did not differ significantly at p < 0.05 for both vehicles. The concentrations of all target VOCs, except benzene, were significantly higher (p < 0.05) in the interior of older car than of newer car. Median in-vehicle concentrations of benzene, toluene, ethylbenzene, p-xylene, m-xylene, and o-xylene were 38.3, 107, 9.2, 7.8, 16.9, and 10.7 micrograms/m3, respectively.