Characterization of Near-Road Pollutant Gradients Using Path-Integrated Optical Remote Sensing

Abstract

Understanding motor vehicle emissions, near-roadway pollutant dispersion, and their potential impact to near-roadway populations is an area of growing environmental interest. As part of ongoing U.S. Environmental Protection Agency research in this area, a field study was conducted near Interstate 440 (I-440) in Raleigh, NC, in July and August of 2006. This paper presents a subset of measurements from the study focusing on nitric oxide (NO) concentrations near the roadway. Measurements of NO in this study were facilitated by the use of a novel path-integrated optical remote sensing technique called deep ultraviolet differential optical absorption spectroscopy (DUV-DOAS). This paper reviews the development and application of this measurement system. Time-resolved near-road NO concentrations are analyzed in conjunction with wind and traffic data to provide a picture of emissions and near-road dispersion for the study. Results show peak NO concentrations in the 150 ppb range during weekday morning rush hours with winds from the road accompanied by significantly lower afternoon and weekend concentrations. Traffic volume and wind direction are shown to be primary determinants of NO concentrations with turbulent diffusion and meandering accounting for significant near-road concentrations in off-wind conditions. The enhanced source capture performance of the open-path configuration allowed for robust comparisons of measured concentrations with a composite variable of traffic intensity coupled with wind transport (R² = 0.84) as well as investigations on the influence of wind direction on NO dilution near the roadway. The benefits of path-integrated measurements for assessing line source impacts and evaluating models is presented. The advantages of NO as a tracer compound, compared with nitrogen dioxide, for investigations of mobile source emissions and initial dispersion under crosswind conditions are also discussed.     

Traffic and Meteorological Impacts on Near-Road Air Quality: Summary of Methods and Trends from the Raleigh Near-Road Study

Abstract

A growing number of epidemiological studies conducted worldwide suggest an increase in the occurrence of adverse health effects in populations living, working, or going to school near major roadways. A study was designed to assess traffic emissions impacts on air quality and particle toxicity near a heavily traveled highway. In an attempt to describe the complex mixture of pollutants and atmospheric transport mechanisms affecting pollutant dispersion in this near-highway environment, several real-time and time-integrated sampling devices measured air quality concentrations at multiple distances and heights from the road. Pollutants analyzed included U.S. Environmental Protection Agency (EPA)-regulated gases, particulate matter (coarse, fine, and ultrafine), and air toxics. Pollutant measurements were synchronized with real-time traffic and meteorological monitoring devices to provide continuous and integrated assessments of the variation of near-road air pollutant concentrations and particle toxicity with changing traffic and environmental conditions, as well as distance from the road. Measurement results demonstrated the temporal and spatial impact of traffic emissions on near-road air quality. The distribution of mobile source emitted gas and particulate pollutants under all wind and traffic conditions indicated a higher proportion of elevated concentrations near the road, suggesting elevated exposures for populations spending significant amounts of time in this microenvironment. Diurnal variations in pollutant concentrations also demonstrated the impact of traffic activity and meteorology on near-road air quality. Time-resolved measurements of multiple pollutants demonstrated that traffic emissions produced a complex mixture of criteria and air toxic pollutants in this microenvironment. These results provide a foundation for future assessments of these data to identify the relationship of traffic activity and meteorology on air quality concentrations and population exposures.     

Traffic and meteorological impacts on near-road air quality: summary of methods and trends from the Raleigh Near-Road Study

A growing number of epidemiological studies conducted worldwide suggest an increase in the occurrence of adverse health effects in populations living, working, or going to school near major roadways. A study was designed to assess traffic emissions impacts on air quality and particle toxicity near a heavily traveled highway. In an attempt to describe the complex mixture of pollutants and atmospheric transport mechanisms affecting pollutant dispersion in this near-highway environment, several real-time and time-integrated sampling devices measured air quality concentrations at multiple distances and heights from the road. Pollutants analyzed included U.S. Environmental Protection Agency (EPA)-regulated gases, particulate matter (coarse, fine, and ultrafine), and air toxics. Pollutant measurements were synchronized with real-time traffic and meteorological monitoring devices to provide continuous and integrated assessments of the variation of near-road air pollutant concentrations and particle toxicity with changing traffic and environmental conditions, as well as distance from the road. Measurement results demonstrated the temporal and spatial impact of traffic emissions on near-road air quality. The distribution of mobile source emitted gas and particulate pollutants under all wind and traffic conditions indicated a higher proportion of elevated concentrations near the road, suggesting elevated exposures for populations spending significant amounts of time in this microenvironment. Diurnal variations in pollutant concentrations also demonstrated the impact of traffic activity and meteorology on near-road air quality. Time-resolved measurements of multiple pollutants demonstrated that traffic emissions produced a complex mixture of criteria and air toxic pollutants in this microenvironment. These results provide a foundation for future assessments of these data to identify the relationship of traffic activity and meteorology on air quality concentrations and population exposures.     

Analysis of air quality data near roadways using a dispersion model

We used a dispersion model to analyze measurements made during a field study conducted by the U.S. EPA in July–August 2006, to estimate the impact of traffic emissions on air quality at distances of tens of meters from an eight-lane highway located in Raleigh, NC. The air quality measurements consisted of long path optical measurements of NO at distances of 7 and 17 m from the edge of the highway. Sonic anemometers were used to measure wind speed and turbulent velocities at 6 and 20 m from the highway. Traffic flow rates were monitored using traffic surveillance cameras. The dispersion model [Venkatram, A., 2004. On estimating emissions through horizontal fluxes. Atmospheric Environment 38, 2439–2446] explained over 60% of the variance of the observed path averaged NO concentrations, and over 90% of the observed concentrations were within a factor of two of the model estimates.Sensitivity tests conducted with the model indicated that the traffic flow rate made the largest contribution to the variance of the observed NO concentrations. The meteorological variable that had the largest impact on the near road NO concentrations was the standard deviation of the vertical velocity fluctuations, σ_w. Wind speed had a relatively minor effect on concentrations. Furthermore, as long as the wind direction was within ±45° from the normal to the road, wind direction had little impact on near road concentrations. The measurements did not allow us to draw conclusions on the impact of traffic-induced turbulence on dispersion. The analysis of air quality and meteorological observations resulted in plausible estimates of on-road emission factors for NO.     

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.     

A wind tunnel study of the effect of roadway configurations on the dispersion of traffic-related pollution

In this paper we examine the effect of different roadway configurations, including noise barriers and roadway elevation or depression relative to the surrounding terrain, on the dispersion of traffic-related pollutants for winds perpendicular to the roadway. A wind tunnel experiment modeling 12 different configurations was performed to study the flow fields and the concentration distributions resulting from emissions from a simulated six-lane highway. All of the configurations examined here reduced the downwind ground-level concentrations relative to that for a flat, unobstructed roadway; however, the degree to which the concentrations were reduced varied widely depending on the particular situation.Ground-level concentration data from the cases considered in this research indicate that a constant entrainment velocity can be used over the region beginning downwind of any initial disturbance to the flow resulting from the roadway configuration (e.g., a recirculation region behind a noise barrier) and extending at least to the end of our measurements. For example, for the case of a single noise barrier on the downwind side of the road, this region extends from approximately four barrier heights downwind of the roadway to 40 barrier heights. It was also found that the virtual origin concept is useful in describing the initial mixing created by the particular roadway configuration. To effectively model the influence of the roadway configuration on the dispersion, a combination of a virtual origin and an entrainment velocity may be effective. The magnitude of the virtual origin shift appears to depend on the particular roadway configuration, while the entrainment velocity appears to be a function of the friction velocity and the roadway geometry. These results suggest that road configuration must be taken into account in modeling near-road air quality.     

Monitoring study of the near-road PM2.5 concentrations in Maryland

The Maryland State Highway Administration (SHA) monitoring program monitored the impact of vehicular emissions on the concentrations of the fine particles smaller than 2.5 microns (PM2.5). PM2.5 concentrations were monitored in close proximity to a highway in order to determine whether traffic conditions on the roadway impact concentrations at this location. The monitoring program attempted to connect monitored concentrations with the roadway traffic exhaust or with the other sources of PM2.5. PM2.5 concentrations were collected near the Capital Beltway (I-495/I-95) in Largo, Maryland. The monitoring program was launched on May 13, 2009 and continued through the end of 2012. Two co-located monitors, one for continuous PM2.5 measurements and the other for speciation measurements, were used in this program. Meteorological and traffic information was also continuously collected at or near the monitoring site. Additionally, data from the two other monitoring locations, one at the Howard University-Beltsville, MD and one at McMillan Reservoir, DC, was used for comparison with the data collected at the SHA monitoring location. The samples collected by the speciation monitor were analyzed at the RTI and DRI Laboratories to determine the composition and the sources of the collected PM2.5 samples. Based on the apportionment analysis, the contribution of roadway sources is about 12 to 17 percent of PM2.5 at the near-road site.

Implications: PM_2.5 monitoring at 150 m (approximately 500 feet) from a major highway in Maryland near Washington, DC, demonstrated that roadway traffic contributes to the total PM_2.5 concentration near the roadway, but the contribution at such distance is small, in the order of 12–17% of the total.     

Near-roadway monitoring of vehicle emissions as a function of mode of operation for light-duty vehicles

Determination of the effect of vehicle emissions on air quality near roadways is important because vehicles are a major source of air pollution. A near-roadway monitoring program was undertaken in Chicago between August 4 and October 30, 2014, to measure ultrafine particles, carbon dioxide, carbon monoxide, traffic volume and speed, and wind direction and speed. The objective of this study was to develop a method to relate short-term changes in traffic mode of operation to air quality near roadways using data averaged over 5-min intervals to provide a better understanding of the processes controlling air pollution concentrations near roadways. Three different types of data analysis are provided to demonstrate the type of results that can be obtained from a near-roadway sampling program based on 5-min measurements: (1) development of vehicle emission factors (EFs) for ultrafine particles as a function of vehicle mode of operation, (2) comparison of measured and modeled CO₂ concentrations, and (3) application of dispersion models to determine concentrations near roadways. EFs for ultrafine particles are developed that are a function of traffic volume and mode of operation (free flow and congestion) for light-duty vehicles (LDVs) under real-world conditions. Two air quality models—CALINE4 (California Line Source Dispersion Model, version 4) and AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model)—are used to predict the ultrafine particulate concentrations near roadways for comparison with measured concentrations. When using CALINE4 to predict air quality levels in the mixing cell, changes in surface roughness and stability class have no effect on the predicted concentrations. However, when using AERMOD to predict air quality in the mixing cell, changes in surface roughness have a significant impact on the predicted concentrations.

Implications: The paper provides emission factors (EFs) that are a function of traffic volume and mode of operation (free flow and congestion) for LDVs under real-world conditions. The good agreement between monitoring and modeling results indicates that high-resolution, simultaneous measurements of air quality and meteorological and traffic conditions can be used to determine real-world, fleet-wide vehicle EFs as a function of vehicle mode of operation under actual driving conditions.     

Air pollutant concentrations near three Texas roadways,Part I: Ultrafine particles

Vehicular emitted air pollutant concentrations were studied near three types of roadways in Austin, Texas: (1) State Highway 71 (SH-71), a heavily traveled arterial highway dominated by passenger vehicles; (2) Interstate 35 (I-35), a limited access highway north of Austin in Georgetown; and (3) Farm to Market Road 973 (FM-973), a heavily traveled surface roadway dominated by truck traffic. Air pollutants examined include carbon monoxide (CO), oxides of nitrogen (NO_x), and carbonyl species in the gas-phase. In the particle phase, ultrafine particle (UFP) concentrations (diameter < 100 nm), fine particulate matter (PM_2.5, diameter < 2.5 μm) mass and carbon content and several particle-bound organics were examined. All roadways had an upwind stationary sampling location, one or two fixed downwind sample locations and a mobile monitoring platform that characterized pollutant concentrations fall-off with increased distance from the roadways. Data reported in this paper focus on UFP while other pollutants and near-roadway chemical processes are examined in a companion paper. Traffic volume, especially heavy-duty traffic, wind speed, and proximity to the road were found to be the most important factors determining UFP concentrations near the roadways. Since wind directions were not consistent during the sampling periods, distances along wind trajectories from the roadway to the sampling points were used to study the decay characteristics of UFPs. Under perpendicular wind conditions, for all studied roadway types, particle number concentrations increased dramatically moving from the upwind side to the downwind side. The elevated particle number concentrations decay exponentially with increasing distances from the roadway with sharp concentration gradients observed within 100–150 m, similar to previously reported studies. A single exponential decay curve was found to fit the data collected from all three roadways very well under perpendicular wind conditions. No consistent pattern was observed for UFPs under parallel wind conditions. However, regardless of wind conditions, particle concentrations returned to background levels within a few hundred meters of the roadway. Within measured UFP size ranges, smaller particles (6–25 nm) decayed faster than larger ones (100–300 nm). Similar decay rates were observed among UFP number, surface, and volume.     

Modeling the impacts of traffic emissions on air toxics concentrations near roadways

The dispersion formulation incorporated in the U.S. Environmental Protection Agency's AERMOD regulatory dispersion model is used to estimate the contribution of traffic-generated emissions of select VOCs – benzene, 1,3-butadiene, toluene – to ambient air concentrations at downwind receptors ranging from 10-m to 100-m from the edge of a major highway in Raleigh, North Carolina. The contributions are computed using the following steps: 1) Evaluate dispersion model estimates with 10-min averaged NO data measured at 7 m and 17 m from the edge of the road during a field study conducted in August, 2006; this step determines the uncertainty in model estimates. 2) Use dispersion model estimates and their uncertainties, determined in step 1, to construct pseudo-observations. 3) Fit pseudo-observations to actual observations of VOC concentrations measured during five periods of the field study. This provides estimates of the contributions of traffic emissions to the VOC concentrations at the receptors located from 10 m to 100 m from the road. In addition, it provides estimates of emission factors and background concentrations of the VOCs, which are supported by independent estimates from motor vehicle emissions models and regional air quality measurements. The results presented in the paper demonstrate the suitability of the formulation in AERMOD for estimating concentrations associated with mobile source emissions near roadways. This paper also presents an evaluation of the key emissions and dispersion modeling inputs necessary for conducting assessments of local-scale impacts from traffic emissions.     

Tracer studies to characterize the effects of roadside noise barriers on near-road pollutant dispersion under varying atmospheric stability conditions

A roadway toxics dispersion study was conducted at the Idaho National Laboratory (INL) to document the effects on concentrations of roadway emissions behind a roadside sound barrier in various conditions of atmospheric stability. The homogeneous fetch of the INL, controlled emission source, lack of other manmade or natural flow obstructions, and absence of vehicle-generated turbulence reduced the ambiguities in interpretation of the data. Roadway emissions were simulated by the release of an atmospheric tracer (SF₆) from two 54 m long line sources, one for an experiment with a 90 m long noise barrier and one for a control experiment without a barrier. Simultaneous near-surface tracer concentration measurements were made with bag samplers on identical sampling grids downwind from the line sources. An array of six 3-d sonic anemometers was employed to measure the barrier-induced turbulence. Key findings of the study are: (1) the areal extent of higher concentrations and the absolute magnitudes of the concentrations both increased as atmospheric stability increased; (2) a concentration deficit developed in the wake zone of the barrier with respect to concentrations at the same relative locations on the control experiment at all atmospheric stabilities; (3) lateral dispersion was significantly greater on the barrier grid than the non-barrier grid; and (4) the barrier tended to trap high concentrations near the “roadway” (i.e. upwind of the barrier) in low wind speed conditions, especially in stable conditions.     

Localizing Gaseous Fugitive Emission Sources by Combining Real-Time Optical Remote Sensing and Wind Data

ABSTRACT

This paper presents a new approach to localize point emissions from ground-level fugitive gaseous air pollution sources. We estimate the crosswind plume's ground-level peak location downwind from the source by combining smooth basis functions minimization (SBFM) with path-integrated optical remote sensing concentration data acquired along the crosswind direction in alternating beam path lengths. Peak location estimates, in conjunction with real-time measured wind direction data, are used to reconstruct the fugitive source location. We conducted a synthetic data study to evaluate the proposed peak location SBFM reconstruction. Furthermore, the methodology was validated with open-path Fourier transform infrared concentration data collected with wind direction data downwind from a controlled point source. This approach was found to provide reasonable estimates of point source location. The field study reconstructed source location was within several meters of the real source location.     

A Method of Predicting Point and Path- Averaged Ambient Air VOC Concentrations,Using Meteorological Data

A method of predicting point and path-averaged ambient air VOC concentrations is described. This method was developed for the case of a plume generated from a single point source, and is based on the relationship between wind directional frequency and concentration. One-minute means of wind direction and wind speed were used as inputs to a Gaussian dispersion model to develop this relationship.

Both FTIR spectrometry and a whole-air sampling method were used to monitor VOC plumes during simulated field tests. One test set was also conducted using only whole-air samplers deployed in a closely-spaced network, thus providing an evaluation of the prediction technique free of any bias that might exist between the two analytical methods.

Correlations between observed point concentrations and wind directional frequencies were significant at the 0.05 level in most cases. Predicted path-integrated concentrations, based on observed point concentrations and meteorological data, were strongly correlated with observed values. Predicted point concentrations, based on observed path-integrated concentrations and meteorological data, accurately reflected the location and magnitude of the highest concentrations from each test, as well as the shape of the concentration-versus-crosswind distance curve.     

Near-road air pollutant concentrations of CO and PM2.5: A comparison of MOBILE6.2/CALINE4 and generalized additive models

The contribution of vehicular traffic to air pollutant concentrations is often difficult to establish. This paper utilizes both time-series and simulation models to estimate vehicle contributions to pollutant levels near roadways. The time-series model used generalized additive models (GAMs) and fitted pollutant observations to traffic counts and meteorological variables. A one year period (2004) was analyzed on a seasonal basis using hourly measurements of carbon monoxide (CO) and particulate matter less than 2.5 μm in diameter (PM_2.5) monitored near a major highway in Detroit, Michigan, along with hourly traffic counts and local meteorological data. Traffic counts showed statistically significant and approximately linear relationships with CO concentrations in fall, and piecewise linear relationships in spring, summer and winter. The same period was simulated using emission and dispersion models (Motor Vehicle Emissions Factor Model/MOBILE6.2; California Line Source Dispersion Model/CALINE4). CO emissions derived from the GAM were similar, on average, to those estimated by MOBILE6.2. The same analyses for PM_2.5 showed that GAM emission estimates were much higher (by 4–5 times) than the dispersion model results, and that the traffic-PM_2.5 relationship varied seasonally. This analysis suggests that the simulation model performed reasonably well for CO, but it significantly underestimated PM_2.5 concentrations, a likely result of underestimating PM_2.5 emission factors. Comparisons between statistical and simulation models can help identify model deficiencies and improve estimates of vehicle emissions and near-road air quality.     

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.     

Road traffic impact on urban water quality: a step towards integrated traffic,air and stormwater modelling

Methods for simulating air pollution due to road traffic and the associated effects on stormwater runoff quality in an urban environment are examined with particular emphasis on the integration of the various simulation models into a consistent modelling chain. To that end, the models for traffic, pollutant emissions, atmospheric dispersion and deposition, and stormwater contamination are reviewed. The present study focuses on the implementation of a modelling chain for an actual urban case study, which is the contamination of water runoff by cadmium (Cd), lead (Pb), and zinc (Zn) in the Grigny urban catchment near Paris, France. First, traffic emissions are calculated with traffic inputs using the COPERT4 methodology. Next, the atmospheric dispersion of pollutants is simulated with the Polyphemus line source model and pollutant deposition fluxes in different subcatchment areas are calculated. Finally, the SWMM water quantity and quality model is used to estimate the concentrations of pollutants in stormwater runoff. The simulation results are compared to mass flow rates and concentrations of Cd, Pb and Zn measured at the catchment outlet. The contribution of local traffic to stormwater contamination is estimated to be significant for Pb and, to a lesser extent, for Zn and Cd; however, Pb is most likely overestimated due to outdated emissions factors. The results demonstrate the importance of treating distributed traffic emissions from major roadways explicitly since the impact of these sources on concentrations in the catchment outlet is underestimated when those traffic emissions are spatially averaged over the catchment area.     

Wind Tunnel Modelling of Roadways: Comparison with Mathematical Models

The assessment of air quality impacts from roadways is a major concern to urban planners. In order to assess future road and building configurations, a number of techniques have been developed, including mathematical models, which simulate traffic emissions and atmospheric dispersion through a series of mathematical relationships and physical models. The latter models simulate emissions and dispersion through scaling of these processes in a wind tunnel. Two roadway mathematical models, HIWAY-2 and CALINE-4, were applied to a proposed development in a large urban area. Physical modelling procedures developed by Rowan Williams Davies & Irwin Inc. (RWDI) in the form of line source simulators were also applied, and the resulting carbon monoxide concentrations were compared. The results indicated a factor of two agreement between the mathematical and physical models. The physical model, however, reacted to changes in building massing and configuration. The mathematical models did not, since no provision for such changes was included in the mathematical models. In general, the RWDI model resulted in higher concentrations than either HIWAY-2 or CALINE-4. Where there was underprediction, it was often due to shielding of the receptor by surrounding buildings. Comparison of these three models with the CALTRANS Tracer Dispersion Experiment showed good results although concentrations were consistently underpredicted.     

Air pollutant concentrations near three Texas roadways, part II: Chemical characterization and transformation of pollutants

Spatial gradients of vehicular emitted air pollutants were measured in the vicinity of three roadways in the Austin, Texas area: (1) State Highway 71 (SH-71), a heavily traveled arterial highway dominated by passenger vehicles; (2) Interstate 35 (I-35), a limited access highway north of Austin in Georgetown; and (3) Farm to Market Road 973 (FM-973), a heavily traveled surface roadway with significant truck traffic. A mobile monitoring platform was used to characterize the gradients of CO and NO_x concentrations with increased distance from each roadway, while concentrations of carbonyls in the gas-phase and fine particulate matter mass and composition were measured at stationary sites upwind and at one (I-35 and FM-973) or two (SH-71) downwind sites. Regardless of roadway type or wind direction, concentrations of carbon monoxide (CO), nitric oxide (NO), and oxides of nitrogen (NO_x) returned to background levels within a few hundred meters of the roadway. Under perpendicular wind conditions, CO, NO and NO_x concentrations decreased exponentially with increasing distance perpendicular to the roadways. The decay rate for NO was more than a factor of two greater than for CO, and it comprised a larger fraction of NO_x closer to the roadways than further downwind suggesting the potential significance of near roadway chemical processing as well as atmospheric dilution. Concentrations of most carbonyl species decreased with distance downwind of SH-71. However, concentrations of acetaldehyde and acrolein increased farther downwind of SH-71, suggesting chemical generation from the oxidation of primary vehicular emissions. The behavior of particle-bound organic species was complex and further investigation of the size-segregated chemical composition of particulate matter (PM) at increasing downwind distances from roadways is warranted. Fine particulate matter (PM_2.5) mass concentrations, polycyclic aromatic hydrocarbons (PAHs), hopanes, and elemental carbon (EC) concentrations generally exhibited concentrations that decreased with distance downwind of SH-71. Concentrations of organic carbon (OC) increased from upwind concentrations immediately downwind of SH-71 and continued to increase further downwind from the roadway. This behavior may have primarily resulted from condensation of semi-volatile organic species emitted from vehicle sources with transport downwind of the roadway.     

Turbulent Diffusion Behind Vehicles: Effect of Traffic Speed on Pollutant Concentrations

Recent theoretical and experimental investigations Indicate that turbulent diffusion behind moving vehicles Is Influenced by the speed of the vehicle. Vertical wake induced turbulent diffusion, explicitly treated in the numerical ROADWAY model, is proportional to the square of the wind speed relative to the moving vehicle. Hence, the model predictions of turbulent mixing and pollutant concentrations on and downwind of a roadway are dependent upon the traffic speed. It Is expected from theoretical considerations that the effect of vehicle speed on pollutant concentrations will be more significant during stable atmospheric conditions, because in neutral and unstable conditions the vehicle-wake turbulence is quickly masked by the ambient turbulence. In this study, experimental data are utilized to evaluate the theoretical predictions of the effects of traffic speed on the ambient pollutant concentrations. The effects of vehicle speed upon ambient concentrations are investigated through wind tunnel experiments and field studies that used dual tracers. Consistent with predictions of the ROADWAY model, data obtained near the Long Island Expressway indicate that the influence of traffic speed on the ambient pollutant concentrations Is not significant during unstable and neutral conditions. The Long Island experiment did not provide sufficient field data to assess the model predictions of the traffic speed effect during stable atmospheric conditions.     

Changes in air quality at near-roadway schools after a major freeway expansion in Las Vegas,Nevada

Near-roadway ambient black carbon (BC) and carbon monoxide (CO) concentrations were measured at two schools adjacent to a freeway and at an urban background school 2 km from the freeway to determine the change in concentrations attributable to vehicle emissions after the three-lane expansion of U.S. Highway 95 (US 95) in Las Vegas, Nevada. Between summer 2007 and summer 2008, average weekday small-vehicle volume increased by 40% ± 2% (standard error). Average weekday large-vehicle volume decreased by 17% ± 5%, due to a downturn in the economy and an associated decline in goods movement. Average vehicle speed increased from 58 to 69 mph, a 16% ± 1% increase. The authors compared BC and CO concentrations in summer 2007 with those in summer 2008 to understand what effect the expansion of the freeway may have had on ambient concentrations: BC and CO were measured 17 m north of the freeway sound wall, CO was measured 20 m south of the sound wall, and BC was measured at an urban background site 2 km south of the freeway. Between summer 2007 and summer 2008, median BC decreased at the near-road site by 40% ± 2% and also decreased at the urban background site by 24% ± 4%, suggesting that much of the change was due to decreases in emissions throughout Las Vegas, rather than only on US 95. CO concentrations decreased by 14% ± 2% and 10% ± 3% at the two near-road sites. The decrease in BC concentrations after the expansion is likely due to the decrease in medium- and heavy-duty-vehicle traffic resulting from the economic recession. The decrease in CO concentrations may be a result of improved traffic flow, despite the increase in light-duty-vehicle traffic.

ImplicationsMonitoring of BC and CO at near-road locations in Las Vegas demonstrated the impacts of changes in traffic volume and vehicle speed on near-road concentrations. However, urban-scale declines in concentrations were larger than near-road changes due to the impacts of the economic recession that occurred contemporaneously with the freeway expansion.