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Communities near transportation sources can be impacted by higher concentrations of particulate matter (PM) and other air pollutants. Few studies have reported on air quality in complex urban environments with multiple transportation sources. To better understand these environments, the Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS) was conducted in three neighborhoods in Southeast Kansas City, Kansas. This area has several emissions sources including transportation (railyards, vehicles, diesel trucks), light industry, commercial facilities, and residential areas. Stationary samples were collected for 1-year (October 24, 2017, to October 31, 2018) at six sites using traditional sampling methods and lower-cost air sensor packages. This work examines PM less than 2.5 μm in diameter (PM 2.5 ), black carbon (BC), and trace metals data collected during KC-TRAQS. PM 2.5 filter samples showed the highest 24-h mean concentrations (9.34 μg/m 3 ) at the sites located within 20-50 m of the railyard. Mean 24-h PM 2.5 concentrations, ranging from 7.96 to 9.34 μg/m 3 , at all sites were lower than that of the nearby regulatory site (9.83 μg/m 3 ). Daily maximum PM 2.5 concentrations were higher at the KC-TRAQS sites (ranging from 25.31 to 43.76 μg/m 3 ) compared to the regulatory site (20.50 μg/m 3 ), suggesting short-duration impacts of localized emissions sources. Across the KC-TRAQS sites, 24-h averaged PM 2.5 concentrations from the sensor package (P-POD) ranged from 3.24 to 5.69 µg/m 3 showing that, out-of-the-box, the PM sensor underestimated the reference concentrations. KC-TRAQS was supplemented by elemental and organic carbon (EC/OC) and trace metal analysis of filter samples. The EC/OC data suggested the presence of secondary organic aerosol formation, with the highest mean concentrations observed at the site within 20 m of the railyard. Trace metals data showed daily, monthly, and seasonal variations for iron, copper, zinc, chromium, and nickel, with elevated concentrations occurring during the summer at most of the sites. Implications : This work reports on findings from a year-long air quality study in Southeast Kansas City, Kansas to understand micro-scale air quality in neighborhoods impacted by multiple emissions sources such as transportation sources (including a large railyard operation), light industry, commercial facilities, and residential areas. While dozens of studies have reported on air quality near roadways, this work will provide more information on PM 2.5 , black carbon, and trace metals concentrations near other transportation sources in particular railyards. This work can also inform additional field studies near railyards.

Communities located in near-road environments experience elevated levels of traffic-related air pollution. Near-road air pollution is a major public health concern, and an environmental justice issue. Roadside green infrastructure such as trees, hedges, and bushes may help reduce pollution levels through enhanced deposition and mixing. Gaussian-based dispersion models are widely used by policymakers to evaluate mitigation strategies and develop regulatory actions. However, vegetation barriers are not included in those models, hindering air quality improvement at the community level. The main modeling challenge is the complexity of the deposition and mixing process within and downwind of the vegetation barrier. We propose a novel multi-regime Gaussian-based model that describes the parameters of the standard Gaussian equations in each regime to account for the physical mechanisms by which the vegetation barrier deposits and disperses pollutants. The four regimes include vegetation, a downwind wake, a transition, and a recovery zone. For each regime, we fit the relevant Gaussian plume equation parameters as a function of the vegetation properties and the local wind speed. Furthermore, the model captures particle deposition, a major factor in pollutant reduction by vegetation barriers. We parameterized the multi-regime model using data generated from a fields-validated computational fluid dynamics (CFD) model, covering a wide range of vegetation properties and meteorological conditions. The proposed multi-regime Gaussian-based model was evaluated across 9 particle sizes and a tracer gas to assess its capability of capturing dispersion and deposition. The multi-regime model's normalized mean error (NME) ranged between 0.18 and 0.3, the fractional bias (FB) ranged between -0.12 and 0.09, and R 2 value ranged from 0.47 to 0.75 across all particle sizes and the tracer gas for ground level concentrations, which are within acceptable ranges for air quality dispersion modeling. Even though the multi-regime model is parameterized for coniferous trees, our sensitivity study indicates that it can provide useful predictions for hedges/bushes vegetative barriers as well., Competing Interests: Conflicts of interest There are no conflicts to declare.

Many countries have adopted portable emissions measurement system (PEMS) testing in their latest regulations to measure real-world vehicular emissions. However, its fleetwide implementation is severely limited by the high equipment costs and lengthy setup procedures, posing a need to develop more cost-effective, efficient emission measurement methods, such as mobile chasing tests. We conducted conjoint PEMS-chasing experiments for twelve heavy-duty diesel vehicles (HDDTs) to evaluate the accuracy of mobile measurement results. Two data processing approaches were integrated to automate the calculations of fuel consumption-based emission factors of nitrogen oxides (NO X ). With a total of 245 plume chasing tests conducted, and then averaged by vehicle and road types, we found that the relative errors of vehicle-specific emission factors using an algorithm developed for this project were within approximately ±20% of the PEMS results for all tested vehicles. Stochastic simulations suggested reasonable results could be obtained using fewer chasing tests per vehicle (e.g., 71% for freeways and 94% for local road, equivalent to two chase tests per vehicle). This study improves the understanding of the accuracy of the mobile chasing method, and provides a practical approach for real-time emission measurements for future scaled-up mobile chasing studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Communities located in near-road environments face adverse health effects due to elevated exposures to traffic-related air pollution (TRAP). While the use of a combination of solid structures (i.e. sound walls) and vegetation barriers can be an effective TRAP mitigation tool, installing these barriers can also present challenges to local communities. Sound walls are costly, and building these structures often requires the involvement of federal, state, and local permitting agencies. In this paper, we proposed that the use of low-cost, impermeable, solid structures (LISS), e.g., an impermeable thin wooden, plastic or metal fence, combined with vegetation can provide an effective option for local communities to improve near-road air quality due to lower costs and easier implementation. We conducted Large Eddy Simulations (LES) for different design scenarios of LISS and vegetation barriers under various conditions. Our results indicate that (i) combining LISS and vegetation is more effective than either alone, (ii) combining a less dense vegetation and LISS can be as effective as a dense vegetation barrier, (iii) In certain scenarios, depending on wind speed and particle size, vegetation barriers alone might lead to elevated pollutant concentrations; however, combining LISS with vegetation can mitigate those negative impacts, (iv) placing LISS closer to the freeway and in front of the vegetation barrier enhances vertical dispersion of pollutants, and (v) increasing LISS height promotes pollutant concentration reduction. These design recommendations can be used by urban planners, developers, and local community leaders to evaluate and implement green infrastructure to mitigate TRAP., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Trees in urban areas have a significant impact on air quality and other environmental issues. Trees can affect the concentration of air pollutants that we breathe in by directly removing pollutants or avoiding emissions and secondary pollutant formation in the atmosphere. In addition, trees have other benefits including increasing property value, intercepting storm water runoff and saving energy needed for cooling of buildings in hot seasons. In this work, we estimate economic and environmental benefits of three tree species typical for desert regions such as Acacia tortilis , Ziziphus spina-christi and Phoenix dactylifera . The benefits varied by species with Acacia tortilis having the highest overall benefits, mostly because of its large leaf surface area and canopy shape. Tree benefits from carbon reduction reached up to US $14 billion annually. Mature trees tended to be more beneficial than smaller trees for improving environmental conditions. The location of trees had minimal impact on the overall economic value. This assessment provides urban planners, foresters, and developers in desert regions with the information needed to make informed decisions on the economic and environmental benefits of urban tree planting., Competing Interests: Conflict of interests The authors declare no conflict of interests.

Nitrogen dioxide (NO 2 ) not only is linked to adverse effects on the respiratory system but also contributes to the formation of ground-level ozone (O 3 ) and fine particulate matter (PM 2.5 ). Our curbside monitoring data analysis in Detroit, MI, and Atlanta, GA, strongly suggests that a large fraction of NO 2 is produced during the "tailpipe-to-road" stage. To substantiate this finding, we designed and carried out a field campaign to measure the same exhaust plumes at the tailpipe-level by a portable emissions measurement system (PEMS) and at the on-road level by an electric vehicle-based mobile platform. Furthermore, we employed a turbulent reacting flow model, CTAG, to simulate the on-road chemistry behind a single vehicle. We found that a three-reaction (NO-NO 2 -O 3 ) system can largely capture the rapid NO to NO 2 conversion (with time scale ≈ seconds) observed in the field studies. To distinguish the contributions from different mechanisms to near-road NO 2 , we clearly defined a set of NO 2 /NO x ratios at different plume evolution stages, namely tailpipe, on-road, curbside, near-road, and ambient background. Our findings from curbside monitoring, on-road experiments, and simulations imply the on-road oxidation of NO by ambient O 3 is a significant, but so far ignored, contributor to curbside and near-road NO 2 .

The present study examines the effects of fuel [an ultralow sulfur diesel (ULSD) versus a 20% v/v soy-based biodiesel-80% v/v petroleum blend (B20)], temperature, load, vehicle, driving cycle, and active regeneration technology on gas- and particle-phase carbon emissions from light and medium heavy-duty diesel vehicles (L/MHDDV). The study is performed using chassis dynamometer facilities that support low-temperature operation (-6.7 °C versus 21.7 °C) and heavy loads up to 12 000 kg. Organic and elemental carbon (OC-EC) composition of aerosol particles is determined using a thermal-optical technique. Gas- and particle-phase semivolatile organic compound (SVOC) emissions collected using traditional filter and polyurethane foam sampling media are analyzed using advanced gas chromatograpy/mass spectrometry methods. Study-wide OC and EC emissions are 0.735 and 0.733 mg/km, on average. The emissions factors for diesel vehicles vary widely, and use of a catalyzed diesel particle filter (CDPF) device generally mutes the carbon particle emissions in the exhaust, which contains ~90% w/w gas-phase matter. Interestingly, replacing ULSD with B20 did not significantly influence SVOC emissions, for which sums range from 0.030 to 9.4 mg/km for the L/MHDDVs. However, both low temperature and vehicle cold-starts significantly increase SVOCs in the exhaust. Real-time particle measurements indicate vehicle regeneration technology did influence emissions, although regeneration effects went unresolved using bulk chemistry techniques. A multistudy comparison of the toxic particle-phase polycyclic aromatic hydrocarbons (PAHs; molecular weight (MW) ≥ 252 amu) in diesel exhaust indicates emission factors that span up to 8 orders of magnitude over the past several decades. This study observes conditions under which PAH compounds with MW ≥ 252 amu appear in diesel particles downstream of the CDPF and can even reach low-end concentrations reported earlier for much larger HDDVs with poorly controlled exhaust streams. This rare observation suggests that analysis of PAHs in particles emitted from modern L/MHDDVs may be more complex than recognized previously., Competing Interests: The authors declare no competing financial interest.

With increasing evidence that exposures to air pollution near large roadways increases risks of a number of adverse human health effects, identifying methods to reduce these exposures has become a public health priority. Roadside vegetation barriers have shown the potential to reduce near-road air pollution concentrations; however, the characteristics of these barriers needed to ensure pollution reductions are not well understood. Designing vegetation barriers to mitigate near-road air pollution requires a mechanistic understanding of how barrier configurations affect the transport of traffic-related air pollutants. We first evaluated the performance of the Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry (CTAG) model with Large Eddy Simulation (LES) to capture the effects of vegetation barriers on near-road air quality, compared against field data. Next, CTAG with LES was employed to explore the effects of six conceptual roadside vegetation/solid barrier configurations on near-road size-resolved particle concentrations, governed by dispersion and deposition. Two potentially viable design options are revealed: a) a wide vegetation barrier with high Leaf Area Density (LAD), and b) vegetation-solid barrier combinations, i.e., planting trees next to a solid barrier. Both designs reduce downwind particle concentrations significantly. The findings presented in the study will assist urban planning and forestry organizations with evaluating different green infrastructure design options., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Emissions of speciated volatile organic compounds (VOCs), including mobile source air toxics (MSATs), were measured in vehicle exhaust from three light-duty spark ignition vehicles operating on summer and winter grade gasoline (E0) and ethanol blended (E10 and E85) fuels. Vehicle testing was conducted using a three-phase LA92 driving cycle in a temperature-controlled chassis dynamometer at two ambient temperatures (-7 and 24 °C). The cold start driving phase and cold ambient temperature increased VOC and MSAT emissions up to several orders of magnitude compared to emissions during other vehicle operation phases and warm ambient temperature testing, respectively. As a result, calculated ozone formation potentials (OFPs) were 7 to 21 times greater for the cold starts during cold temperature tests than comparable warm temperature tests. The use of E85 fuel generally led to substantial reductions in hydrocarbons and increases in oxygenates such as ethanol and acetaldehyde compared to E0 and E10 fuels. However, at the same ambient temperature, the VOC emissions from the E0 and E10 fuels and OFPs from all fuels were not significantly different. Cold temperature effects on cold start MSAT emissions varied by individual MSAT compound, but were consistent over a range of modern spark ignition vehicles.

Speciated volatile organic compounds (VOCs) were measured in diesel exhaust from three heavy-duty trucks equipped with modern aftertreatment technologies. Emissions testing was conducted on a chassis dynamometer at two ambient temperatures (-7 and 22 °C) operating on two fuels (ultra low sulfur diesel and 20% soy biodiesel blend) over three driving cycles: cold start, warm start and heavy-duty urban dynamometer driving cycle. VOCs were measured separately for each drive cycle. Carbonyls such as formaldehyde and acetaldehyde dominated VOC emissions, making up ∼ 72% of the sum of the speciated VOC emissions (∑VOCs) overall. Biodiesel use led to minor reductions in aromatics and variable changes in carbonyls. Cold temperature and cold start conditions caused dramatic enhancements in VOC emissions, mostly carbonyls, compared to the warmer temperature and other drive cycles, respectively. Different 2007+ aftertreatment technologies involving catalyst regeneration led to significant modifications of VOC emissions that were compound-specific and highly dependent on test conditions. A comparison of this work with emission rates from different diesel engines under various test conditions showed that these newer technologies resulted in lower emission rates of aromatic compounds. However, emissions of other toxic partial combustion products such as carbonyls were not reduced in the modern diesel vehicles tested.

Unlabelled: Representative profiles for particulate matter particles less than or equal to 2.5 microm (PM2.5) are developed from the Kansas City Light-Duty Vehicle Emissions Study for use in the US. Environmental Protection Agency (EPA) vehicle emission model, the Motor Vehicle Emission Simulator (MOVES), and for inclusion in the EPA SPECIATE database for speciation profiles. The profiles are compatible with the inputs of current photochemical air quality models, including the Community Multiscale Air Quality Aerosol Module Version 6 (AE6). The composition of light-duty gasoline PM2.5 emissions differs significantly between cold start and hot stabilized running emissions, and between older and newer vehicles, reflecting both impacts of aging/deterioration and changes in vehicle technology. Fleet-average PM2.5 profiles are estimated for cold start and hot stabilized running emission processes. Fleet-average profiles are calculated to include emissions from deteriorated high-emitting vehicles that are expected to continue to contribute disproportionately to the fleet-wide PM2.5 emissions into the future. The profiles are calculated using a weighted average of the PM2.5 composition according to the contribution of PM2.5 emissions from each class of vehicles in the on-road gasoline fleet in the Kansas City Metropolitan Statistical Area. The paper introduces methods to exclude insignificant measurements, correct for organic carbon positive artifact, and control for contamination from the testing infrastructure in developing speciation profiles. The uncertainty of the PM2.5 species fraction in each profile is quantified using sampling survey analysis methods. The primary use of the profiles is to develop PM2.5 emissions inventories for the United States, but the profiles may also be used in source apportionment, atmospheric modeling, and exposure assessment, and as a basis for light-duty gasoline emission profiles for countries with limited data., Implications: PM2.5 speciation profiles were developed from a large sample of light-duty gasoline vehicles tested in the Kansas City area. Separate PM2.5 profiles represent cold start and hot stabilized running emission processes to distinguish important differences in chemical composition. Statistical analysis was used to construct profiles that represent PM2.5 emissions from the U.S. vehicle fleet based on vehicles tested from the 2005 calendar year Kansas City metropolitan area. The profiles have been incorporated into the EPA MOVES emissions model, as well as the EPA SPECIATE database, to improve emission inventories and provide the PM2.5 chemical characterization needed by CMAQv5.0 for atmospheric chemistry modeling.

Unlabelled: Exposures to mobile source air toxics (MSATs) have been associated with numerous adverse health effects. While thousands of air toxic compounds are emitted from mobile sources, members of a subset of compounds are considered high priority due to their significant contribution to cancer and noncancer health risks and the contribution of mobile sources to total exposure as evaluated by the U.S. Environmental Protection Agency (EPA) National-Scale Air Toxics Assessments (NATA). These pollutants include benzene, 1,3-butadiene, ethylbenzene, acrolein, acetaldehyde, formaldehyde, naphthalene, polycyclic organic matter, and diesel particulate matter/organic gases. This study provided year-long trends of benzene, 1,3-butadiene, acrolein, acetaldehyde, and formaldehyde in Las Vegas, NV Results indicated that MSAT concentrations often did not exhibit trends typical of other primary emitted pollutants in this study. Instead, other mobile sources beyond the highway of interest contributed to the measured values, including a major arterial road, a large commercial airport, and a nearby parking lot. The data were compared with relevant census-tract NATA estimates, with estimated ambient 1,3-butadiene concentrations similar to the measured values. Measured benzene values were much lower relative to the NATA total ambient benzene concentrations. Measured acrolein values were much higher relative to the NATA total acrolein concentrations. Measured acetaldehyde and formaldehyde values were also higher relative to the NATA total acetaldehyde and formaldehyde concentrations for all wind conditions and downwind conditions. Some possible explanations for these differences include nearby sources influencing the measured values; meteorological influences that may not be well captured by the NATA modeling regime; chemical reactivity of measured compounds; and additional explanatory variables may be needed for certain urban areas in order to accurately disaggregate anthropogenic air toxics emissions., Implications: Comparison of air toxics concentrations measured at four long-term near-road sites in Las Vegas, NV, show generally good agreement with the EPA 2005 NATA total ambient concentrations. Measured concentrations did not compare as well with EPA 2005 NATA for the on-road mobile portion of the ambient concentrations. This highlights the complexity of air toxic emission sources and impacts in urban areas, especially around large highway facilities; NATA's inability to capture local-scale meteorology and fine-scale ambient gradients; and that additional explanatory variables may be needed for certain urban areas in order to accurately disaggregate anthropogenic air toxics emissions.

One proposed method for reducing exposure to mobile source air pollution is the construction or preservation of vegetation barriers between major roads and nearby populations. This study combined stationary and mobile monitoring approaches to determine the effects of an existing, mixed-species tree stand on near-road black carbon (BC) and particulate matter concentrations. Results indicated that wind direction and time of day significantly affected pollutant concentrations behind the tree stand. Continuous sampling revealed reductions in BC behind the barrier, relative to a clearing, during downwind (12.4% lower) and parallel (7.8% lower) wind conditions, with maximum reductions of 22% during the late afternoon when winds were from the road. Particle counts in the fine and coarse particle size range (0.5-10 μm aerodynamic diameter) did not show change. Mobile sampling revealed BC concentration attenuation, a result of the natural dilution and mixing that occur with transport from the road, was more gradual behind the vegetation barrier than in unobstructed areas. These findings suggest that a mature tree stand can modestly improve traffic-related air pollution in areas located adjacent to the road; however, the configuration of the tree stand can influence the likelihood and extent of pollutant reductions., (Published by Elsevier B.V.)

Unlabelled: A study, conducted in Las Vegas, NV from mid-December 2008 to mid-December 2009 along an interstate highway, collected continuous and integrated samples for a wide variety of air pollutant species including NO2 and NO(x) associated with roadway traffic. This study examined long-term trends of NO2 and NO(x) in a near-road environment compared with previous near-road studies typically lasting only a few days to months. Study results revealed concentration gradients for NO2 and NO(x) with highest absolute and average concentrations at distances closest to the roadway throughout the year. Diurnal ambient temperature changes also influenced concentrations due to atmospheric chemistry activity as well as concentration changes due to seasonal effects. These concentration gradients were observed for all wind conditions; however under downwind conditions (winds from highway), the concentration gradients are more pronounced. Higher pollutant concentrations are generally observed during low wind speed conditions especially when those winds were from the highway. Understanding long-term, seasonal variability and levels of pollutant concentrations in the near-road environment is important to researchers and decision-makers evaluating exposures and risks for near-road populations; identifying locations for future near-road monitoring sites; and determining the viability and effectiveness of mitigation strategies., Implications: Population exposures to traffic emissions near roads have led to heightened public health concerns and awareness of the long-term levels and variability of these air pollutants. Epidemiological studies have lead to improved understanding of the associated risks and health effects of near road air pollutant emissions. While short-term studies provide insights on near-road air quality, longer-term trends need to be understood, especially for reactive pollutants such as NO2.

This research characterizes associations between multiple pollutants in the near-road environment attributed to a roadway line source. It also examines the use of a tracer gas as a surrogate of mobile source pollutants. Air samples were collected in summa canisters along a 300 m transect normal to a highway in Raleigh, North Carolina for five sampling periods spanning four days. Samples were subsequently measured for volatile organic compounds (VOCs) using an electron capture gas chromatograph. Sulfur hexafluoride (SF6) was released from a finite line source adjacent to the roadway for two of the sampling periods, collected in the canisters and measured with the VOCs. Associations between each VOC, and between VOCs and the tracer, were quantified with Pearson correlation coefficients to assess the consistency of the multi-pollutant dispersion profiles, and assess the tracer as a potential surrogate for mobile source pollutants. As expected, benzene, toluene, ethylbenzene, and m,p- and o-xylenes (collectively, BTEX) show strong correlations between each other; further BTEX shows a strong correlation to SF6. Between 26 VOCs, correlation coefficients were greater than 0.8, and 14 VOCs had coefficients greater than 0.6 with the tracer gas. Even under non-downwind conditions, chemical concentrations had significant correlations with distance. Results indicate that certain VOCs are representative of a larger multi-pollutant mixture, and many VOCs are well-correlated with the tracer gas.

The contribution of lubricating oil to particulate matter (PM) emissions representative of the in-use 2004 light-duty gasoline vehicles fleet is estimated from the Kansas City Light-Duty Vehicle Emissions Study (KCVES). PM emissions are apportioned to lubricating oil and gasoline using aerosol-phase chemical markers measured in PM samples obtained from 99 vehicles tested on the California Unified Driving Cycle. The oil contribution to fleet-weighted PM emission rates is estimated to be 25% of PM emission rates. Oil contributes primarily to the organic fraction of PM, with no detectable contribution to elemental carbon emissions. Vehicles are analyzed according to pre-1991 and 1991-2004 groups due to differences in properties of the fitting species between newer and older vehicles, and to account for the sampling design of the study. Pre-1991 vehicles contribute 13.5% of the KC vehicle population, 70% of oil-derived PM for the entire fleet, and 33% of the fuel-derived PM. The uncertainty of the contributions is calculated from a survey analysis resampling method, with 95% confidence intervals for the oil-derived PM fraction ranging from 13% to 37%. The PM is not completely apportioned to the gasoline and oil due to several contributing factors, including varied chemical composition of PM among vehicles, metal emissions, and PM measurement artifacts. Additional uncertainties include potential sorption of polycyclic aromatic hydrocarbons into the oil, contributions of semivolatile organic compounds from the oil to the PM measurements, and representing the in-use fleet with a limited number of vehicles.

Roadside barriers, such as tree stands or noise barriers, are prevalent in many populated areas and have been shown to affect the dispersion of traffic emissions. If roadside noise barriers or tree stands are found to consistently lower ground-level air pollution concentrations in the near-road environment, this may be a practical strategy for reducing exposures to air contaminants along populated traffic corridors. This study measured ultrafine particle (UFP) concentrations using an instrumented mobile measurement approach, collecting data on major roadways and in near-road locations for more than forty sampling sessions at three locations in central North Carolina, USA. Two of the sampling sites had relatively thin tree stands, one evergreen and one deciduous, along a portion of the roadway. The third sampling site had a brick noise wall along a portion of the road. At 10 m from the road, UFPs measured using a mobile sampling platform were lower by approximately 50% behind the brick noise wall relative to a nearby location without a barrier for multiple meteorological conditions. The UFP trends at the vegetative barrier sites were variable and the barrier effect is uncertain. In some cases, higher concentrations were observed behind the vegetative barrier, with respect to the clearing, which may be due to gaps in the thin tree stands allowing the transport of traffic-related air pollution to near-road areas behind the vegetation. On-road sampling revealed no consistent difference in UFP levels in on-road portions of the road with or without a roadside barrier present. These findings support the notion that solid roadside barriers may mitigate near-road impact. Given the co-benefits of vegetative barriers in the urban landscape, research regarding the mitigation potential of vegetative barriers of other configurations (e.g., greater density, wider buffer) is encouraged., (Published by Elsevier B.V.)

Mobile sources significantly contribute to ambient concentrations of airborne particulate matter (PM). Source apportionment studies for PM10 (PM < or = 10 microm in aerodynamic diameter) and PM2.5 (PM < or = 2.5 microm in aerodynamic diameter) indicate that mobile sources can be responsible for over half of the ambient PM measured in an urban area. Recent source apportionment studies attempted to differentiate between contributions from gasoline and diesel motor vehicle combustion. Several source apportionment studies conducted in the United States suggested that gasoline combustion from mobile sources contributed more to ambient PM than diesel combustion. However, existing emission inventories for the United States indicated that diesels contribute more than gasoline vehicles to ambient PM concentrations. A comprehensive testing program was initiated in the Kansas City metropolitan area to measure PM emissions in the light-duty, gasoline-powered, on-road mobile source fleet to provide data for PM inventory and emissions modeling. The vehicle recruitment design produced a sample that could represent the regional fleet, and by extension, the national fleet. All vehicles were recruited from a stratified sample on the basis of vehicle class (car, truck) and model-year group. The pool of available vehicles was drawn primarily from a sample of vehicle owners designed to represent the selected demographic and geographic characteristics of the Kansas City population. Emissions testing utilized a portable, light-duty chassis dynamometer with vehicles tested using the LA-92 driving cycle, on-board emissions measurement systems, and remote sensing devices. Particulate mass emissions were the focus of the study, with continuous and integrated samples collected. In addition, sample analyses included criteria gases (carbon monoxide, carbon dioxide, nitric oxide/nitrogen dioxide, hydrocarbons), air toxics (speciated volatile organic compounds), and PM constituents (elemental/organic carbon, metals, semi-volatile organic compounds). Results indicated that PM emissions from the in-use fleet varied by up to 3 orders of magnitude, with emissions generally increasing for older model-year vehicles. The study also identified a strong influence of ambient temperature on vehicle PM mass emissions, with rates increasing with decreasing temperatures.

The Kansas City Light-Duty Vehicle Emissions Study (KCVES) measured exhaust emissions of regulated and unregulated pollutants from 496 vehicles recruited in the Kansas City metropolitan area in 2004 and 2005. Vehicle emissions testing occurred during the summer and winter, with the vehicles operated at ambient temperatures. One key component of this study was the investigation of the influence of ambient temperature on particulate matter (PM) emissions from gasoline-powered vehicles. A subset of the recruited vehicles were tested in both the summer and winter to further elucidate the effects of temperature on vehicle tailpipe emissions. The study results indicated that PM emissions increased exponentially as temperature decreased. In general, PM emissions doubled for every 20 degrees F drop in ambient temperature, with these increases independent of vehicle model year. The effects of temperature on vehicle emissions was most pronounced during the initial start-up of the vehicle (cold start phase) when the vehicle was still cold, leading to inefficient combustion, inefficient catalyst operation, and the potential for the vehicle to be operating under fuel-rich conditions. The large data set available from this study also allowed for the development of a model to describe temperature effects on PM emission rates due to changing ambient conditions. This study has been used as the foundation to develop PM emissions rates, and to model the impact of ambient temperature on these rates, for gasoline-powered vehicles in the EPA's new regulatory motor vehicle emissions model, MOVES.

Assessment of near-road air quality is challenging in urban environments that have roadside structures, elevated road sections, or depressed roads that may impact the dispersion of traffic emissions. Vehicles traveling on arterial roadways may also contribute to air pollution spatial variability in urban areas. To characterize the nature of near-road air quality in a complex urban environment, an instrumented all-electric vehicle was deployed to perform high spatial- and temporal-resolution mapping of ultrafine particles (UFPs, particle diameter <100 nm) and carbon monoxide (CO). Sampling was conducted in areas surrounding a highway in Durham, NC, with multiple repeats of the driving route accomplished within a morning or evening commute time frame. Six different near-road transects were driven, which included features such as noise barriers, vegetation, frontage roads, and densely built houses. Under downwind conditions, median UFP and CO levels in near-road areas located 20-150 m from the highway were a factor of 1.8 and 1.2 higher, respectively, than in areas characterized as urban background. Sampling in multiple near-road neighborhoods during downwind conditions revealed significant variability in absolute UFP and CO concentrations as well as in the rate of concentration attenuation with increasing distance from the highway. During low-speed meandering winds, regional UFP and CO concentrations nearly doubled relative to crosswind conditions; however, near-road UFP levels were still higher than urban background levels by a factor of 1.2, whereas near-road CO concentrations were not significantly different than the urban background.

Background: Epidemiologic studies have reported an association between proximity to highway traffic and increased cardiopulmonary illnesses., Objectives: We investigated the effect of size-fractionated particulate matter (PM), obtained at different distances from a highway, on acute cardiopulmonary toxicity in mice., Methods: We collected PM for 2 weeks in July-August 2006 using a three-stage (ultrafine, < 0.1 microm; fine, 0.1-2.5 microm; coarse, 2.5-10 microm) high-volume impactor at distances of 20 m [near road (NR)] and 275 m [far road (FR)] from an interstate highway in Raleigh, North Carolina. Samples were extracted in methanol, dried, diluted in saline, and then analyzed for chemical constituents. Female CD-1 mice received either 25 or 100 microg of each size fraction via oropharyngeal aspiration. At 4 and 18 hr postexposure, mice were assessed for pulmonary responsiveness to inhaled methacholine, biomarkers of lung injury and inflammation; ex vivo cardiac pathophysiology was assessed at 18 hr only., Results: Overall chemical composition between NR and FR PM was similar, although NR samples comprised larger amounts of PM, endotoxin, and certain metals than did the FR samples. Each PM size fraction showed differences in ratios of major chemical classes. Both NR and FR coarse PM produced significant pulmonary inflammation irrespective of distance, whereas both NR and FR ultrafine PM induced cardiac ischemia-reperfusion injury., Conclusions: On a comparative mass basis, the coarse and ultrafine PM affected the lung and heart, respectively. We observed no significant differences in the overall toxicity end points and chemical makeup between the NR and FR PM. The results suggest that PM of different size-specific chemistry might be associated with different toxicologic mechanisms in cardiac and pulmonary tissues.

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.

Field data for coarse particulate matter ([PM] PM10) and fine particulate matter (PM2.5) were collected at selected sites in Southeast Kansas from March 1999 to October 2000, using portable MiniVol particulate samplers. The purpose was to assess the influence on air quality of four industrial facilities that burn hazardous waste in the area located in the communities of Chanute, Independence, Fredonia, and Coffeyville. Both spatial and temporal variation were observed in the data. Variation because of sampling site was found to be statistically significant for PM10 but not for PM2.5. PM10 concentrations were typically slightly higher at sites located within the four study communities than at background sites. Sampling sites were located north and south of the four targeted sources to provide upwind and downwind monitoring pairs. No statistically significant differences were found between upwind and downwind samples for either PM10 or PM2.5, indicating that the targeted sources did not contribute significantly to PM concentrations. Wind direction can frequently contribute to temporal variation in air pollutant concentrations and was investigated in this study. Sampling days were divided into four classifications: predominantly south winds, predominantly north winds, calm/variable winds, and winds from other directions. The effect of wind direction was found to be statistically significant for both PM10 and PM2.5. For both size ranges, PM concentrations were typically highest on days with predominantly south winds; days with calm/variable winds generally produced higher concentrations than did those with predominantly north winds or those with winds from "other" directions. The significant effect of wind direction suggests that regional sources may exert a large influence on PM concentrations in the area.

The U.S. Environmental Protection Agency (EPA) implemented a program to identify tailpipe emissions of criteria and air-toxic contaminants from in-use, light-duty low-emission vehicles (LEVs). EPA recruited 25 LEVs in 2002 and measured emissions on a chassis dynamometer using the cold-start urban dynamometer driving schedule of the Federal Test Procedure. The emissions measured included regulated pollutants, particulate matter, speciated hydrocarbon compounds, and carbonyl compounds. The results provided a comparison of emissions from real-world LEVs with emission standards for criteria and air-toxic compounds. Emission measurements indicated that a portion of the in-use fleet tested exceeded standards for the criteria gases. Real-time regulated and speciated hydrocarbon measurements demonstrated that the majority of emissions occurred during the initial phases of the cold-start portion of the urban dynamometer driving schedule. Overall, the study provided updated emission factor data for real-world, in-use operation of LEVs for improved emissions modeling and mobile source inventory development.

In siting a monitor to measure compliance with U.S. National Ambient Air Quality Standards (NAAQS) for particulate matter (PM), there is a need to characterize variations in PM concentration within a neighborhood-scale region to achieve monitor siting objectives. A simple methodology is provided here for the selection of a neighborhood-scale site for meeting either of the two objectives identified for PM monitoring. This methodology is based on analyzing middle-scale (from 100 to 500 m) data from within the area of interest. The required data can be obtained from widely available dispersion models and emissions databases. The performance of the siting methodology was evaluated in a neighborhood-scale field study conducted in Hudson County, NJ, to characterize the area's inhalable particulate (PM10) concentrations. Air monitors were located within a 2- by 2-km area in the vicinity of the Lincoln Tunnel entrance in Hudson County. Results indicate the siting methodology performed well, providing a positive relationship between the predicted concentration rank at each site and the actual rank experienced during the field study. Also discussed are factors that adversely affected the predictive capabilities of the model.

An ambient air quality monitoring network has been established using risk assessment techniques to evaluate adverse health effects from exposures to airborne contaminants. The risk assessment method was compared to traditional methods of establishing air quality monitoring networks: identifying m aximum concentration impacts or maximum total population. Results suggest that the health risk method best predicted the location of adverse, non-carcinogenic respiratory illnesses during the evaluation period. Spearman Rank Correlation Coefficient, r(s), values obtained using the risk assessment method were statistically greater than the values obtained using the concentration and population methods. The concentration method was the least accurate predictor of adverse effects.

Existing methods of establishing ambient air quality monitoring networks typically evaluate only parameters related to ambient concentrations of the contaminant(s) of interest such as emission source characteristics, atmospheric transport and dispersion, secondary reactions, deposition characteristics, and local topography. However, adverse health risks from exposures to airborne contaminants are a function of the contaminant and the anatomic and physiologic characteristics of the exposed population. Thus, ambient air quality monitoring networks designed for the protection of public health or for epidemiological studies evaluating adverse health impacts from exposures to ambient air contaminants should account for both contaminant characteristics and human health parameters. A methodology has been established which optimizes ambient air quality monitoring networks for assessments of adverse human health impacts from exposures to airborne contaminants by incorporating human health risk assessment techniques. The use of risk assessment techniques as the basis for designing ambient air quality monitoring networks will help to target limited financial and human resources to evaluate human health risks from exposures to airborne contaminants.