Analysis of PM2.5, black carbon, and trace metals measurements from the Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS).

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 (PM2.5), black carbon (BC), and trace metals data collected during KC-TRAQS. PM2.5 filter samples showed the highest 24-h mean concentrations (9.34 µg/m3) at the sites located within 20-50 m of the railyard. Mean 24-h PM2.5 concentrations, ranging from 7.96 to 9.34 µg/m3, at all sites were lower than that of the nearby regulatory site (9.83 µg/m3). Daily maximum PM2.5 concentrations were higher at the KC-TRAQS sites (ranging from 25.31 to 43.76 µg/m3) compared to the regulatory site (20.50 µg/m3), suggesting short-duration impacts of localized emissions sources. Across the KC-TRAQS sites, 24-h averaged PM2.5 concentrations from the sensor package (P-POD) ranged from 3.24 to 5.69 µg/m3 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 PM2.5, black carbon, and trace metals concentrations near other transportation sources in particular railyards. This work can also inform additional field studies near railyards.

Evaluating mobile monitoring of on-road emission factors by comparing concurrent PEMS measurements.

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 (NOX). 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.

Enhancing the local air quality benefits of roadside green infrastructure using low-cost, impermeable, solid structures (LISS).

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.

Identifying air pollution source impacts in urban communities using mobile monitoring.

With increasing population, rapid urbanization, and increased migration to cities, the local impacts of increasing transportation and industrial-related air pollution are of growing concern worldwide. Elevated air pollution concentrations near these types of sources have been linked to adverse health effects including acute and chronic respiratory and cardiovascular diseases. Mobile monitoring has proven to be a useful technique to characterize spatial variability of air pollution in urban areas and pollution concentration gradients from specific sources. A study was conducted in the Kansas City, Kansas (USA) metropolitan area using mobile monitoring to characterize the spatial variability and gradients of air pollutants to identify the contribution of multiple sources on community-level air quality in a complex urban environment. Measurements focused on nitrogen dioxide (NO2), black carbon (BC), and ultrafine particulate matter (UFP). Mobile monitoring showed that median concentrations of these pollutants ranged by up to a factor of three between the communities, with individual measurements ranging over an order of magnitude within the community. Evaluating these air quality measurements with wind direction data highlighted the influence of specific and combinations of air pollution sources on these elevated concentrations, which can provide valuable information to environmental and public health officials in prioritizing and implementing cost-effect air quality management strategies to reduce exposures for urban populations.

Impact of School Location on Children's Air Pollution Exposure.

The role of school location in children's air pollution exposure and ability to actively commute is a growing policy issue. Well-documented health impacts associated with near-roadway exposures have led school districts to consider school sites in cleaner air quality environments requiring school bus transportation. We analyze children's traffic-related air pollution exposure across an average Detroit school day to assess whether the benefits of reduced air pollution exposure at cleaner school sites are eroded by the need to transport students by bus or private vehicle. We simulated two school attendance scenarios using modeled hourly pollutant concentrations over the school day to understand how air pollution exposure may vary by school location and commute mode. We found that busing children from a high-traffic neighborhood to a school 19 km away in a low-traffic environment resulted in average daily exposures 2 to 3 times higher than children walking to a local school. Health benefits of siting schools away from high-volume roadways may be diminished by pollution exposure during bus commutes. School districts cannot simply select sites with low levels of air pollution, but must carefully analyze tradeoffs between location, transportation, and pollution exposure.

Estimating economic and environmental benefits of urban trees in desert regions.

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.

Combining Dispersion Modeling and Monitoring Data for Community-Scale Air Quality Characterization.

Spatially and temporally resolved air quality characterization is critical for community-scale exposure studies and for developing future air quality mitigation strategies. Monitoring-based assessments can characterize local air quality when enough monitors are deployed. However, modeling plays a vital role in furthering the understanding of the relative contributions of emissions sources impacting the community. In this study, we combine dispersion modeling and measurements from the Kansas City TRansportation local-scale Air Quality Study (KC-TRAQS) and use data fusion methods to characterize air quality. The KC-TRAQS study produced a rich dataset using both traditional and emerging measurement technologies. We used dispersion modeling to support field study design and analysis. In the study design phase, the presumptive placement of fixed monitoring sites and mobile monitoring routes have been corroborated using a research screening tool C-PORT to assess the spatial and temporal coverage relative to the entire study area extent. In the analysis phase, dispersion modeling was used in combination with observations to help interpret the KC-TRAQS data. We extended this work to use data fusion methods to combine observations from stationary, mobile measurements, and dispersion model estimates.

Considerations for evaluating green infrastructure impacts in microscale and macroscale air pollution dispersion models.

Green infrastructure (GI) in urban areas may be adopted as a passive control system to reduce air pollutant concentrations. However, current dispersion models offer limited modelling options to evaluate its impact on ambient pollutant concentrations. The scope of this review revolves around the following question: how can GI be considered in readily available dispersion models to allow evaluation of its impacts on pollutant concentrations and health risk assessment? We examined the published literature on the parameterisation of deposition velocities and datasets for both particulate matter and gaseous pollutants that are required for deposition schemes. We evaluated the limitations of different air pollution dispersion models at two spatial scales - microscale (i.e. 10-500 m) and macroscale (i.e. 5-100 km) - in considering the effects of GI on air pollutant concentrations and exposure alteration. We conclude that the deposition schemes that represent GI impacts in detail are complex, resource-intensive, and involve an abundant volume of input data. An appropriate handling of GI characteristics (such as aerodynamic effect, deposition of air pollutants and surface roughness) in dispersion models is necessary for understanding the mechanism of air pollutant concentrations simulation in presence of GI at different spatial scales. The impacts of GI on air pollutant concentrations and health risk assessment (e.g., mortality, morbidity) are partly explored. The i-Tree tool with the BenMap model has been used to estimate the health outcomes of annually-averaged air pollutant removed by deposition over GI canopies at the macroscale. However, studies relating air pollution health risk assessments due to GI-related changes in short-term exposure, via pollutant concentrations redistribution at the microscale and enhanced atmospheric pollutant dilution by increased surface roughness at the macroscale, along with deposition, are rare. Suitable treatments of all physical and chemical processes in coupled dispersion-deposition models and assessments against real-world scenarios are vital for health risk assessments.

The effects of roadside vegetation characteristics on local, near-road air quality.

Roadside vegetation has been shown to impact downwind, near-road air quality, with some studies identifying reductions in air pollution concentrations and others indicating increases in pollutant levels when vegetation is present. These widely contradictory results have resulted in confusion regarding the capability of vegetative barriers to mitigate near-road air pollution, which numerous studies have associated with significant adverse human health effects. Roadside vegetation studies have investigated the impact of many different types and conditions of vegetation barriers and urban forests, including preserved, existing vegetation stands usually consisting of mixtures of trees and shrubs or plantings of individual trees. A study was conducted along a highway with differing vegetation characteristics to identify if and how the changing characteristics affected downwind air quality. The results indicated that roadside vegetation needed to be of sufficient height, thickness, and coverage to achieve downwind air pollutant reductions. A vegetation stand which was highly porous and contained large gaps within the stand structure had increased downwind pollutant concentrations. These field study results were consistent with other studies that the roadside vegetation could lead to reductions in average, downwind pollutant concentrations by as much as 50% when this vegetation was thick with no gaps or openings. However, the presence of highly porous vegetation with gaps resulted in similar or sometimes higher concentrations than measured in a clearing with no vegetation. The combination of air quality and meteorological measurements indicated that the vegetation affects downwind pollutant concentrations through attenuation of meteorological and vehicle-induced turbulence as air passes through the vegetation, enhanced mixing as portions of the traffic pollution plume are blocked and forced over the vegetation, and through particulate deposition onto leaf and branch surfaces. Computational fluid dynamic modeling highlighted that density of the vegetation barrier affects pollutant levels, with a leaf area density of 3.0 m2 m-3 or higher needed to ensure downwind pollutant reductions for airborne particulate matter. These results show that roadside bushes and trees can be preserved or planted along highways and other localized pollution sources to mitigate air quality and human health impacts near the source if the planting adheres to important characteristics of height, thickness, and density with full coverage from the ground to the top of the canopy. The results also highlight the importance of planting denser vegetation and maintaining the integrity and structure of these vegetation barriers to achieve pollution reductions and not contribute to unintended increases in downwind air pollutant concentrations.

The Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS): Integration of Low-Cost Sensors and Reference Grade Monitoring in a Complex Metropolitan Area. Part 1: Overview of the Project.

Emissions from transportation sources can impact local air quality and contribute to adverse health effects. The Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS), conducted over a 1-year period, researched emissions source characterization in the Argentine, Turner, and Armourdale, Kansas (KS) neighborhoods and the broader southeast Kansas City, KS area. This area is characterized as a near-source environment with impacts from large railyard operations, major roadways, and commercial and industrial facilities. The spatial and meteorological effects of particulate matter less than 2.5 µm (PM2.5), and black carbon (BC) pollutants on potential population exposures were evaluated at multiple sites using a combination of regulatory grade methods and instrumentation, low-cost sensors, citizen science, and mobile monitoring. The initial analysis of a subset of these data showed that mean reference grade PM2.5 concentrations (gravimetric) across all sites ranged from 7.92 to 9.34 µg/m3. Mean PM2.5 concentrations from low-cost sensors ranged from 3.30 to 5.94 µg/m3 (raw, uncorrected data). Pollution wind rose plots suggest that the sites are impacted by higher PM2.5 and BC concentrations when the winds originate near known source locations. Initial data analysis indicated that the observed PM2.5 and BC concentrations are driven by multiple air pollutant sources and meteorological effects. The KC-TRAQS overview and preliminary data analysis presented will provide a framework for forthcoming papers that will further characterize emission source attributions and estimate near-source exposures. This information will ultimately inform and clarify the extent and impact of air pollutants in the Kansas City area.

On-Road Chemical Transformation as an Important Mechanism of NO2 Formation.

Nitrogen dioxide (NO2) not only is linked to adverse effects on the respiratory system but also contributes to the formation of ground-level ozone (O3) and fine particulate matter (PM2.5). Our curbside monitoring data analysis in Detroit, MI, and Atlanta, GA, strongly suggests that a large fraction of NO2 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-NO2-O3) system can largely capture the rapid NO to NO2 conversion (with time scale ≈ seconds) observed in the field studies. To distinguish the contributions from different mechanisms to near-road NO2, we clearly defined a set of NO2/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 O3 is a significant, but so far ignored, contributor to curbside and near-road NO2.

Influential factors affecting black carbon trends at four sites of differing distance from a major highway in Las Vegas.

Elevated air pollution levels adjacent to major highways are an ongoing topic of public health concern worldwide. Black carbon (BC), a component of particulate matter (PM) emitted by diesel and gasoline vehicles, was measured continuously via a filter-based light absorption technique over ~ 16 months at four different stations positioned on a perpendicular trajectory to a major highway in Las Vegas, NV. During downwind conditions (winds from the west), BC at 20 m from the highway was 32 and 60% higher than concentrations at 100 and 300 m from the roadway, respectively. Overall highest roadside (20-m site) BC concentrations were observed during the time period of 4 a.m.-8 a.m. under low-speed variable winds (3.02 µg/m3) or downwind conditions (2.84 µg/m3). The 20-m site BC concentrations under downwind conditions are 85% higher on weekday periods compared to weekends during the time period of 4 a.m.-8 a.m. Whereas total traffic volume was higher on weekdays versus weekends and differed by approximately 3% on weekdays versus weekends, similarly, the detected heavy-duty fraction was higher on weekdays versus weekends and differed by approximately 21% on weekdays versus weekend. Low wind speeds predominated during early morning hours, leading to higher BC concentrations during early morning hours despite the maximum traffic volume occurring later in the day. No noticeable impact from the airport or nearby arterial roadways was observed, with the 300-m site remaining the lowest of the four-site network when winds were from the east. Multivariate linear regression analysis revealed that heavy-duty traffic volume, light-duty traffic volume, wind speed, weekday versus weekend, surface friction velocity, ambient temperature, and the background BC concentration were significant predictors of roadside BC concentrations. Comparison of BC and PM2.5 downwind concentration gradients indicates that the BC component contributes substantially to the PM2.5 increase in roadside environments. These results suggest that BC is an important indicator to assess the contribution of primary traffic emissions to near-road PM2.5 concentrations, providing opportunities to evaluate the feasibility and effectiveness of mitigation strategies.

Phenology of a Vegetation Barrier and Resulting Impacts on Near-Highway Particle Number and Black Carbon Concentrations on a School Campus.

Traffic-related air pollution is a persistent concern especially in urban areas where populations live in close proximity to roadways. Innovative solutions are needed to minimize human exposure and the installation of vegetative barriers shows potential as a method to reduce near-road concentrations. This study investigates the impact of an existing stand of deciduous and evergreen trees on near-road total particle number (PNC) and black carbon (BC) concentrations across three seasons. Measurements were taken during spring, fall and winter on the campus of a middle school in the Atlanta (GA, USA) area at distances of 10 m and 50 m from a major interstate highway. We identified consistent decreases in BC concentrations, but not for PNC, with increased distance from the highway. In multivariable models, hour of day, downwind conditions, distance to highway, temperature and relative humidity significantly predicted pollutant concentrations. The magnitude of effect of these variables differed by season, however, we were not able to show a definitive impact of the vegetative barrier on near-road concentrations. More detailed studies are necessary to further examine the specific configurations and scenarios that may produce pollutant and exposure reductions.

Near-port air quality assessment utilizing a mobile measurement approach.

Mobile monitoring is a strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA's Geospatial Measurement of Air Pollution (GMAP) vehicle - an all-electric vehicle is outfitted with a number of measurement devices to record real-time concentrations of particulate matter and gaseous pollutants - was used to map air pollution levels near the Port of Charleston in South Carolina. High-resolution monitoring was performed along driving routes near several port terminals and rail yard facilities, recording geospatial coordinates and concentrations of pollutants including black carbon, size-resolved particle count ranging from ultrafine to coarse (6 nm-20 µm), carbon monoxide, and nitrogen dioxide. Additionally, a portable meteorological station was used to characterize local conditions. The primary objective of this work was to characterize the impact of port facilities on local scale air quality. The study determined that elevated concentration measurements of black carbon and PM correlated to periods of increased port activity and a significant elevation in concentration was observed downwind of ports. However, limitations in study design prevented a more complete analysis of the port effect.

Roadside Vegetation Design to Improve Local, Near-Road Air Quality.

As public health concerns have increased due to the rising number of studies linking adverse health effects with exposures to traffic-related pollution near large roadways, interest in methods to mitigate these exposures have also increased. Several studies have investigated the use of roadside features in reducing near-road air pollution concentrations since this method is often one of the few short-term options available to reduce near-road air pollution. Since roadside vegetation has other potential benefits, the impact of this feature has been of particular interest. The literature has been mixed on whether roadside vegetation reduces nearby pollutant concentrations or whether this feature has no effect or even potentially increases downwind pollutant concentrations. However, these differences in study results highlight key characteristics of the vegetative barrier that can result in pollutant reductions or increase local pollutant levels. This paper describes the characteristics of roadside vegetation that previous research shows can result in improved local air quality, as well as identify characteristics that should be avoided in order to protect from unintended increases in nearby concentrations. These design conditions include height, thickness, coverage, porosity/density, and species characteristics that promote improved air quality. These design considerations can inform highway departments, urban and transportation planners, and developers in understanding how best to preserve existing roadside vegetation or plant vegetative barriers in order to reduce air pollution impacts near transportation facilities.

Evaluation and development of tools to quantify the impacts of roadside vegetation barriers on near-road air quality.

Traffic emissions are associated with the elevation of health risks of people living close to highways. Roadside vegetation barriers have the potential of reducing these risks by decreasing near-road air pollution concentrations. However, while we understand the mechanisms that determine the mitigation caused by solid barriers, we still have questions about how vegetative barriers affect dispersion. The US EPA conducted several field experiments to understand the effects of vegetation barriers on dispersion of pollutants near roadways (e.g., 2008 North Carolina study and 2014 California study) that indicate the reduction of near-road pollutant concentrations can be up to 30% due to the barrier effects. The results of these field studies are being used to develop and evaluate dispersion models that account for the effects of near-road vegetative barriers. These models can be used for evaluating the effectiveness of vegetation barriers as a potential mitigation strategy to reduce exposure to traffic-related pollutants and their associated adverse health effects. This paper presents the results of the analysis of the field studies and discusses dispersion models being used to describe the data in order to simulate the effects of near-road barriers and to develop recommendations for model improvements.

Temperature and Driving Cycle Significantly Affect Carbonaceous Gas and Particle Matter Emissions from Diesel Trucks.

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.

Ultrafine Particle Metrics and Research Considerations: Review of the 2015 UFP Workshop.

In February 2015, the United States Environmental Protection Agency (EPA) sponsored a workshop in Research Triangle Park, NC, USA to review the current state of the science one missions, air quality impacts, and health effects associated with exposures to ultrafine particles[1].[...].

The effects of vegetation barriers on near-road ultrafine particle number and carbon monoxide concentrations.

Numerous studies have shown that people living in near-roadway communities (within 100 m of the road) are exposed to high ultrafine particle (UFP) number concentrations, which may be associated with adverse health effects. Vegetation barriers have been shown to affect pollutant transport via particle deposition to leaves and altering the dispersion of emission plumes, which in turn would modify the exposure of near-roadway communities to traffic-related UFPs. In this study, both stationary (equipped with a Scanning Mobility Particle Sizer, SMPS) and mobile (equipped with Fast Mobility Particle Sizer, FMPS) measurements were conducted to investigate the effects of vegetation barriers on downwind UFP (particle diameters ranging from 14 to 102 nm) concentrations at two sites in North Carolina, USA. One site had mainly deciduous vegetation while the other was primarily coniferous; both sites have a nearby open field without the vegetation barriers along the same stretch of limited access road, which served as a reference. During downwind conditions (traffic emissions transported towards the vegetation barrier) and when the wind speed was above or equal to 0.5m/s, field measurements indicated that vegetation barriers with full foliage reduced UFP and CO concentrations by 37.7-63.6% and 23.6-56.1%, respectively. When the test was repeated at the same sites during winter periods when deciduous foliage was reduced, the deciduous barrier during winter showed no significant change in UFP concentration before and after the barrier. Results from the stationary (using SMPS) and mobile (using FMPS) measurements for UFP total number concentrations generally agreed to within 20%.