Incorporating the impact of roadside barrier effects on dispersion into AERMOD.

This paper focuses on the impact of solid barriers located upwind of a highway in reducing vehicle related concentrations that occur downwind of the roadway, compared to a highway without barriers. Measurements made in the United States Environmental Protection Agency's meteorological wind tunnel show that the mitigating impact of an upwind barrier is comparable to that of a downwind barrier. Upwind barriers lead to reductions in pollution concentrations by drawing emissions in from the highway toward the barrier. The emissions are then entrained into the flow above the recirculation zone and dispersed vertically as they are advected downwind. This upwind transport of vehicle emissions leads to concentrations at the center of the roadways that are roughly 200-300% higher than those measured on roadways with downwind barriers. This difference between on-road concentrations indicates that although both types of barriers mitigate the impact of vehicle emissions downwind of a roadway, the upwind barrier may create adverse air quality impacts for the people on the road.We have formulated a semiempirical dispersion model that incorporates the physics revealed by the wind tunnel measurements. This model improves upon a model proposed by Ahangar et al. (2017) by adjusting the wind speed to get a more realistic plume dispersion just downwind of the upwind barrier and also by providing vertical profiles of concentrations in addition to ground-level concentrations. The upwind barrier model proposed in this paper and the downwind barrier model described in Francisco et al. (2022) have been incorporated into AERMOD (version 21112) as a nonregulatory option, including the new two-barrier option when modeling both barriers on the same roadway.Implications: Our paper presents an air dispersion model algorithm for modeling the effect of upwind noise barriers on dispersion of traffic-related emissions from roadways, which was incorporated into EPA's AERMOD and then evaluated using observations from a wind tunnel experiment. The results are compared and contrasted with results from both a no-barrier case and downwind barrier cases. This manuscript expands on previously published work analyzing the effect of barrier height and source-to-barrier distance on downwind dispersion (Atmos. Pollut. Res., 13:101385, 2022, https://doi.org/10.1016/j.apr.2022.101385). The current manuscript uses the same wind tunnel setup as reported there, but focuses on a different subset of cases, namely the upwind barrier cases, when developing dispersion model algorithms to simulate the observed effects. We believe the evaluations of the vertical profiles from the wind tunnel study, development, and incorporation of the upwind barrier algorithms into AERMOD, and model evaluation of these new algorithms are significant contributions to understanding the effects of these commonly used roadside barriers.

Observations and Parameterization of the Effects of Barrier Height and Source-to-Barrier Distance on Concentrations Downwind of a Roadway.

New results are presented from wind tunnel studies performed at the United States Environmental Protection Agency (U.S. EPA), which include cases with solid roadside barriers of varying heights and cases with varying distances between the line source (roadway) and a 6-m-tall barrier. The Source-to-Barrier Distance cases include seven lanes of traffic with each lane acting as an independent source of continuous emissions along a line (i.e., line source). A mixed-wake algorithm that accounts for barrier effects within a steady-state air dispersion model was updated based on the recent wind tunnel studies. To study the effects of a solid roadside barrier, varying barrier heights and varying distances between the line source and barrier were modeled with the U.S. EPA regulatory air dispersion model AERMOD (v. 21112) using the line-source option that includes an experimental barrier option (RLINEXT). The mixed-wake algorithm reproduced the shape of the vertical concentration profiles observed in the wind tunnel data, including the uniform concentration profile from the ground vertically to a height somewhat greater than the height of the barrier. The algorithm responded appropriately to changes in barrier height and source-to-barrier distance, producing greater reductions in ground-level concentrations for taller barriers and for shorter source-to-barrier distances. Additionally, a rule of thumb that approximates the effect of a downwind barrier was formulated by converting an estimated vertical dispersion into an additional travel distance. The wind tunnel results, the update to the mixed-wake algorithm, and a comparison of the two data sets are described in this paper.

Simulations of dispersion through an irregular urban building array.

Following the release of a harmful substance within an urban environment, buildings and street canyons create complex flow regimes that affect dispersion and localized effluent concentrations. While some fast-response dispersion models can capture the effects caused by individual buildings, further research is required to refine urban characterizations such as plume channeling and spreading, and initial dispersion, especially within the presence of a nonhomogeneous array of structures. Field, laboratory, and modeling experiments that simulate urban or industrial releases are critical in advancing current dispersion models. This project leverages the configuration of buildings used in a full-scale, mock urban field study to examine the concentrations of a neutrally buoyant tracer in a series of wind tunnel and Embedded Large Eddy Simulation (ELES) experiments. The behavior, propagation, and magnitude of the plumes were examined and compared to identify microscale effects. After demonstrating excellent quantitative and qualitative comparisons between the wind tunnel and ELES via lateral and vertical concentration profiles, we show that a nonlinear least squares fit of the Gaussian plume equation well represents these profiles, even within the array of buildings and network of street canyons. The initial plume dispersion depended strongly on the structures immediately adjacent to the release, and consequently, the near-surface plume spread very rapidly in the first few street canyons downwind of the source. The ELES modeling showed that under slightly oblique incoming wind directions of 5° and 15°, an additional 5° and 14° off-axis channeling of the plume occurred at ground level, respectively. This indicates how building structures can cause considerable plume drift from the otherwise expected centerline axis, especially with greater wind obliquity. Additionally, AERMOD was used to represent the class of fast-running, Gaussian dispersion models to inform where these types of models may be usefully applied within urban areas or groups of buildings. Using an urban wind speed profile and other parameters that may be locally available after a release, AERMOD was shown to qualitatively represent the ground-level plume while somewhat underestimating peak concentrations. It also overestimated the lateral plume spread and was challenged in the very near-field to the source. Adding a turbulence profile from the ELES data into AERMOD's meteorological input improved model estimates of lateral plume spread and centerline concentrations, although peak concentration values were still underestimated in the far field. Finally, we offer some observations and suggestions for Gaussian dispersion modeling based on this mock urban modeling exercise.

Dispersion at the edges of near road noise barriers.

This paper presents an analysis of data from a wind tunnel study conducted to examine the dispersion of emissions at the edges of near-road noise barriers. The study is motivated by the concern that a barrier positioned downwind of a roadway may guide highly polluted plumes along the barrier leading to heightened concentrations as the plume spills around and downwind of the barrier end. The wind tunnel database consists of measurements of dispersion around a simulated roadway segment with various noise barrier configurations. Each roadway segment simulated in the wind tunnel had full-scale equivalent dimensions of 135 m long. Barrier segments, 135 m long with a height (H) of 6 m, were located on the downwind side of the source at a distance of 18 m from it (measured perpendicularly from the line source). Examination of the concentration patterns associated with the cases indicates that 1) vertical mixing induced by barriers persists at crosswind distances up to the edge (lateral end) of the barrier and downwind distances of x/H = 10, 2) concentration levels at all heights below z/H = 1 increase towards the edge of the barrier at downwind distances less than x/H = 7, and 3) concentration is well mixed in the vertical at the edge of the barrier, and the levels can be higher than in the middle of the barrier even when the source ends at the edge of the barrier. We have formulated a parameterization that captures the major features of these observations and can be incorporated in models such as RLINE.

Urban wind field analysis from the Jack Rabbit II Special Sonic Anemometer Study.

The Jack Rabbit II Special Sonic Anemometer Study (JRII-S), a field project designed to examine the flow and turbulence within a systematically arranged mock-urban environment constructed from CONEX shipping containers, is described in detail. The study involved the deployment of 35 sonic anemometers at multiple heights and locations, including a 32 m tall, unobstructed tower located about 115 m outside the building array to document the approach wind flow characteristics. The purpose of this work was to describe the experimental design, analyze the sonic data, and report observed wind flow patterns within the urban canopy in comparison to the approaching boundary layer flow. We show that the flow within the building array follows a tendency towards one of three generalized flow regimes displaying channeling over a wide range of wind speeds, directions, and stabilities. Two or more sonic anemometers positioned only a few meters apart can have vastly different flow patterns that are dictated by the building structures. Within the building array, turbulence values represented by normalized vertical velocity variance ( σ w 2 ) are at least two to three times greater than that in the approach flow. There is also little evidence that σ w 2 measured at various heights or locations within the JRII array is a strong function of stability type in contrast to the approach flow. The results reinforce how urban areas create complicated wind patterns, channeling effects, and localized turbulence that can impact the dispersion of an effluent release. These findings can be used to inform the development of improved wind flow algorithms to better characterize pollutant dispersion in fast-response models.

Development and Evaluation of the R-LINE Model Algorithms to Account for Chemical Transformation in the Near-road Environment.

With increased urbanization, there is increased mobility leading to higher amount of traffic-related activity on a global scale. Most NOx from combustion sources (about 90-95%) are emitted as NO, which is then readily converted to NO2 in the ambient air, while the remainder is emitted largely as NO2. Thus, the bulk of ambient NO2 is formed due to secondary production in the atmosphere, and which R-LINE cannot predict given that it can only model the dispersion of primary air pollutants. NO2 concentrations near major roads are appreciably higher than those measured at monitors in existing networks in urban areas, motivating a need to incorporate a mechanism in R-LINE to account for NO2 formation. To address this, we implemented three different approaches in order of increasing degrees of complexity and barrier to implementation from simplest to more complex. The first is an empirical approach based upon fitting a 4th order polynomial to existing near-road observations across the continental U.S., the second involves a simplified two-reaction chemical scheme, and the third involves a more detailed set of chemical reactions based upon the Generic Reaction Set (GRS) mechanism. All models were able to estimate more than 75% of concentrations within a factor of two of the near-road monitoring data and produced comparable performance statistics. These results indicate that the performance of the new R-LINE chemistry algorithms for predicting NO2 is comparable to other models (i.e. ADMS-Roads with GRS), both showing less than ±15% fractional bias and less than 45% normalized mean square error.

Modeling Dispersion of Emissions from Depressed Roadways.

This paper presents an analysis of data from a wind tunnel (Heist et al., 2009) conducted to study dispersion of emissions from three depressed roadway configurations; a 6 m deep depressed roadway with vertical sidewalls, a 6 m deep depressed roadway with 30° sloping sidewalls, and a 9 m deep depressed roadway with vertical sidewalls. The width of the road at the bottom of the depression is 36 m for all cases. All these configurations induce complex flow fields, increase turbulence levels, and decrease surface concentrations downwind of the depressed road compared to those of the at-grade configuration. The parameters of flat terrain dispersion models are modified to describe concentrations measured downwind of the depressed roadways. In the first part of the paper, a flat terrain model proposed by van Ulden (1978) is adapted. It turns out that this model with increased initial vertical dispersion and friction velocity is able to explain the observed concentration field. The results also suggest that the vertical concentration profiles of all cases under neutral conditions are best explained by a vertical distribution function with an exponent of 1.3. In the second part of the paper, these modifications are incorporated into a model based on the RLINE (Snyder et al., 2013) line-source dispersion model. While this model can be adapted to yield acceptable estimates of near-surface concentrations (z< 6m) measured in the wind tunnel, the Gaussian vertical distribution in RLINE, with an exponent of 2, cannot describe the concentration at higher elevations. Our findings suggest a simple method to account for depressed highways in models such as RLINE and AERMOD through two parameters that modify vertical plume spread.

Reduction of air pollution levels downwind of a road with an upwind noise barrier.

We propose a dispersion model to estimate the impact of a solid noise barrier upwind of a highway on air pollution concentrations downwind of the road. The model, based on data from wind tunnel experiments conducted by Heist et al. (2009), assumes that the upwind barrier has two main effects: 1) it creates a recirculation zone behind the barrier that sweeps the emissions from the highway back towards the wall, and 2) it enhances vertical dispersion and initial mixing. By combining the upwind barrier model with the mixed wake model for a downwind barrier described in Schulte et al. (2014), we are able to model dispersion of emissions from a highway with noise barriers on both sides. The model provides a good description of measurements made in the wind tunnel. The presence of an upwind barrier causes reductions in concentrations relative to those measured downwind of a road with no barriers. The reduction can be as large as that caused by a downwind barrier if the recirculation zone covers the width of the highway. Barriers on both sides of the highway result in larger reductions downwind of the barriers than those caused by a single barrier either upwind or downwind. As expected, barrier effects are small beyond 10 barrier heights downwind of the highway. We also propose a tentative model to estimate on-road concentrations within the recirculation zone induced by the upwind barrier.

Air quality modeling in support of the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS).

A major challenge in traffic-related air pollution exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related air pollutants and adverse health outcomes. A hybrid air quality modeling approach was used to estimate exposure to traffic-related air pollutants in support of the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS) conducted in Detroit (Michigan, USA). Model-based exposure metrics, associated with local variations of emissions and meteorology, were estimated using a combination of the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) and Research LINE-source dispersion model for near-surface releases (RLINE) dispersion models, local emission source information from the National Emissions Inventory, detailed road network locations and traffic activity, and meteorological data from the Detroit City Airport. The regional background contribution was estimated using a combination of the Community Multi-scale Air Quality (CMAQ) and the Space-Time Ordinary Kriging (STOK) models. To capture the near-road pollutant gradients, refined "mini-grids" of model receptors were placed around participant homes. Exposure metrics for CO, NOx, PM2.5 and its components (elemental and organic carbon) were predicted at each home location for multiple time periods including daily and rush hours. The exposure metrics were evaluated for their ability to characterize the spatial and temporal variations of multiple ambient air pollutants compared to measurements across the study area.

Screening level assessment of risks due to dioxin emissions from burning oil from the BP Deepwater Horizon Gulf of Mexico spill.

Between April 28 and July 19 of 2010, the U.S. Coast Guard conducted in situ oil burns as one approach used for the management of oil spilled after the explosion and subsequent sinking of the BP Deepwater Horizon platform in the Gulf of Mexico. The purpose of this paper is to describe a screening level assessment of the exposures and risks posed by the dioxin emissions from these fires. Using upper estimates for the oil burn emission factor, modeled air and fish concentrations, and conservative exposure assumptions, the potential cancer risk was estimated for three scenarios: inhalation exposure to workers, inhalation exposure to residents on the mainland, and fish ingestion exposures to residents. U.S. EPA's AERMOD model was used to estimate air concentrations in the immediate vicinity of the oil burns and NOAA's HYSPLIT model was used to estimate more distant air concentrations and deposition rates. The lifetime incremental cancer risks were estimated as 6 × 10(-8) for inhalation by workers, 6 × 10(-12) for inhalation by onshore residents, and 6 × 10(-8) for fish consumption by residents. For all scenarios, the risk estimates represent upper bounds and actual risks would be expected to be less.

The effect of a tall tower on flow and dispersion through a model urban neighborhood: part 1. Flow characteristics.

Wind tunnel experiments were performed to examine the effect of a tall tower on the flow around an otherwise uniform array of buildings. Additionally, preliminary CFD simulations were run to visualize the flow with more resolution. The model used in both the wind tunnel and CFD studies was designed to simulate an area of Brooklyn, NY, USA, where blocks of residential row houses form a neighborhood bordering a major urban highway. This area was the site of a field study that, along with the work reported here, had the goal of improving the understanding of airflow and dispersion patterns within urban microenvironments. Results reveal that a tall tower has a dramatic effect on the flow in the street canyons in the neighboring blocks, enhancing the exchange between the street canyon flow and the freestream flow aloft. In particular, vertical motion down the windward side and up the leeward side of the tower resulted in strong flows in the lateral street canyons and increased winds in the street canyons in the immediate vicinity of the tower. These phenomena were visible in both the wind tunnel and CFD results, although some minor differences in the flow fields were noted.

The effect of a tall tower on flow and dispersion through a model urban neighborhood: part 2. Pollutant dispersion.

This article is the second in a two-paper series presenting results from wind tunnel and computational fluid dynamics (CFD) simulations of flow and dispersion in an idealized model urban neighborhood. Pollutant dispersion results are presented and discussed for a model neighborhood that was characterized by regular city blocks of three-story row houses with a single 12-story tower located at the downwind edge of one of these blocks. The tower had three significant effects on pollutant dispersion in the surrounding street canyons: drawing the plume laterally towards the tower, greatly enhancing the vertical dispersion of the plume in the wake of the tower, and significantly decreasing the residence time of pollutants in the wake of the tower. In the wind tunnel, tracer gas released in the avenue lee of the tower, but several blocks away laterally, was pulled towards the tower and lifted in the wake of the tower. The same lateral movement of the pollutant was seen in the next avenue, which was approximately 2.5 tower heights downwind of the tower. The tower also served to ventilate the street canyon directly in its wake more rapidly than the surrounding areas. This was evidenced by CFD simulations of concentration decay where the residence time of pollutants lee of the 12-story tower was found to be less than half the residence time behind a neighboring three-story building. This same phenomenon of rapid vertical dispersion lee of a tower among an array of smaller buildings was also demonstrated in a separate set of wind tunnel experiments using an array of cubical blocks. A similar decrease in the residence time was observed when the height of one block was increased.

Methodology for siting ambient air monitors at the neighborhood scale.

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.