Evaluation of the Relationship between Momentum Wakes behind Moving Vehicles and Dispersion of Vehicle Emissions Using Near-Roadway Measurements

Abstract

A parameterization of initial vertical dispersion coefficient (σ z,init) was developed for incorporation into California line source dispersion model, version 4 (CALINE4) and AMS/EPA regulatory model (AERMOD) to better predict pollutant concentrations near roadways. The momentum wake theory of moving vehicles indicates that both vehicle-induced turbulence (VIT) and dispersion occur in the vehicle wake. Based on a literature review, it is postulated that σ z,init near roadways can be estimated using a “wake area model” concept of effective wake area defined as the vehicle height times the wake length, vehicle density, and vehicle type. A total of 523 5-min near-roadway simultaneous measurements (2016–2018) of pollutant concentrations and meteorological and traffic information were used to evaluate the model. Two roadways with distinct fleet composition and simple road configurations were selected for monitoring. The near-roadway σ z,init ranged from 1 to 4 m for light-duty vehicles (LDVs) and from 3 to 7 m for fleet-mix (LDVs and heavy-duty vehicles (HDVs)). The results demonstrate that the dispersion contribution from one HDV was 31 times larger than that from one LDV. Calculated pollutant dispersion using the wake area model compared favorably with measurements (R 2 = 0.91, slope = 1.07). These results indicate that σ z,init varies with vehicle density and HDVs. Pollutant dispersion related to the vehicle wakes can be used to correctly parameterize dispersion models and improve prediction of pollutant concentrations near roadways.

Development and Evaluation of SLINE 1.0, a Line Source Dispersion Model for Gaseous Pollutants by Incorporating Wind Shear Near the Ground under Stable and Unstable Atmospheric Conditions

“…The Transition Phase includes the effect of thermal turbulence, vehicular turbulence, and atmospheric turbulence. This phase is assumed from the downwind distances of 6.5 m to 50 m. The value of 50 m will depend on the type of vehicles on the highway and could be as high as 150 m for large trucks, as pointed by Yu et al [37]; c.…”

“…The values of σ z0 obtained from the above four procedures for a test case are shown in Table 2 using the width of the road as 3.5 m. The wind velocity considered was 1.4 m/s, the wind angle concerning the road was taken as 90 • , and the average height of the vehicle was H = 1.65 m. The effective wake length was considered as 9.3 m, and the vehicle density on the roadway was 0.125 vehicles/m. [37,[40][41][42].…”

“…Other methods have been used to define stability class, including Monin-Obukhov length, Richardson number, Bulk Richardson number, fluctuations in wind direction, and temperature gradient. Benson [40] and the Wake area model by Yu et al [37] use P-G stability classes, AERMOD [41] uses the surface roughness length and the Monin-Obukhov length, and Chock [42] uses the Richardson Number to define stability class. Therefore, care should be taken in comparing the methods given in Table 2.…”

Variability of NO2/NOx Ratios in Multiple Microenvironments from On-Road and Near-Roadway Measurements

“…By conducting field measurement , and simulation, researchers concluded that VIT and RIT dominate on-road turbulent mixing, while ABLT dominates turbulent mixing at downwind locations (near-roadway). Researchers also found that HDDVs produce much larger and stronger turbulent mixing than light-duty gasoline vehicles (LDGVs) , and the strength of the turbulent mixing was more correlated to HDDVs than to LDGVs. ,, Besides effects from turbulent mixing, a recent study found that the NO 2 /NO x ratios measured at curbside were less sensitive to ambient background O 3 , which is probability because of the limited amount of available O 3 (not titrated) in the curbside environment.…”

NOx and CO Fluctuations in a Busy Street Canyon

“…The ventilation within the canyon may be suppressed [9], and vortices can leave dead zones with stagnant air [2]. Sometimes, slow-moving, heavy traffic along the roads at the canyon bottom exhausts large amounts of primary pollutants and generates turbulence [10]. Typically, ozone (O 3 ) is a limiting factor for the oxidation of nitric oxide (NO) to nitrogen dioxide (NO 2 ) [11], making the contribution of primary NO 2 important.…”