Modeling dispersion of emissions from depressed roadways

Abstract

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 < 6 m) 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.

Effects of wind speed and atmospheric stability on the air pollution reduction rate induced by noise barriers

“…Indeed, several authors have investigated the efficiency of noise barriers in reducing atmospheric pollutant concentrations behind the barriers using in-field (Baldauf et al, 2008(Baldauf et al, , 2016Finn et al, 2010;Hagler et al, 2012;Lee et al, 2018;Ning et al, 2010), wind tunnel (Heist et al, 2009) measurements and numerical models (Bowker et al, 2007;Hagler et al, 2011;Schulte et al, 2014). Some authors have studied the effects of barrier heights and distances on pollution reduction (Amini et al, 2018;Gong and Wang, 2018). Other authors have studied the effects of barrier shapes and locations on improving the reduction of atmospheric pollutants (Brechler and Fuka, 2014; 3/25 Enayati Ahangar et al, 2017;Wang and Wang, 2019).…”

Numerical Study of Noise Barriers’ Side Edge Effects on Pollutant Dispersion near Roadside under Various Thermal Stability Conditions

“…Noise barriers were originally designed to reduce moving vehicles' noise effects on roadside neighborhood. Studies have suggested that roadside barriers have positive effects on the reduction of downwind pollutant concentration [4][5][6][7][8][9][10][11][12][13][14]. The level of benefits can be influenced by many factors, such as roadway configuration, local meteorology, barrier height, or barrier edge design.…”

“…Most recently, Lee et al studied the combination of noise barrier and roadside vegetation effects on air pollution dispersion under various wind conditions, based on a field study in 2017 [12]. In 2018, Amini et al studied effects of different roadway configurations on near-road contaminant dispersion [13]. Generally, a noise barrier will carry the same length as the length of a roadway.…”