Depressed Roadways

This data set is associated with the results found in the journal article: Amini et al, 2018. Modeling Dispersion of Emissions from Depressed Roadways. Authors: Seyedmorteza Amini, Faraz Enayati Ahangar, David K. Heist, Steven G. Perry, Akula Venkatram. This paper presents an analysis of data from a wind tunnel study of 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. 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 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. This dataset is associated with the following publication: Amini, S., F. Ahangar, D. Heist, S. Perry, and A. Venkatram. Modeling Dispersion of Emissions from Depressed Roadways. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 186: 189-197, (2018).

[
  "020:00"
]

[
  "020:094"
]

[
  "https://doi.org/10.1016/j.atmosenv.2018.04.058"
]