8A.8 Analysis of Vehicle-Induced Turbulence on a Highway

Wednesday, 13 June 2018: 9:45 AM
Ballroom D (Renaissance Oklahoma City Convention Center Hotel)
Pietro Breviglieri, Univeristy of Trento, Trento, Italy; and L. Giovannini, M. Falocchi, and D. Zardi

Emissions from traffic represent one of the main sources of air pollutants and may cause serious environmental and health problems, especially for people living close to roadways. The correct modeling of the dispersion from near-surface mobile source emissions depends on many aspects, including the adequate representation of the mean wind and of the turbulence fields close to the road.

Turbulence in the close proximity to roadways is strongly influenced by the traffic itself, which represents an additional source of turbulence and may enhance pollutants’ dispersion. In order to evaluate turbulence statistics and in particular the vehicle-induced turbulence adjacent to a highway, a field campaign was carried out during the winter and spring 2018, using two HS-100 Gill sonic anemometers, sampling at 20 Hz. Sonic anemometers were located at 3 and 8 m above ground level (AGL), at a horizontal distance of 3 m from the highway (A22 highway, Italy). Detailed information on traffic intensity and composition was also available, so as to correlate turbulence statistics with vehicle fluxes.

As expected, observations highlight that turbulence statistics are strongly affected by the traffic flow along the highway, with different effects at the two different heights. In particular, a strong connection between traffic intensity and velocity and the turbulent kinetic energy (TKE) is found, especially for the lower anemometer. In fact, the analysis of TKE spectra highlights a significant energy increase for frequencies higher than 10-2 Hz, as traffic intensifies. Moreover, in high traffic situations TKE at 3 m AGL is significantly higher than at 8 m AGL. These effects are particularly evident in low wind speed conditions, while no significant influence of traffic on TKE is detected with strong winds. Based on these results, relationships between the increase of TKE and traffic intensity and velocity are derived.

Results found in the present work represent the basis for the derivation of a parameterization of vehicle-induced turbulence, which is going to be included in a dispersion model and tested against air quality data measured at different horizontal distances from the highway.

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