Effects of atmospheric stratification on flow and dispersion in the urban environment.

Abstract

Atmospheric stratification involves differences in the air density caused by a positive (stable) or negative (unstable) vertical gradient of virtual potential temperature. The stability of the layer depends on the stratification and affects the atmospheric boundary layer depth and structure as well as velocity, temperature and turbulence properties. In the first phase of the work, artificially thickened stable and unstable boundary layers were simulated in the EnFlo wind tunnel over a very rough surface, by means of spires, roughness elements and heaters. The effect of different parameters was investigated (among them, inlet temperature profile, capping inversion and surface roughness). These boundary layers were then employed as approaching flow for two idealised urban model geometries. A regular array of rectangular blocks was considered as geometry while a pollutant tracer was released from a point source at ground level. Mean and fluctuating velocities, temperatures and concentrations were sampled, together with heat and pollutant fluxes. The analysis of the data revealed that even in case of weak stratification there are important modifications inside and above the canopy on both the urban boundary layer and the plume characteristics. Finally, the combined effects of a stable approaching flow and local surface heating were investigated in a bi-dimensional street canyon geometry. This was an entirely novel experimental design and the results highlighted how both local and incoming stratification can significantly affect the flow and dispersion at a microscale level in a complex way that depends on the particular case of study. This work sheds more light on the effects of stratification and encourages further work on the topic. The experimental database produced during the project is unique and of high quality. It can assist in developing, improving and validating numerical models, as well as developing parametrisations for simpler models.