Impacts of Realistic Urban Heating. Part II: Air Quality and City Breathability

Abstract

Urban morphology and inter-building shadowing result in a non-uniform distribution of surface heating in urban areas, which can significantly modify the urban flow and thermal field. In Part I, we found that in an idealized three-dimensional urban array, the spatial distribution of the thermal field is correlated with the orientation of surface heating with respect to the wind direction (i.e. leeward or windward heating), while the dispersion field changes more strongly with the vertical temperature gradient in the street canyon. Here, we evaluate these results more closely and translate them into metrics of “city breathability,” with large-eddy simulations coupled with an urban energy-balance model employed for this purpose. First, we quantify breathability by, (i) calculating the pollutant concentration at the pedestrian level (horizontal plane at $z\approx 1.5$–2 m) and averaged over the canopy, and (ii) examining the air exchange rate at the horizontal and vertical ventilating faces of the canyon, such that the in-canopy pollutant advection is distinguished from the vertical removal of pollution. Next, we quantify the change in breathability metrics as a function of previously defined buoyancy parameters, horizontal and vertical Richardson numbers ($Ri_\text {h}$ and $Ri_\text {v}$, respectively), which characterize realistic surface heating. We find that, unlike the analysis of airflow and thermal fields, consideration of the realistic heating distribution is not crucial in the analysis of city breathability, as the pollutant concentration is mainly correlated with the vertical temperature gradient ($Ri_\text {v}$) as opposed to the horizontal ($Ri_\text {h}$) or bulk ($Ri_\text {b}$) thermal forcing. Additionally, we observe that, due to the formation of the primary vortex, the air exchange rate at the roof level (the horizontal ventilating faces of the building canyon) is dominated by the mean flow. Lastly, since $Ri_\text {h}$ and $Ri_\text {v}$ depend on the meteorological factors (ambient air temperature, wind speed, and wind direction) as well as urban design parameters (such as surface albedo), we propose a methodology for mapping overall outdoor ventilation and city breathability using this characterization method. This methodology helps identify the effects of design on urban microclimate, and ultimately informs urban designers and architects of the impact of their design on air quality, human health, and comfort.

Appendix 1: Supplementary Information on Model Validation

The energy balance model (the TUF-IOBES model) by Yaghoobian and Kleissl (2012) has been validated by comparing the change of modelled interior wall temperature in response to a step change in outside air temperature with an analytical solution as well as other models. The difference between the analytical solution and the TUF-IOBES model indicated a 2.3% error, which was lower than other numerical models, including the 5% difference reported for the CBS-MASS model (Zmeureanu et al. 1987).

The PALM model for unstable flow in the urban canopy was validated by Park et al. (2012) against the wind-tunnel data of Uehara et al. (2000). The agreement in the vertical profiles of the normalized streamwise horizontal velocity component and temperature supported the validity of the temperature wall function in the PALM model. The normalized scalar concentration simulated using the PALM model was successfully validated against wind-tunnel data of Meroney et al. (1996) with $R^2=0.97$.

The coupling of the TUF-IOBES and PALM models was validated against data from the wind-tunnel experiment of Kovar-Panskus et al. (2002) for a 2-D street canyon with a heated windward wall, and also compared with the LES results of Cai (2012). Both numerical studies showed that based on mass conservation (downward mass flux into the canyon near the windward wall equals the upward mass flux out of the canyon near the leeward wall) the primary vortex should be shifted to the right, which is different from the sketch provided by Kovar-Panskus et al. (2002) and renders this portion of the experimental data questionable. The agreement with the Cai (2012) numerical simulation is encouraging.

Additionally, in Part I the quadrant analysis obtained by large-eddy simulation is compared with the direct numerical simulation of aligned arrays of cubes at $Re_\mathrm{H}=5800$ for a neutral case performed by Coceal et al. (2007a) and showed close agreement in the shape of the quadrants, the frequency of events, as well as the value of exuberance at heights 0.5H and 1.5H at the centre of the canyon.