On the application and grid-size sensitivity of the urban dispersion model CAIRDIO for the simulation of a real city and realistic meteorology
Abstract. There is a gap between the need for city-wide air-quality simulations considering the intra-urban variability and mircoscale dispersion features and the computational capacities that conventional urban microscale models require. This gap can be bridged by targeting model applications on the gray zone situated between the mesoscale and large-eddy scale. The urban dispersion model CAIRDIO is a new contribution to the class of computational-fluid dynamics models operating in this scale range. It uses a diffuse-obstacle boundary method to represent buildings as physical obstacles at gray-zone resolutions in the order of tens of meters. The main objective of this approach is to find an acceptable compromise between computationally inexpensive grid sizes for spatially comprehensive applications and the required accuracy in the description of building and boundary-layer effects. For this purpose, CAIRDIO is applied in dispersion simulation of black carbon and particulate matter for an entire mid-size city using an uniform horizontal resolution of 40 m in this paper. For evaluation, the simulation results are compared with measurements from 5 operational air monitoring stations, which are representative for the urban background and high-traffic roads, respectively. Moreover, the comparison includes the mesoscale host simulation, which provides the boundary conditions. The temporal variability of the concentration measurements at the background sites was largely influenced only by the characteristics of the mixing layer. As a consequence, the model results were not significantly dependent on spatial resolution, so that the mesoscale simulation also performed reasonably well. At the traffic sites, however, concentrations were in addition markedly influenced by the proximity to road-traffic sources and the surrounding building environment. Here, the mesoscale simulation indiscriminately reproduced almost the same urban-background profiles, which resulted in a large positive model bias. On the other hand, the CAIRDIO simulation was able to respond to the significantly amplified diurnal variability with its pronounced rush-hour peaks. This resulted in a consistent improvement of the model deviation to mea- surements compared to the mesoscale simulation. Nevertheless, discrepancies to measurements remain in the 40 m-CAIRDIO simulation, e.g., an underestimation of peak concentrations at two traffic sites inside narrow street canyons. To further research resolution sensitivity, the horizontal grid spacing of locally nested CAIRDIO domains is refined down to 5 m. While for the street canyons the representation of peak concentrations can be improved using horizontal grid spacings of up to 10 m, no further improvements beyond this resolution can be observed. This suggests that the too low peak concentrations with the default grid spacing of 40 m result from an inadequate representation of the traffic emissions inside narrow street canyons. If the total gain in accuracy due to the grid refinements is put in relation to the remaining model error, the improvements are only modest. In conclusion, the proposed gray-scale modeling is a promising downscaling approach for urban air-quality applications. Nevertheless, the results also show that aspects other than the actual resolution of flow patterns and numerical effects can determine the simulations at the urban microscale.
