Urban outdoor ventilation and pollutant dispersion have important implications for urban design and planning. In this paper, two urban morphology parameters, i.e. the floor area ratio (FAR) and the building site coverage (BSC), are considered to investigate their quantitative correlation with urban ventilation indices. An idealized model, including nine basic units with FAR equal to 5, is considered and the BSC is increased from 11% to 77%, generating 101 non-repetitive asymmetric configurations, with attention to the influence of plan density, volume ratio, and building layout on ventilation performance within urban plot areas. Computational Fluid Dynamics (CFD) simulations are used to assess the ventilation efficiency at pedestrian level (2m above the ground) within each model central area. Six indices, including the air flow rate (Q), the mean age of air (τ_P), the net escape velocity (NEV), the purging flow rate (PFR), the visitation frequency (VF), and the resident time (TP) are used to assess the local ventilation performance. Results clearly show that, fixing the FAR, the local ventilation performance is not linearly related to BSC, but it also depends on buildings arrangement. Specifically, as the BSC increases, the ventilation in the central area does not keep reducing. On the contrary, some forms with low BSC have poor ventilation and some particular configurations with high BSC have better ventilation, which indicates that not all high-density configurations experience poor ventilation. The local ventilation performance can be effectively improved by rationally arranging the buildings. Even though the application of these results to real cities requires further research, the present findings suggest a preliminary way to build up a correlation between urban morphology parameters and ventilation efficiency tailored to develop a feasible framework for urban designers.

With the sustainability of contemporary cities gaining more and more attention, interest in the correlation between urban geometry and urban microclimate is increasing. On this basis, this paper aims to investigate the quantification of geometric characteristics of urban space. Based on a combination of easily accessible software packages, a quantitative method composed of spatial partition, spatial characteristic indices (area, shape, and openness), and a spatial classification chart is proposed for the study of the correlation between urban spatial geometry and urban microclimate. Two blocks with different spatial geometric characteristics of the Xinjiekou central area in Nanjing are selected as the cases to verify the operability and effectiveness of this method. The results reveal that complex real urban space can be quantitatively described and classified by this spatial quantification method. In addition, a possible correlation between urban spatial geometry and urban wind environment is demonstrated by using the method, which may also be applicable to the correlation study between urban spatial geometry and other environmental issues.

Correlation research on urban space and pedestrian–level wind (PLW) environments is helpful for improving the wind comfort in complex urban space. It could also be significant for building and urban design. Correlation research is usually carried out in a space with clear urban spatial characteristics, so it is necessary to define the space first. In this paper, a typical urban area in Nanjing, China, is selected as the research object, and a spatial partition method is used to divide the real complex urban space into subspaces. The urban spatial characteristics of such subspaces are quantified using three urban spatial indices: openness (O), area (A), and shape (S). By comparing the quantitative results, 24 (12 pairs) subspaces with prominent urban spatial indices are selected as the correlation research cases. The 24 subspaces also provide a reference for the layout of the measurement points in a wind tunnel experiment. This is a new arrangement for locating the measurement points of a wind tunnel for correlation research. In the experiment, 45 measurement points are located, and the mean wind velocity of four different wind directions at 45 measurement points is experimented. The results clearly show that, when the experimental conditions are the same, the changes of mean wind velocity ratio ( $\overline{{\mathrm{U}}_{\mathrm{R}}}$ ) of 24 (12pairs) subspaces under the four experimental wind directions are close. The $\overline{{\mathrm{U}}_{\mathrm{R}}}$ s of the subspaces are not significantly affected by the wind direction, which is affected more by the subspaces’ spatial characteristics. When making the correlation analysis between mean wind speed ratio and spatial characteristics’ indices, a direct numerical comparison was not able to find a correlation. By comparing the difference values of mean wind speed (△ $\overline{{\mathrm{U}}_{\mathrm{R}}}$ ) and indices between each pair of subspaces, the correlation between $\overline{{\mathrm{U}}_{\mathrm{R}}}$ and openness of subspaces were found. Limited by spatial partition method, the correlation between $\overline{{\mathrm{U}}_{\mathrm{R}}}$ and the other indices was not obvious.