This study numerically investigates the influence of different vegetation types and layouts on microclimate and air quality in residential districts based on the morphology and green layout of Nanjing, China. Simulations were performed using Computational Fluid Dynamics and the microclimate model ENVI-met. Four green indices, i.e., the green cover ratio, the grass and shrub cover ratio, the ecological landscaping plot ratio and the landscaping isolation index, were combined to evaluate thermal and wind fields, as well as air quality in district models. Results show that under the same green cover ratio (i.e., the same quantity of all types of vegetation), the reduction of grass and shrub cover ratio (i.e., the quantity of grass and shrubs), replaced by trees, has an impact, even though small, on thermal comfort, wind speed and air pollution, and increases the leisure space for occupants. When trees are present, a low ecological landscaping plot ratio (which expresses the weight of carbon dioxide absorption and is larger in the presence of trees) is preferable due to a lower blocking effect on wind and pollutant dispersion. In conjunction with a low landscaping plot ratio, a high landscaping isolation index (which means a distributed structure of vegetation) enhances the capability of local cooling and the general thermal comfort, decreasing the average temperature up to about 0.5 °C and the average predicted mean vote (PMV) up to about 20% compared with the non-green scenario. This paper shows that the relationship vegetation-microclimate-air quality should be analyzed taking into account not only the total area covered by vegetation but also its layout and degree of aggregation.

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.

This paper explores the method of assessing regional spatial ventilation performance for the design of residential building arrangements at an operational level. Three ventilation efficiency (VE) indices, Net Escape Velocity (NEV), Visitation Frequency (VF) and spatial-mean Velocity Magnitude (VM), are adopted to quantify the influence of design variation on VE within different regional spaces. Computational Fluid Dynamics (CFD) method is applied to calculate VE indices mentioned above. Several residential building arrangement cases are set to discuss the effect of different building length, lateral spacing and layouts on four typical space patterns under wind directions oblique or perpendicular to the main (long) building facade. The simulation results prove that NEV, VF and VM are useful VE indices, which can reflect different features of flow pattern in studied regional domains. Preliminary parametric studies indicate that wind direction might be the most important factor for improving spatial ventilation. When the angle between main building facade and wind direction is more than 30°, ventilation of different exterior spaces could improve evidently. When wind direction is perpendicular to main building façade, decreasing building length can increase NEV of the middle space by 50%, while decreasing lateral spacing would decrease NEV of the intersection space by 35%.

Using computational fluid dynamic (CFD) simulations, the correlation between residential building arrangement designs and ventilation efficiency of various outdoor spaces is explored. Three indices—purging flow rate (PFR), visitation frequency (VF) and air residence time (T_p)—are adopted to quantify the ventilation efficiency of regional outdoor spaces. Using these indices, changes in residential building lateral spacing, building length, and stagger size were investigated under the effects of different surrounding building arrays for different wind directions. The simulation results indicated that wind direction is the most important factor for improving the residential wind environment, regardless of the patterns of the surrounding building arrays. When the angle between the wind direction and the building’s main façade orientation is more than 30°, the ventilation of different outdoor spaces improves. Staggered surrounding building arrays lower the spatial ventilation of the studied areas. However, this staggering does not affect the variation trend of spatial ventilation influenced by building arrangement design changes.

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.