## 3 Results
### Optimization of Microclimate Performance at Street Level  
In this section of the study, the optimization scope was adjusted to focus on street space instead of comfort inside the block. The calculation was stopped after the Galapagos module showed the numerical value was convergent and stable. The study lasted 31 h to obtain results of 948 generations, of which the data of 452 generations were valid (optimization target value was not 0). After the invalid data were removed, the change line of the optimization target value was drawn, as shown in Figure 13. The comfort index of the whole simulated area illustrated a continuous rising trend from 0 to 130 generations and tended to be stable with the calculation. Figure 11: Correlation results of average UTCI, MRT, and acceptable UTCI percentage at block level. Figure 12: Correlation results of average unacceptable wind percentage, average wind speed, and acceptable UTCI percentage at block level. Similarly, we selected two generations of morphology for each of the best and the worst, respectively, to reproduce the comfort level at street level, showed in Figure 14. The data indicated that through optimization, the overall comfort ratio of the block increased dramatically from 73.7% in the poorest case to 90.6%, an increase of about 23%. This indicated the optimization can effectively improve the microclimate comfort performance of the whole block combination by searching for the optimal combination of morphology. This study selected the generation results through optimization with higher than 85% of acceptable UTCI percentage to check the building form characteristics at street level, presented in Figure 15. Building form 1 and 2 occupied the top two positions of most locations (A1, A2, B1, B2, B3, C1, C2, and C3 location blocks). Building form 3 only occurred in high frequency at location A3, and building form 4 did not appear in any high-frequency block location. Furthermore, the total number occurring in these generations was significantly less than in the overall optimization, and form 5 did not appear in these generations either. Additionally, multistory building form 1 and 2 were chosen more frequently than high-rise 3 and 4 and open space 5. Figures 16-18 show the optimization results of building density, plot ratio, building enclosure, variation of building heights, and SVF, respectively. The overall density of the block decreased gradually between 0 and 120 generations and presented a steady state in subsequent generations. In terms of this trend, the high-density urban layout was beneficial to improving the microclimate comfort of outdoor streets during winter in cold areas. However, the change curve of plot ratio was disordered in general. The value of the first half was relatively small, while the value of the second half was relatively large. If reflected in the morphology, results indicate that the relatively high urban density was not conducive to improvement of thermal comfort of outdoor streets during winter, which was not in line  
Figure 14: Example optimization results at street level: the best optimization (left, street width: 20 m, acceptable UTCI percentage: 90.6%) and the worst optimization (right, street width: 30 m, acceptable UTCI percentage: 73.7%). Figure 13: Change trends in comfort ratios generated by Galapagos genetic algorithm at street level. with previous study conclusions. The speculated cause of the difference is that the form prototypes in this study contributing to improvement of plot ratio were basically high-rise buildings, and the wind environment around high-rise buildings is generally poor, with an adverse effect on outdoor thermal comfort. The change trend of mean SVF increased steadily with the decrease of comfort ratio, which indicated that the smaller SVF can improve the microclimate comfort of outdoor streets. In other words, the street space with a higher building enclosure degree was beneficial to improvement of the street's comfort performance in winter.