Influencing factors of urban wind environments in comprehensive functional areas along subway corridors

In the context of rapid urbanization, heat island effects and microclimate degradation caused by poor ventilation have become important challenges for sustainable urban development. Taking the comprehensive functional area along the Qingnian Street metro corridor in Shenyang, China, as the study area, this study combines multi-season CFD simulations, urban block morphological indicators, the XGBoost machine learning model, and the SHAP interpretability method to systematically evaluate the influence mechanisms of block-scale morphological factors on the near-ground wind environment. The results show that the wind environment in the study area exhibits significant seasonal variation and spatial heterogeneity. The area of stagnant-wind zones follows the order of summer > winter > autumn > spring. Ventilation conditions are relatively weak in the high-density blocks in the northern part of the study area, while comfortable wind zones are mainly distributed along major roads and open spaces in the southern part. Further analysis indicates that enclosure degree, sky view factor, frontal area index, building density, building height, building volume density, green space ratio, and impervious surface ratio are the main morphological factors affecting the wind environment, and their effects show obvious seasonal sensitivity. Highly enclosed urban forms significantly suppress ventilation in summer, whereas the winter wind environment is more dependent on the guidance of airflow by road networks and spatial openness. The SHAP marginal effect results further reveal the nonlinear responses and threshold characteristics of key morphological factors. For example, when the enclosure degree is approximately 2, building density is approximately 0.3, sky view factor is above 0.85, and green space ratio is above 0.3, the effects of some indicators on the wind environment change significantly. This study verifies the interpretability and applicability of the XGBoost-SHAP method in urban wind environment modeling, reveals the nonlinear influence mechanism of urban block morphology on the wind environment, and provides quantitative evidence and methodological references for high-density urban block planning oriented toward ventilation optimization and microclimate improvement.