Mitigating heat stress in high-density historical districts remains a critical challenge in urban renewal due to complex morphological heterogeneity. Existing research often relies on isolated intervention measures, lacking systematic, multi-strategy assessments driven by high-precision spatial data. This study addresses this gap by establishing a quantitative framework that couples thermal infrared remote sensing with Computational Fluid Dynamics (CFD) to optimize microclimate responses in Beijing’s Liulichang Historic District. Remote sensing data were utilized to retrieve high-resolution Land Surface Temperature (LST), providing accurate thermal boundary conditions for micro-scale wind-thermal simulations. A baseline scenario (S0) and seven renewal strategies (S1–S7)—integrating varying configurations of greenery, water bodies, and permeable pavements—were evaluated using pedestrian-level comfort indices. Results reveal that single-factor interventions yield marginal improvements or thermodynamic trade-offs; specifically, adding greenery (S1) in narrow street canyons increased aerodynamic roughness, thereby obstructing ventilation and inducing localized warming. Conversely, composite strategies significantly enhanced microclimatic quality. The “greenery-water-permeable pavement” strategy (S4) achieved optimal synergistic effects, characterized by substantial cooling and spatial homogenization. Regression analysis identified water bodies as the dominant cooling driver, where a 10% increase in water coverage resulted in a temperature reduction of approximately 5.17 °C. Conversely, greenery alone showed no statistically significant cooling contribution (p > 0.05) without the synergistic presence of water or pavement modifications. This research suggests that urban renewal in high-temperature zones (>36 °C) should prioritize composite cooling networks. Furthermore, vegetation layouts near wind corridors must be precisely regulated to prevent ventilation degradation. These findings provide a scientific basis for the climate-adaptive sustainable regeneration of culturally significant, high-density urban blocks.
Huo et al. (Tue,) studied this question.
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