As a critical transportation infrastructure, high-speed rail (HSR) greatly enhances accessibility and shortens the spatial-temporal distance among cities. It is well documented that HSR significantly impacts regions and cities’ economic development and spatial structure. The proportion and frequency of business passenger trips are increasing yearly, and the demand for “station as the final destination” is becoming more and more prominent. Given the pivotal role of the design and construction of HSR station areas in achieving “station as the final destination,” the study of their development characteristics and patterns has important implications for urban planning. Previous studies have focused extensively on the macro impact of the HSR operation on regional economies, urban industries, and tourism development, whereas only a few were conducted at the station level. Furthermore, the business-commercial agglomeration effects of the HSR operation on the development and construction of station areas have neither been studied nor accurately measured. To fill this gap, we first constructed a panel data set consisting of the point of interest (POI) data, China City Statistical Yearbook data, and the HSR station operation data from 2012 to 2017. Next, we developed difference-in-differences (DID) models to decipher the impact of the HSR operation on the station-level business and commercial agglomeration. The results show that the HSR operation has increased the business-commercial agglomeration index (BCAI), the commercial agglomeration index (BAI), and the business agglomeration index (CAI) by 28.3%, 29%, and 21.3%, respectively. In other words, the HSR operation has significant business-commercial agglomeration effects in the station area, and the agglomeration effect size of business is more extensive than that of commerce. Interestingly, the BCAI grew slowly in the first 3 years after the HSR operation but started to rise much faster from the fourth year, which HSR’s catalytic effects can explain. The results also reveal that the business-commercial agglomeration effects have a clear spatial threshold as the BCAI tends to decrease from 1500 m to 3000 m away from HSR stations. The plausibility of the results has been confirmed by the parallel trend, placebo, and robustness tests.

In rapidly urbanizing regions, enhancing passenger comfort in subway systems through sustainable methods is a critical challenge. This study introduces an innovative exploration of the impact of subway entrance geometry on natural ventilation and its subsequent effects on the thermal environment within Cairo’s subway system. The primary objective is to identify optimal entrance configurations that maximize natural airflow, thereby improving passenger comfort and reducing energy consumption. Focusing on the newly constructed segments of the Cairo subway, the research employs a mixed-methods approach that integrates computational fluid dynamics (CFD) simulations with a questionnaire survey to evaluate interactions between various entrance designs and urban wind flow patterns. This dual approach allows for a comprehensive assessment of how different geometrical configurations influence the capture and distribution of prevailing winds. The results indicate that specific entrance geometries can significantly enhance ventilation efficiency by optimizing wind capture and distribution. The most effective designs demonstrated substantial improvements in air quality and thermal comfort, providing practical insights for subway systems in similar hot arid climates. The novelty of this research lies in its detailed analysis of architectural elements to leverage natural environmental conditions for improving indoor air quality and thermal comfort in public transit systems. The significance of this study is its contribution to the field of sustainable urban transport, offering a valuable framework for urban planners and engineers. By demonstrating how thoughtful design can lead to energy savings and enhanced passenger experiences, this research advances the discourse on sustainable urban infrastructure. This work not only enhances theoretical understanding but also provides actionable recommendations for creating more sustainable and comfortable public transit infrastructures.

The traditional residential courtyards in Xiaoyi Ancient City, Shanxi, are a typical architectural form demonstrating significant energy efficiency and climate adaptability. This research examines the climate adaptability of the traditional residential courtyards in Xiaoyi by conducting field measurements and quantitative analysis, and it suggests appropriate optimization strategies. The study concludes that the thermal comfort of the building can be significantly improved by the following factors: a south-facing orientation, central positioning of the inverted house, an enclosure degree of 0.85, a distance of 2400 mm between the main house and side house, a T-shaped courtyard proportions of 3:1, a linear courtyard proportions of 5:1, a U-shaped courtyard proportions of 3:1, an entrance porch proportions of 1.5:1, a gray space scale of 1200 mm under the main house eaves, 500 mm under the side house eaves, and window-to-wall proportion of 0.33 for the main house and 0.32 for the side house. This optimization not only enhances the energy efficiency of the building but also improves internal comfort, as it is based on climate-responsive design. In terms of the inheritance of traditional architectural wisdom and its modern application, this study emphasizes the significance of considering the climatic environment in building design, providing a theoretical foundation for renovating traditional residential and modern architectural design.

High-speed rail (HSR) station areas play a vital role in shaping urban form, stimulating economic activity, and enhancing spatial vitality. Understanding the factors that influence this vitality is key to supporting sustainable urban development and transit-oriented planning. This study investigates 66 HSR station areas in 35 Chinese cities by integrating multi-source data—Sina Weibo check-in records, urban support indicators, station attributes, and built environment variables—within a city–node–place analytical framework. Using Multiple Linear Regression (MLR) and Light Gradient Boosting Machine (LightGBM) models, we identify key drivers of spatial vitality, while SHAP analysis reveals nonlinear and interaction effects. The results show that city population size, urbanization level, commercial land use, transit accessibility, and parking facilities significantly enhance station area vitality. However, diminishing returns are observed when commercial land and bus stop densities exceed certain thresholds. The station location index shows a negative correlation with spatial vitality. The analysis of interaction effects highlights strong synergies between urban development and functional configuration, as well as between accessibility and service infrastructure. Different station types exhibit varied spatial patterns and require differentiated strategies. This study offers empirical insights for aligning transport infrastructure and land use planning, supporting the development of vibrant, accessible, and sustainable HSR station areas.

Subway-hub blocks are critical areas where the pressures of metropolitan populations and environmental quality are closely interconnected. This study constructs a “pressure–context–carrier–response” (PCRC) framework (F1–F7) to systematically reveal the correlations between built-environment characteristics and environmental performance. The results demonstrate that resource allocation (F7) and comprehensive response (F5) display notable “asymmetric differentiation”. The socio-economic environment (F2, F3) considerably influences the concentration of green-space resource allocations (F7) (p < 0.01), with affluent blocks demonstrating a clear advantage in resource distribution. The thermo-ecological composite response (F5), which includes NDVI and LST, demonstrates “statistical convergence” (p = 0.894) across various block types, indicating that resource inputs cannot be linearly transformed into environmental efficiency. This disconnection is ascribed to two physical limitations: firstly, the stochastic nature of spatial distribution (Global Moran’s I ≈ 0) restricts the scale effects of green spaces; secondly, the nonlinear limitations of the physical medium indicate that under conditions of high pressure load (F1) and elevated spatial capacity (F6), the regulatory effectiveness of greening demonstrates a significant diminishing marginal return effect. Therefore, intervention planning must shift from controlling macro-level indicators to optimising micro-level accuracy to address ecological performance constraints in densely populated metropolitan areas.