Research has demonstrated that urban green spaces play a crucial role in mitigating the severe urban heat island (UHI) effect. However, existing studies often suffer from limitations such as the neglect of the cooling effect of water bodies within the green spaces and incomplete considerations of the overall cooling effect. These limitations may lead to inaccuracies in the research findings. Therefore, the present study takes the city of Xi’an as a case study to explore the optimal green space size for achieving efficient cooling. The results indicate that (i) urban green spaces exhibit robust cooling effects, with variations observed among the various types; (ii) for community parks without water, and for street gardens, the optimal areas of these green spaces are 3.44 and 0.83 hectares, respectively; (iii) for community parks with water, the area of internal water bodies should ideally be maintained at around 29.43% of the total green space area in order to achieve an optimal cooling efficiency. In conclusion, this study introduces a new perspective and new optimization methods for urban green space planning, thereby offering scientific guidance to urban planners in formulating effective development and management policies and urban planning schemes.

Heavy metal (HM) contamination in arid inland river basins is intensifying with economic development, posing ongoing ecological and public health risks. Conventional monitoring is constrained by landscape heterogeneity and limited field data, hindering basin-scale spatiotemporal analysis. This study integrates multispectral Sentinel‑2A imagery, Random Forest (RF) regression, and harmonized ground observations to quantify and map As, Cd, Cu, Pb, and Zn in soils and waters of China’s Tarim River Basin (TRB), and to evaluate related health risks using the EPA model. Field data showed soil ΣHMs averaged 118.71 mg kg⁻¹ (95.15–191.32 mg kg⁻¹) and river ΣHMs 3.89 µg L⁻¹ (1.14–99.00 µg L⁻¹), with Cd and As above background levels. RF models yielded preliminary spatial patterns (R² = 0.741–0.999; RMSE = 0.12–0.38 mg kg⁻¹ for soils, 0.21–0.57 µg L⁻¹ for waters). Spatial patterns revealed As and Cd hotspots in Aksu, Cu and Pb enrichment in central and southeastern sub‑basins, and Zn predominance in the east. Pearson correlation and principal component analyses attributed Pb–Cu–Zn mainly to natural sources and riverine metals to atmospheric deposition and hydrology. Oral ingestion was the major exposure route; ~10% of soil samples exceeded the non‑carcinogenic hazard index for children, while As and Cd posed carcinogenic risks > 1 × 10⁻⁴. The geo‑accumulation index (I_geo > 2 for As) and HPI > 100 in Hotan, Kashgar, and Aksu indicated localized hazards. Recommended actions include RS‑based quarterly monitoring, targeted As/Cd control, basin‑wide HM coordination, child health screening, and nature‑based remediation to reduce HM risks by 2035. This work provides the first high-resolution, basin-wide HM assessment in the TRB, demonstrating Sentinel-2A-RF inversion as a cost-effective tool for hotspot identification, risk-informed management, and alignment with China’s dual-carbon goals, rural revitalization, and UN Sustainable Development Goals.

The wind environment in residential areas can exert a direct or indirect influence on the spread of epidemics, with some scholars paying particular attention to the epidemic prevention and control of residential areas from the perspective of wind environments. As a result, it is urgent to re-examine the epidemic prevention response of residential spaces. Taking high-rise residential areas in Xi’an as an example, the article defines the air flow field area based on on-site wind environment measurements, crowd behavior annotation, and CFD simulation. Using the double-effect superposition of crowd behavior and risk space, the paper undertook a multiple identification strategy of epidemic prevention space. The identification methods and management and control strategies of epidemic prevention in high-rise residential areas are proposed. Additionally, the living environment of residential areas is optimized, and a healthy residential space is created. The transformation from concept and calls for action to space implementation is made to provide a reference for improving the space management and control capabilities in high-rise residential areas in China. The results of this study can be used as a guideline for future residential planning and design from the perspective of preventing airborne diseases.

Under intensifying climate change and increasingly frequent extreme heat events, improving outdoor thermal environments has become critical for sustainable human settlements. While prior studies have mainly focused on urban contexts, systematic investigations of rural microclimates—particularly regarding the regulatory mechanisms of landscape configurations—remain limited. This study examines a mountain-adjacent village in the Loess Tableland region of China, integrating field measurements with ENVI-met simulations to analyze thermal characteristics of rural road spaces and the effects of vegetation and paving materials on human thermal comfort. The results show that village boundary areas experience the largest fluctuations in air temperature and relative humidity during midday and evening, indicating higher thermal sensitivity. Model validation demonstrates satisfactory accuracy, with RMSE values of 0.39–3.62 °C for air temperature, 1.32–3.22% for relative humidity, and 1.35–2.24 m/s for wind speed, and MAPE ranging from 0.80% to 9.05%. Furthermore, Basalt Brick and Populus alba show the best cooling performance, but when considering multiple factors such as temperature, humidity, and wind speed, Ligustrum lucidum has the most significant effects in improving thermal comfort and increasing humidity. Analysis based on Physiological Equivalent Temperature (PET) further indicates that vegetation configurations play a more substantial role in thermal comfort regulation than paving materials, and that different landscape elements exhibit synergistic and trade-off relationships in terms of cooling, humidification, and ventilation. This study provides quantitative reference for vegetation configuration and material selection in rural roads within the Loess Tableland region and similar semi-arid areas, enriches the research scope of rural microclimate studies, and offers scientific support for climate-adaptive rural planning and optimization of rural living environments.

A significant transition is taking place in China’s urban development, which is moving away from rapid expansion and towards improved quality and efficiency. The distribution of primary education resources is thus experiencing a substantial change: transitioning from a traditional emphasis on merely providing school placements to becoming a systematic effort intricately linked with the functional attributes of adjacent urban environments. Nonetheless, current research has not comprehensively examined the relational dynamics between primary schools and adjacent facilities, nor the discrepancies in these dynamics across various cities. This study analyzes nine major Chinese cities as case studies to investigate the compatibility between elementary schools and adjacent infrastructure. It develops a compatibility model through data gathering, feature selection, and model validation. Significant findings indicate the following: (1) The models trained using several machine learning methods to assess the suitability of primary schools in nine cities for their surrounding facilities all obtained accuracy rates surpassing 72%, with Random Forest displaying the most consistent performance across several cities. (2) Developed cities prioritize spatial coordination among schools, with the SHAP feature representing 20.37% of its significance; conversely, less developed cities exhibit a stronger inclination towards coordinated placement with educational and training facilities, where the SHAP feature constitutes 20.52% of its significance. (3) The compatibility of primary schools with surrounding facilities suggests that Guangzhou, Zhengzhou, and Chongqing possess considerable prospective need for education, whereas the existing distribution in Beijing, Shanghai, and Tianjin is rather well-structured. This study provides a novel, data-driven framework for optimizing educational resource allocation, offering critical insights for achieving sustainable urban development and quality education in China’s cities as they evolve.