评估依赖尺度的城市风损失模式：1980 - 2020年现实城市段的CFD分析

IF 12 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society Pub Date : 2025-10-01 DOI:10.1016/j.scs.2025.106841

Ran Wang , Ziwei Mo , Di Mei , Wai-Chi Cheng , Kangcheng Zhou , Chun-Ho Liu

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引用次数: 0

摘要

由于基于点的观测和粗分辨率中尺度模式的局限性，量化城市化对风速的影响仍然是一个重大挑战。本研究采用微尺度计算流体动力学（CFD）方法，研究了1980年至2020年中国顺德、中山和深圳三个城市在不同城市化阶段2公里半径范围内的风模式。分析了2 km、1 km、0.5 km、0.3 km、0.1 km半径等空间尺度和风向对风速的影响，并利用地表风损失率（SWLR）和边界层风损失率（BWLR）评价城市化效应。结果表明，城市化显著减缓了风速，因为建筑阻塞，扩大了低风区，并创造了局部的高风区。空间尺度是评价城市化过程中风速降低的关键因素。较大的域（半径1公里-2公里）捕获了与城市发展相关的风速变化，而较小的域可能无法反映建筑增长或由于高层建筑效应而夸大城市化效应。风向变率在较小尺度上具有更显著的影响，特别是在具有高层城市结构的地区。从1980 - 2000年，陆地生物多样性和城市生物多样性显著增加，在高度城市化地区的影响最为显著。到2020年，2公里和1公里缓冲带的水净度达到42% - 67%，而深圳的水净度超过31%，几乎是其他城市段的两倍。分析发现，在1 km ~ 2 km半径尺度上，建筑密度（λp）、建筑地表覆盖率（λb）和前缘面积密度（λf）与地表覆盖度呈对数关系，与地表覆盖度呈较弱的相关关系。这些研究结果为观测站点周围风场随建筑形态变化的演变提供了有价值的见解，并有助于更准确地评估城市化对风速的影响。

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Assessing scale-dependent urban wind loss patterns: A CFD analysis of realistic urban segments from 1980 to 2020

Quantifying the impact of urbanization on wind speed remains a significant challenge due to the limitations of point-based observation and coarse-resolution mesoscale modeling. This study employed a micro-scale computational fluid dynamics (CFD) method to examine wind patterns around three urban segments within circles of 2-km radius in Shunde, Zhongshan, and Shenzhen, China, across different stages of urbanization from 1980 to 2020. The influences of spatial scales (2-km, 1-km, 0.5-km, 0.3-km, and 0.1-km radii) and wind directions on wind speed were analyzed, and the urbanization effect was assessed using the surface wind loss rate (SWLR) and boundary-layer wind loss rate (BWLR). The results show that urbanization significantly slowed down wind speeds due to building blockage, expanding low-wind zones and creating localized high-wind areas. Spatial scale played a crucial role in evaluating the wind speed reduction during urbanization. Larger domains (1 km-2 km radii) captured wind speed changes associated with urban development, whereas small domains might either fail to reflect building growth or exaggerate urbanization effects due to high‐rise building effects. Wind direction variability has a more significant impact at smaller scales, especially in areas with tall urban structures. SWLR and BWLR notably increased from 1980 to 2000, with the most significant effects in highly urbanized areas. By 2020, SWLR in the 2-km and 1-km buffer zones reached 42 %-67 %, while BWLR in Shenzhen exceeded 31 % that were nearly double compared with those observed in other urban segments. The analysis reveals that building density (λ_p), building surface coverage ratio (λ_b), and frontal area density (λ_f) strongly correlated with SWLR through a logarithmic function at 1 km-2 km radius scales, but had a weaker relationship with BWLR. The findings offer valuable insights into the evolution of wind fields around observation stations in response to changes in building configurations and contribute to more accurate evaluations of urbanization on wind speed.

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来源期刊

Sustainable Cities and Society Social Sciences-Geography, Planning and Development

CiteScore

22.00

自引率

13.70%

发文量

810

审稿时长

27 days

期刊介绍： Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including: 1. Smart cities and resilient environments; 2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management; 3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management); 4. Energy efficient, low/zero carbon, and green buildings/communities; 5. Climate change mitigation and adaptation in urban environments; 6. Green infrastructure and BMPs; 7. Environmental Footprint accounting and management; 8. Urban agriculture and forestry; 9. ICT, smart grid and intelligent infrastructure; 10. Urban design/planning, regulations, legislation, certification, economics, and policy; 11. Social aspects, impacts and resiliency of cities; 12. Behavior monitoring, analysis and change within urban communities; 13. Health monitoring and improvement; 14. Nexus issues related to sustainable cities and societies; 15. Smart city governance; 16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society; 17. Big data, machine learning, and artificial intelligence applications and case studies; 18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems. 19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management; 20. Waste reduction and recycling; 21. Wastewater collection, treatment and recycling; 22. Smart, clean and healthy transportation systems and infrastructure;