CN 11-5366/S     ISSN 1673-1530
“风景园林,不只是一本期刊。”

城市通风环境的多情景动态模拟与优化——以太原都市区为例

Multi-scenario Dynamic Simulation and Optimization of Urban Ventilation Environment: A Case Study of Taiyuan Metropolitan Area

  • 摘要:
    目的 随着高密度建成区的扩张,作为消散空气污染与积热重要途径的城市通风环境面临着不同程度的威胁。依据不同规划目标对城市通风环境进行动态模拟,识别其变化趋势,为建设“凉爽城市”、保障城市可持续发展提供指导。
    方法 以太原都市区多时序高精度数据为基础,从地表气压梯度、地表粗糙度和地表起伏度3个维度构建城市通风环境评价指标体系,分析城市通风环境变化趋势,并基于自然发展、耕地保护与生态优先3种用地情景,通过随机森林模型模拟2030、2040、2050年多情景下的城市通风环境。
    结果 通风环境主要受粗糙度长度和地表温度梯度的影响;研究区域通风环境在2000—2020年整体呈恶化趋势,尤其在中心城区与晋中市之间;相比于耕地保护情景,生态优先情景对极好与较好等级通风环境面积的增加有更积极的影响;依据通风环境在不同情景下的差异,因地制宜地提出城市通风优化策略与规划建议。
    结论 结合城市通风环境评价指标体系与随机森林模型模拟城市通风环境的动态变化,得到3条核心结论:1)林地与水域作为绿色基础设施对城市通风起着关键作用;2)平原耕地作为自然冷源和人为热源之间的过渡空间,是形成风廊的重要载体;3)城市规划应权衡建设用地扩张与良好的通风空间保护之间的关系。并提出风景园林城市气候优化策略,可为建设韧性城市提供理论支持与实践指导。

     

    Abstract:
    Objective In recent decades, China’s rapid urbanization has led to large amounts of energy consumption and carbon dioxide emissions, triggering significant urban heat island effects and air pollution, which seriously threaten the physical and mental health of residents. How to improve the urban human settlement environment has become the focus of urban planning. Urban ventilation, as an important way to deliver fresh and cold air to built-up areas, can effectively improve the comfort level. Although many international scholars have researched the optimization of urban ventilation, the existing research in China mainly focuses on the measurement of the current urban ventilation environment, while neglecting the long-term dynamic changes of the urban ventilation environment in response to different planning objectives in the process of urban development.
    Methods This research proposes a research framework generally applicable to the simulation of future changes in ventilation environment within city – region systems for the first time. Firstly, this research defines five indicators (surface temperature gradient, roughness length, forest canopy density, elevation variation coefficient, and slope) to evaluate the ventilation environment from three dimensions: surface pressure gradient, surface roughness, and surface undulation. Secondly, based on previous research and considering the natural environment and socio-economic development of the research area, DEM, slope, distance to primary roads, distance to secondary roads, distance to tertiary roads, population density, GDP, and building density are selected as driving factors in this research to investigate the transformation pattern of land use types. The data on driving factors and land use types in the research area in 2000 and 2010 are imported into the PLUS model. Three scenarios of natural development, farmland protection and ecological priority are set to simulate the land use types. Then, a prediction model is constructed based on the random forest algorithm. The land use types and ventilation environment of multiple scenarios in 2010 and 2020 are input into the validated prediction model to simulate changes in the future ventilation environment. Finally, depending on the historical trends in ventilation potential and differences across multiple scenarios within the research area, specific applications of the simulation results are proposed for spatial planning and management of metropolitan areas.
    Results Influenced by urban development from 2000 to 2020, the ventilation environment of the Taiyuan metropolitan area varied with time, space, and planning objectives, with a decreasing trend and an increasing trend shown in local areas. Patches of better ventilation environments occurred at the Jinyang Lake, the Fen River, and the Fen River Park. Several potential ventilation corridors were formed on the east and west sides of the built-up area. Under the scenarios of natural development, farmland protection, and ecological priority, the ventilation environment of the research area shows a trend of gradual improvement from 2030 to 2050. Specifically, from 2030 to 2050, the grade of the ventilation environment is gradually improved; from 2040 to 2050, the area of the ventilation environment graded as extremely good or good is significantly increased. Meanwhile, the ventilation environments in different regions show differences in spatial distribution. Under the natural development scenario, there is a significant increase in the area of ventilation environments graded as extremely good or good in 2030. From 2030 to 2040, the area of poorly rated ventilation environments increases between the central urban area and the eastern and western mountainous areas. From 2040 to 2050, the ventilation environment in the above areas gradually improves, and a significant wind corridor with high ventilation potential appears between the eastern mountainous area and the central urban area. The continuous protection of basic farmland effectively limits the encroachment of construction land on farmland. By the end of 2050, a large amount of basic farmland is retained in the north and south plains. From 2030 to 2050, the villages and towns located in the southern plains transform from early isolated islands to a grid-like structure, and the ventilation environment level of the surrounding roads, rivers and other linear spaces gradually increases. Under the ecological priority scenario, water bodies, forests and sparse grasslands are preserved to the maximum extent possible. The area of ventilation environments graded as extremely good increases significantly from 2030 to 2050. These areas are mainly distributed around large water bodies such as the Fen River and the Jinyang Lake.
    Conclusion In this research, a dynamic simulation model of the urban ventilation environment is constructed and the spatial distribution of the ventilation environment under different scenarios is mapped. To cope with a series of urban problems caused by urban sprawl and densification, the trends of the ventilation environment in the Taiyuan metropolitan area are predicted and identified, based on which a series of targeted optimization strategies are proposed. However, this research still has limitations. Since this research uses historical data spanning a period of 10 years, various factors, such as climate change and human activities, may have interfered with the simulation results during this period. Therefore, to improve the simulation accuracy, future research may incorporate more environmental factors into the modeling process to explore the objective laws of the ventilation environment in the process of long time-series changes, which may provide guidance for the construction of local climate adaptive cities.

     

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