A review of multi-scale modelling, assessment, and improvement methods of the urban thermal and wind environment

Zhang, Xinkai; Jin, Xing; Zhou, Xia; Du, Sihong

doi:10.1016/j.buildenv.2022.108860

Cited by 55 publications

(15 citation statements)

References 211 publications

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“…The main aim behind the establishment of outdoor thermal environment models is to identify and improve solutions to existing problems [72]. When considering frequent heatwaves, a variety of factors should be combined to analyze the interactive relationship between factors.…”

Section: Discussionmentioning

confidence: 99%

Quantitative Study on the Effects of Street Geometries and Tree Configurations on the Outdoor Thermal Environment

Wu,

Wang,

et al. 2024

Energies

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Global warming and the urban heat island effect has aroused the attention of research on the outdoor thermal environment. As outdoor spaces often used by citizens, streets play an important role in improving the thermal environment. In this study, six factors relating to street geometries and tree configurations in Busan are measured and quantified to form 32 typical scenarios. The degree of importance of these six factors is evaluated based on ENVI-met simulation results, and GeoDetector is introduced to evaluate the interactions between the factors and their impacts on the outdoor thermal environment. This study confirms the significantly higher impact of street geometry factors on the air temperature and physiological equivalent temperature compared to tree configuration factors. Particularly, Hb/Ws shows the most significant impact during the research period. The impact of interactions between any two factors of street geometry is much higher than that of interactions between the geometry and tree configuration factors and that of interactions between the tree configuration factors. We recommend dynamically adjusting the relationship between street geometry and tree configurations in different situations to improve the outdoor thermal environment, especially at noon and in the afternoon.

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Section: Discussionmentioning

confidence: 99%

Quantitative Study on the Effects of Street Geometries and Tree Configurations on the Outdoor Thermal Environment

Wu,

Wang,

et al. 2024

Energies

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“…The generalization workflow is depicted in Figure 2. (1) To avoid inappropriate merging of buildings on opposite sides of the roads, we initially divided the study area into multiple zones (e.g., shp_1, shp_2, shp_3... shp_i) based on the administrative boundaries and major roads in the study area. (2) One of the zones, shp_i, was selected for the generalization.…”

Section: Generalization Schemementioning

confidence: 99%

“…Cities worldwide and building densities have grown significantly [1]. It is estimated that 68% of the global population will reside in urban areas by 2025.…”

Section: Introductionmentioning

confidence: 99%

A Generalization of Building Clusters in an Urban Wind Field Simulated by CFD

Qiu,

He,

et al. 2023

Atmosphere

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The urban climate has a critical influence on developing sustainable cities, and one important factor is the urban wind environment. Moreover, refining urban wind fields is required for the quantitative assessment of urban wind environments. Computational fluid dynamics (CFD) is a powerful tool for modeling the wind flow characteristics in urban areas. Although CFD has been widely used in various fields, its use for simulating urban wind fields has limitations because of the complexity of urban building models and the high computational workload. Accordingly, we consider the generalization parameters in the vertical and horizontal directions based on the CFD results and the building topology based on the state of the building nodes. We perform a two-dimensional generalization of building clusters, conduct spatial analysis in a geographic information system (GIS), and generate three-dimensional models. This generalization scheme is applied to Meiling Street in Jinjiang City, Fujian Province, China. The results indicate that the generalization decreases the number of buildings from 7003 to 3367 and the computation time from 11 h and 26 min to 10 h and 25 min. The computation efficiency is improved by 8.89%, with 1.85% changes in the average wind speed ratio. This scheme substantially improves the computational efficiency of urban wind field CFD simulations by reducing the geometric model’s complexity without compromising the accuracy. This strategy is suitable for simulating large-scale urban wind fields.

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“…Along with the sustained improvement of human society and economy, the process of urbanisation has been accelerated, the urban population has increased dramatically, and urban land resources have been reduced year by year, which makes the global warming phenomenon more serious. Also, the surface temperature has been rising continuously, which has led to a profound change in the urban thermal environment [1][2][3], which is now a common problem in cities worldwide [4][5][6][7]. Changes in the city's thermal environment decrease the amount of heat dissipated by the city, and also generate, store, absorb, and retain excess heat, resulting in higher temperatures in urban areas than in suburban areas, exacerbating the UHI [8,9].…”

Section: Introductionmentioning

confidence: 99%

Quantifying Urban Spatial Morphology Indicators on the Green Areas Cooling Effect: The Case of Changsha, China, a Subtropical City

Li,

Wang,

Cai

et al. 2024

Land

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Green city areas are crucial in mitigating the Urban Heat Island Effect (UHI). However, the cooling effect of green city areas can be influenced by the surrounding complex urban spatial environment. This study focuses on Changsha, a subtropical city in China, where 40 green city areas were screened and analyzed. The study aims to quantify the specific impact of urban spatial morphology on the cooling effect of green city areas. Through statistical correlation and regression analysis, this study focused on six urban spatial morphology indicators: building density (BD), building floor area ratio (BFR), building volume density (BVD), building evenness index (BEI), building average height (BH), and building height standard deviation (BSD). The results indicate that the cooling effect of green city areas could be influenced by urban spatial morphology. Factors such as BD, BFR, BH, and BSD were found to be significantly correlated with the cooling effect of green city areas, with BH showing the strongest influence. BD and BFR were negatively correlated, while BH and BSD were positively correlated. The range values of BD, BFR, BH, and BSD were determined to achieve the optimal conditions for the cooling effect of green city areas. Additionally, the relative position of the green city areas in the neighboring urban areas affects the cooling effect of the green city areas. The cooling effect is most pronounced in the urban area situated to the south of the green city areas. These findings provide a solid foundation for urban planning around green city spaces and offer scientifically sound evidence for mitigating the UHI.

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A review of multi-scale modelling, assessment, and improvement methods of the urban thermal and wind environment

Cited by 55 publications

References 211 publications

Quantitative Study on the Effects of Street Geometries and Tree Configurations on the Outdoor Thermal Environment

Quantitative Study on the Effects of Street Geometries and Tree Configurations on the Outdoor Thermal Environment

A Generalization of Building Clusters in an Urban Wind Field Simulated by CFD

Quantifying Urban Spatial Morphology Indicators on the Green Areas Cooling Effect: The Case of Changsha, China, a Subtropical City

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