Analysis of article using Artificial Intelligence tools
Id | 2719 | |
Author | Wang Y.; Su Y.; Koerniawan M.D. | |
Title | Climate-Sensitive Urban Design for Thermal Comfort | |
Reference | Wang Y.; Su Y.; Koerniawan M.D. Climate-Sensitive Urban Design for Thermal Comfort,Advances in 21st Century Human Settlements |
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Link to article | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144045285&doi=10.1007%2f978-981-19-6641-5_8&partnerID=40&md5=12d7fdfbed81515c984f139135fb0248 |
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Abstract | Urban and microclimate have an intense relationship that affects each other. The specific urban structure can affect microclimate because of the high radiation generated. On the other side, urban structure blocks the distribution of incoming wind. Urban structure changes how the microclimate influences the city. The successful urban structure can impact how outdoor open spaces are used meanwhile good open spaces are affected by how comfortable can be accepted. In addition, water and greenery space is an essential urban part and has a vital environmental implication in alleviating the urban heat island (UHI). This chapter analysed thermal comfort in cold coastal areas and tropical areas. Especially in the cold coastal areas, this chapter chooses 3 plots of land used for education, 2 used as parks, 6 for commercial use, 2 for industrial land, 11 for residential land, and 6 for other land-use types. Because the field measurement points are scattered throughout the city, and the numbers of measurement instruments and researchers are limited, the 30 points are divided into five groups. Through simultaneous tests at the same period and time interval, the degree of difference in the urban thermal environment under different land categories and building types is analyzed. Through research, we found that the coupling relationship between outdoor environmental performance (OEP) and BH is analyzed qualitatively at different ranges. The maximum R2 is 0.9052, the minimum is 0.3813, and the average is 0.80, indicating an apparent quadratic polynomial relationship between AT and BH within 500 m. In addition, the coupling strength between BH and RH is relatively high. The coupling relationship between AT and BH appears to be the opposite of RH and BH. The data are also highly discrete, so there is no clear relationship between BH and WS. Coupling strength in the range of 100 m, 300 m, 700 m, and 900 m is not as strong as that of 500 m, showing higher data dispersion and a smaller R2 value. So urban structures must be well designed to make wind release the heat trapped in the urban area. This chapter also takes urban green infrastructure of Tianjin in China as a case, using subjective and objective analysis and model simulation. Waterfront compound greenery’s cooling effect was found more significant at waterfront 3–6 m, where the location was suitable for construction. When the green lawn of the waterfront space was 12 m and the water shore’s geometric form was S-shaped, this could improve the cooling effect of water significantly. This chapter provides practical implications and useful guidance for the urban planning and design. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. |
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Metodology | Technique |