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An analytical method to determine typical residential district models for predicting the urban heat island effect in residential areas

住宅区 城市热岛 环境科学 基线(sea) 土木工程 气象学 地理 工程类 海洋学 地质学
作者
Xuexiu Zhao,He Jiang,Yanwen Luo,Yigang Li
出处
期刊:urban climate [Elsevier BV]
卷期号:41: 101007-101007 被引量:13
标识
DOI:10.1016/j.uclim.2021.101007
摘要

Residential areas play an important role in the formation of the urban heat island (UHI). Many studies adopted hypothetical or simplified models to analyze UHI in residential areas based on numerical simulation. Nevertheless there is still a lack of an accurate and efficient method to obtain typical residential district models with regional characteristics. This paper presented an analytical method to determine the typical residential district model which can provide a baseline model for analyzing the relationship between residential planning indicators and UHI. Using a case study approach, this study collected residential information (including site size, layout type, building size, building orientation, building density, average building height and building interval) from 97 residential districts constructed in Nanning (a southern city of China), and obtained four typical residential district models. The applicability of the proposed method was discussed in terms of heat island intensity (HII) for the typical residential district models with actual residential districts using a numerical simulation tool (ENVI-met). The simulation results showed that the average difference of HII values was less than 0.1 °C. It was found that the proposed method can provide a baseline model for predicting the residential thermal environment at the scheme design stage. • An analytical method was proposed for determining the typical residential district models. • The determination process of the typical model was presented through a case study based on GIS data. • The typical residential district models with four layouts in Nanning were obtained. • The applicability of the typical residential district models was discussed using ENVI-met. • The proposed method can provide the baseline model for predicting the residential thermal environment.
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