Heat risk of residents in different types of communities from urban heat-exposed areas

城市热岛 北京 地理 环境卫生 热浪 中国 人口 热病 社会经济学 医学 生态学 气象学 气候变化 生物 社会学 考古
作者
Bin Chen,Min Xie,Qianqian Feng,Zhaoyang Li,Lixia Chu,Qi Liu
出处
期刊:Science of The Total Environment [Elsevier]
卷期号:768: 145052-145052 被引量:24
标识
DOI:10.1016/j.scitotenv.2021.145052
摘要

Heat risk assessment is important due to serious health problems caused by heat waves. The complexity and diversity of socio-ecological characteristics in urban areas that lead to heat risk are more serious in heat-exposed areas, while risk assessments and determinant based on individuals in heat-exposed areas have been neglected in previous studies. This study pursues a new idea of combining questionnaire surveys and remote sensing analysis to identify urban heat-exposed areas and assess heat risk in heat-exposed areas of Beijing, China. Morphological spatial pattern analysis (MSPA) was used to identify large and continuous hotspot regions as urban heat-exposed areas based on summer surface temperature from 2011 to 2017. A total of 1484 valid questionnaires were completed by residents of heat-exposed areas. The majority of respondents (96.4%) indicated that they perceived heat risk. Moreover, the residents without a local “hukou” were a potentially vulnerable group (note: hukou refers to the population registration management system.). This study further analysed the diversity of community types within the heat-exposed areas. There were significant differences in heat risk among the different community types of multi-story residential districts, Hutong (a traditional architectural form) residential districts and city villages. In particular, the degree of heat risk perceived by residents living in these the community types was determined by whether they had pre-existing medical conditions; however, age only played a decisive role in city villages. This study not only enriches the current understanding of health risks affected by heat waves but also explores the determinants contributing to the severity of heat risk. The output provides important information for future development of heat mitigation and adaptation strategies.
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