Applied Meteorological Research Division, National Institute of Meteorological Sciences, 33, Seohobuk-ro, Seogwipo-si, 63568, Jeju-do, Republic of Korea.
Institute of Ecology, Technische Universität Berlin, Rothenburgstraße 12, 12165, Berlin, Germany.
Int J Biometeorol. 2019 Jan;63(1):1-12. doi: 10.1007/s00484-018-1631-2. Epub 2018 Nov 20.
This study quantifies heat-stress hazard (air temperature), vulnerability (heat vulnerability index and age score), and risk (heat-related mortality) on the district scale in Seoul, Korea, for a comprehensive heat-stress impact assessment. Moreover, the heat-stress impact assessment is evaluated by checking the spatial consistency between heat-stress hazard, vulnerability, and risk, which was rarely done before. We applied numerical and geo-empirical models to simulate the spatial pattern of heat-stress hazard. For heat-stress vulnerability, we used demographic and socioeconomic factors. Heat-related mortality was estimated based on an event-based heat-stress risk analysis. Results are that heat-stress hazard, vulnerability, and risk are spatially variable in Seoul. The highest heat-stress hazard was detected in the districts Mapo, Yeongdeungpo, and Yangcheon, the highest vulnerability in Jongno and the highest risk in Jongno and Yangcheon. The different components (heat-stress hazard, vulnerability, and risk) and variables (heat vulnerability index and percentage of seniors) showed different spatial patterns. Knowledge about the causes of higher heat-stress risk, either the hazard or vulnerability, is helpful to design tailored adaptation measures that focus on the reduction of thermal loads or on the preparation of the vulnerable population. The evaluation showed that heat-stress vulnerability and hazard explain the spatial pattern of risk only partly. This highlights the need to evaluate heat-stress impact assessment systems to produce reliable urban heat-stress maps.
本研究旨在量化韩国首尔市的热应激危害（气温）、脆弱性（热脆弱性指数和年龄评分）和风险（与热相关的死亡率），以进行全面的热应激影响评估。此外，通过检查热应激危害、脆弱性和风险之间的空间一致性来评估热应激影响评估，这在以前很少进行。我们应用数值和地理经验模型来模拟热应激危害的空间格局。对于热应激脆弱性，我们使用了人口统计学和社会经济因素。基于基于事件的热应激风险分析来估计与热相关的死亡率。结果表明，首尔的热应激危害、脆弱性和风险在空间上是可变的。在麻浦区、永登浦区和杨川区检测到最高的热应激危害，在钟路区检测到最高的脆弱性，在钟路区和杨川区检测到最高的风险。不同的组成部分（热应激危害、脆弱性和风险）和变量（热脆弱性指数和老年人的百分比）显示出不同的空间模式。了解导致更高热应激风险的原因，无论是危害还是脆弱性，都有助于设计有针对性的适应措施，重点减少热负荷或为脆弱人群做好准备。评估结果表明，热应激脆弱性和危害仅部分解释了风险的空间模式。这强调了需要评估热应激影响评估系统，以生成可靠的城市热应激图。
