State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), China Meteorological Administration, Beijing, 100081, China.
Beijing Meteorological Data Center, Beijing, 100097, China.
J Environ Manage. 2024 Jan 1;349:119576. doi: 10.1016/j.jenvman.2023.119576. Epub 2023 Nov 17.
Urban heat waves pose a significant risk to the health and safety of city dwellers, with urbanization potentially amplifying the health impact of extreme heat. Accurate assessments of population heat exposure hinge on the interplay between temperature, population spatial dynamics, and the epidemiological effects of temperature on health. Yet, many past studies have over-simplified the matter by assuming static populations, leading to substantial inaccuracies in heat exposure assessments. To address these issues, this study integrates dynamic population data, fluctuating temperature, and the exposure-response relationship between temperature and health to construct an advanced heat exposure assessment framework predicated on a population dynamic model. We analyzed urban heat island characteristics, population dynamics, and heat exposure during heat wave conditions in Beijing, a major city in China. Our findings highlight significant intra-day population movement between urban and suburban areas during heat wave conditions, with spatial population flow patterns showing clear scale-dependent characteristics. These population flow dynamics intensify heat exposure levels, and the disparity between dynamic population-weighted temperature and average temperature is most pronounced at night. Our research provides a more comprehensive understanding of real urban population heat exposure levels and can furnish city administrators with more scientifically rigorous evidence.
城市热波对城市居民的健康和安全构成重大风险，城市化可能会加剧极端高温对健康的影响。准确评估人口对热的暴露程度取决于温度、人口空间动态以及温度对健康的流行病学影响之间的相互作用。然而，许多过去的研究通过假设静态人口简化了这个问题，导致热暴露评估存在很大的误差。为了解决这些问题，本研究整合了动态人口数据、波动的温度以及温度与健康之间的暴露反应关系，基于人口动态模型构建了一个先进的热暴露评估框架。我们分析了中国主要城市北京的城市热岛特征、人口动态和热浪条件下的热暴露情况。我们的研究结果突出显示了热浪条件下城市和郊区之间的日间人口流动，人口流动模式表现出明显的尺度依赖特征。这些人口流动动态加剧了热暴露水平，动态人口加权温度与平均温度之间的差异在夜间最为明显。我们的研究提供了对真实城市人口热暴露水平的更全面理解，并为城市管理者提供了更具科学严谨性的证据。
