长江三角洲地区高温热浪人群健康风险评价

发布时间：2018-02-27 08:54

本文关键词： 高温热浪公共健康高温风险风险评估长江三角洲地区　出处：《地球信息科学学报》2017年11期 　论文类型：期刊论文

【摘要】：在全球极端气象、气候事件频发的背景下,获取高分辨的灾害风险信息对于区域防灾减灾决策具有重要的参考价值。而在当前的灾害风险评估中,基于行政单元的人口和社会经济等承灾体信息与栅格水平上的致灾因子普遍存在空间不匹配的现象。本文通过融合多源遥感数据和人口、社会经济统计数据,在利用人居指数对高温人口暴露进行空间化的基础上,获取了250 m分辨率的长江三角洲地区高温热浪人群健康风险空间格局。结果表明,风险等级较高的地区集中在上海、常州、杭州、宁波、无锡、嘉兴、泰州等城市的中心城区,主要是较高的人口暴露度和城市高温共同作用的结果;而大城市近郊以及各规模较小的城区的风险等级次之;相对欠发达地区虽然人口暴露程度较低,但较高的高温危险性和社会经济脆弱性指数使得这些地区的高温人群健康风险也不容忽视。识别高风险地区的风险主导因子对于提高人群高温适应能力以及减轻高温健康风险具有重要意义。
[Abstract]:Under the background of global extreme weather and frequent climate events, obtaining high-resolution disaster risk information has important reference value for regional disaster prevention and mitigation decision-making. The spatial mismatch between population and socio-economic information and the disaster-causing factors at grid level is common in this paper. This paper combines multi-source remote sensing data with population and socio-economic statistics. On the basis of using human settlements index to spatialize the exposure to high temperature population, a 250 m resolution spatial pattern of health risk of high temperature heat wave population in the Yangtze River Delta is obtained. The results show that the areas with higher risk level are concentrated in Shanghai. The central urban areas of Changzhou, Hangzhou, Ningbo, Wuxi, Jiaxing, Taizhou and other cities are mainly the result of the combination of high population exposure and urban high temperature, while the peri-urban areas of big cities and smaller urban areas have the second risk level. Although population exposure is relatively low in less developed regions, However, high high temperature risk and socioeconomic vulnerability index make the health risk of high temperature population in these areas should not be ignored. Identification of risk leading factors in high risk areas can improve the ability of population to adapt to high temperature and reduce the risk. High temperature health risk is of great significance.
【作者单位】：江西师范大学地理与环境学院;浙江大学海洋学院;
【基金】：国家自然科学基金项目(41371068)
【分类号】：R122.26

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