气候变化背景下极端天气事件的人群健康风险及其经济损失预测研究——以热浪为例

Projecting the public health risks associated with extreme weather events is an essential component of the formulation of adaptation policy addressing the effects of climate change. However, the quantitative relationships between extreme weather events and health effects are not clear in china. Also, the present projection method for health risks and costs still need to be improved. This study will use heat-wave as an example, and examine data from three representative cities in China to investigate heat-wave related health impacts based on the retrospective analyses of meteorological, health and air pollution data. Quantitative relationships between heat-waves and health outcomes will be determined using epidemiological statistical models, and differences between the three cities will be examined. Sensitive disease and vulnerable population associated with heat-wave will be clarified. Secondly, General Circulation Models (GCMs) and downscaling techniques will be used to project future temperatures. Combining this with the quantitative relationships derived from historical data will allow us to project heat-wave related public health risks in two future periods under three scenarios. We will further refine the projection method to include factors such as the heat-wave characteristic; population changes; changes in the population's ability to adapt; and calculate the uncertainties in these projections. We will improve the accuracy of the projected results and the scientific basis of the calculation of uncertainties. Finally, we will apply market and contingent valuation methods to assign a monetary value to the health costs according to risks; and we will analyze the results in terms of time, location, heat-wave sensitive diseases and valnerable populations, in order to provide specific policy recommendations. The methodology which will be used in this study can be extended and applied to other extreme weather events. The results from this study will help to provide information for policy making and contribute to the protection of the public health of the Chinese people.

预测极端天气事件的人群健康风险是制定气候变化适应性政策的重要基础。但是我国极端天气事件与人群健康影响的定量关系尚不清晰，国际上现有的健康风险及其经济损失的预测方法仍需改进。本研究以热浪为例，选取我国三个城市，首先基于历史气象、健康、空气污染物数据，应用流病统计模型明确热浪对我国人群健康影响的定量关系，分析不同区域人群影响的差异，辨识脆弱人群与敏感疾病；进而应用GCMs及降尺度技术预测未来温度，整合健康影响定量关系预测高中低排放情景下，未来中远期人群健康风险。预测中将考虑热浪特征、人口与人群适应性变化、不确定性表达以改进现有方法，使得预测更准确不确定性表达更科学；最后应用市场价值法与条件价值法货币化定量未来人群健康风险的经济损失并分析不同时间空间、敏感疾病、脆弱人群的特征，提出政策建议。本研究建立的方法体系可推广应用于其他极端天气事件。研究结果对制定适应性政策，保护我国人群健康具有重要意义。

科学预测未来人群健康风险是制定气候变化适应性政策的重要基础。然而现阶段我国极端天气事件与人群健康影响的定量关系尚不明晰，国际上现有的健康风险及其经济损失的预测方法仍需改进。本研究以高温热浪为例，应用流行病学统计模型明确热浪对我国人群健康影响的定量关系，分析不同区域人群影响的差异，辨识脆弱人群与敏感疾病；进而应用GCMs及降尺度技术预测未来温度，整合健康影响定量关系预测高中低排放情景下，未来中远期人群健康风险。最后应用市场价值法与条件价值法货币化定量未来人群健康风险的经济损失。.在南京开展的极端热浪天气事件人群健康风险空间分析发现，热浪不仅仅发生在城市的城区，而郊区也已成为热浪的重灾区；在北京开展的心脑血管疾病与呼吸系统疾病温度热效应死亡风险的预估结果表明，温度热效应死亡风险在2020s，2050s，2080s不同时期内增长，并随时间推移而增加，在RCP4.5与RCP8.5两种情景下，热效应死亡风险未来远期的增幅要大于未来中期增幅；老龄化对热相关死亡风险影响的预估研究发现，从1980s到2080s年代，热相关死亡风险显著增加，对比人口结构改变与不变的情境下，人口老龄化情境下的热相关死亡风险显著升高；居民对热浪健康防护相关措施的支付意愿调查研究发现，当防护措施的提供方为政府时，城区和郊区的支付率分别为31.6%和51.6%，提供方为市场时，城区和郊区居民的支付率分别为32.0%和47.4%，两区居民的支付金额集中于40元/（人▪年）。.本项目执行期间获取了北京和南京历史性气象健康数据集，北京2013年居民热浪调查（支付意愿）及北京和南京2020-2100温度预估数据等关键数据。本研究初步建立了高温热浪人群健康风险及其经济损失评估预测方法体系，对制定气候变化适应性政策，保护我国人群健康具有重要意义。该方法体系可推广应用于其他极端天气事件，这对我国公共卫生系统应对极端天气事件的实践工作提供有力支持。