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A New Method to Estimate Heat Exposure Days and Its Impacts in China

文献类型： 外文期刊

作者： Guo, Guizhen 1 ; Wang, Dandan 1 ; Ren, Zhoupeng 2 ; Yin, Qian 2 ; Gao, Yunbing 3 ;

作者机构： 1.Minist Emergency Management, Natl Disaster Reduct Ctr China, Beijing 100124, Peoples R China

2.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China

3.Beijing Acad Agr & Forestry Sci, Informat Technol Res Ctr, Beijing 100097, Peoples R China

关键词： heat exposure days; most frequency temperature; climate change; temperature distribution; climate zone

期刊名称：ATMOSPHERE （ 影响因子：2.686； 五年影响因子：2.848 ）

ISSN：

年卷期： 2021 年 12 卷 10 期

页码：

收录情况： SCI

摘要： Understanding the spatiotemporal trends of temperature in the context of global warming is significant for public health. Although many studies have examined changes in temperature and the impacts on human health over the past few decades in many regions, they have often been carried out in data-rich regions and have rarely considered acclimatization explicitly. The most frequent temperature (MFT) indicator provides us with the ability to solve this problem. MFT is defined as the longest period of temperature throughout the year to which a human is exposed and therefore acclimates. In this study, we propose a new method to estimate the number of heat exposure days from the perspective of temperature distribution and MFT, based on the daily mean temperature readings of 2142 weather stations in eight major climate zones in China over the past 20 years. This method can be used to calculate the number of heat exposure days in terms of heat-related mortality risk without the need for mortality data. We estimated the distribution and changes of annual mean temperature (AMT), minimum mortality temperature (MMT), and the number of heat exposure days in different climate zones in China. The AMT, MMT, and number of heat exposure days vary considerably across China. They all tend to decrease gradually from low to high latitudes. Heat exposure days are closely related to the risk of heat-related mortality. In addition, we utilized multiple linear regression (MLR) to analyze the association between the risk of heat-related mortality and the city and its climatic characteristics. Results showed that the number of heat exposure days, GDP per capita, urban population ratio, proportion of elderly population, and climate zone were found to modify the estimate on heat effect, with an R-2 of 0.71. These findings will be helpful for the creation of public policies protecting against high-temperature-induced mortalities.

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