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

Qian Yin,Zhoupeng Ren,Dandan Wang,Yunbing Gao,Guizhen Guo

doi:10.3390/atmos12101294

Abstract

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 R2 of 0.71. These findings will be helpful for the creation of public policies protecting against high-temperature-induced mortalities.

Highlights

Global climate change causes ambient temperature to increase, and changes the intensity, frequency, and duration of extreme weather events, such as heat waves, and temperature distribution [1,2,3]
Among the 2142 stations, the annual mean temperature (AMT) ranged from −5 ◦C to 26.5 ◦C (Figure 2a), the mortality temperature (MMT) ranged from 11 ◦C to 33 ◦C (Figure 2b), and the number of heat exposure days ranged from 40 to 120 days (Figure 2c)
The maximum number of heat exposure days occurred in areas with high temperature, such as the marginal tropical zone and south subtropical zone, with the largest values at 120 days (Figure 2c)

Summary

Introduction

Global climate change causes ambient temperature to increase, and changes the intensity, frequency, and duration of extreme weather events, such as heat waves, and temperature distribution [1,2,3]. Many studies revealed changes in temperature and extreme weather events over the past few decades [5,6,7,8]. Their choice of heat threshold has generally followed two approaches: (1) exceedance of fixed absolute values (e.g., 35 ◦C) or (2) deviation from normal. A population’s adaptation to temperature is rarely explicitly considered

Methods

Results

Discussion

Conclusion