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    Understanding the relationships between high temperatures (HT) and heat waves (HW) is vital for enhancing human health, especially in areas with dense population. This paper analyzes the temporal and spatial characteristics of different HT and HW intensities, their spatial influence, and the population distribution risk at different HW intensities for 844 meteorological stations between 1951 and 2019. The results indicate that (1) HT and extreme temperature (ET) days are symmetrically distributed along the Huhuanyong Line, from southeast to northwest China. The times, days, and accumulated temperatures of HW, the times, days, and accumulated temperature of strong heat waves (SHW), and the times, days, and accumulated temperature of extreme heat waves (EHW) were distributed similarly; (2) with the increase in high temperatures or heat waves from HT to ET or from HW to SHW, the proportion of stations with an upward trend was always greater in China, while stations with a downward trend were mainly located in the North China Plain and Huai River Basin. For HW, SHW, and EHW, the increasing range of times and days were less than the accumulated temperatures; (3) between 1990 and 2019, there was an expansion of the HW and SHW distribution area with an annual average of more than 10 days, and the EHW distribution area with an annual average of more than 3 days. Moreover, the number of people exposed to HW, SHW, and EHW also increased during this period; and (4) considering the population distribution characteristics and the regional HT and HW characteristics, society needs to form regional adaptation actions for different HT and HW intensities. © 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.


    Xiaoju Ning, Yuanzheng Li, Genghe Gao, Yan Zhang, Yaochen Qin. Temporal and spatial characteristics of high temperatures, heat waves, and population distribution risk in China from 1951 to 2019. Environmental science and pollution research international. 2023 Sep;30(42):96629-96646

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    PMID: 37578588

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