Evaluating long-term and high spatiotemporal resolution of wet-bulb globe temperature through land-use based machine learning model.

Journal: Journal of exposure science & environmental epidemiology
PMID: 38104232

Abstract

BACKGROUND: The increase in global temperature and urban warming has led to the exacerbation of heatwaves, which negatively affect human health and cause long-term loss of work productivity. Therefore, a global assessment in temperature variation is essential.

Authors

  • Chin-Yu Hsu
    Department of Safety, Health and Environmental Engineering, Ming Chi University of Technology, New Taipei 243303, Taiwan.
  • Pei-Yi Wong
    Department of Environmental and Occupational Health, National Cheng Kung University, Tainan, Taiwan.
  • Yinq-Rong Chern
    Department of Geomatics, National Cheng Kung University, Tainan, Taiwan.
  • Shih-Chun Candice Lung
    Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan.
  • Chih-Da Wu
    Department of Geomatics, National Cheng Kung University, Tainan 70101, Taiwan.

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