Volume 13 Issue 6
Feb.  2023
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Xiaokang Su, Fang Wang, Demin Zhou, Hongwen Zhang. Heat Health Risk and Adaptability Assessments at the Subdistrict Scale in Metropolitan Beijing[J]. International Journal of Disaster Risk Science, 2022, 13(6): 987-1003. doi: 10.1007/s13753-022-00449-8
Citation: Xiaokang Su, Fang Wang, Demin Zhou, Hongwen Zhang. Heat Health Risk and Adaptability Assessments at the Subdistrict Scale in Metropolitan Beijing[J]. International Journal of Disaster Risk Science, 2022, 13(6): 987-1003. doi: 10.1007/s13753-022-00449-8

Heat Health Risk and Adaptability Assessments at the Subdistrict Scale in Metropolitan Beijing

doi: 10.1007/s13753-022-00449-8

This work was jointly supported by the National Key Research and Development Program of China (2019YFC0507805) and the Strategic Leading Science and Technology Program of the Chinese Academy of Sciences (XDA20020202). We express our sincere appreciation to the anonymous reviewers for their constructive comments.

  • Received Date: 2022-10-03
  • Accepted Date: 2022-10-03
  • Available Online: 2023-02-09
  • Publish Date: 2022-10-24
  • Against the background of global climate change, the increasing heat health risk from the combined effect of changes in high temperature, exposure, vulnerability, and other factors has become a growing concern. Yet the low number of temperature observation stations is insufficient to represent the complex changes in urban heatwaves, and subdistrict-scale (town, township, neighborhood committee, and equivalent) heat health risk and adaptability assessments are still limited. In this study, we built daytime and nighttime high-temperature interpolation models supported by data from 225 meteorological stations in Beijing. The models performed well at interpolating the cumulative hours of high temperature and the interpolation quality at night was better than that during the day. We further established a methodological framework for heat health risk and adaptability assessments based on heat hazard, population exposure, social vulnerability, and adaptability at the subdistrict scale in Beijing. Our results show that the heat health risk hotspots were mainly located in the central urban area, with 81 hotspots during the day and 76 at night. The average value of the heat health risk index of urban areas was 5.60 times higher than that of suburban areas in the daytime, and 6.70 times higher than that of suburban areas in the night. Greater population density and higher intensity of heat hazards were the main reasons for the high risk in most heat health risk hotspots. Combined with a heat-adaptive-capacity evaluation for hotspot areas, this study suggests that 11 high-risk and low-adaptation subdistricts are priority areas for government action to reduce heat health risk in policy formulation and urban development.
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