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March 27, 2026npj Urban Sustainability1 citationsOpen Access

Building level heat-health risk assessment in a three-dimensional and deprived built environment in Hong Kong

ELEric Tsz-Chun LaiHHHo HoPWPaulina Pui-Yun Wong

Key Points

  • The research aims to assess heat-health risks at the building level in a densely populated, deprived area of Hong Kong.
  • Developed a heat-health risk index integrating hazard, exposure, and vulnerability.
  • Estimated heat hazard using complete urban surface temperature from Landsat 8 imagery.
  • Analyzed data from 1277 buildings, focusing on their thermal loads and socioeconomic contexts.
  • Heat health risk index ranged from 0.163 to 0.661 during the day and 0.152 to 0.845 at night.
  • Highest risks identified in urban cores with overcrowdedness over 400% and over 25% low-income households.
  • Findings support targeted adaptation measures like enhancing cooling access for identified high-risk buildings.

Abstract

Abstract Extreme heat events are becoming more frequent, intense, and prolonged under global climate change, with urban areas particularly affected by the urban heat island effect. Rapid urbanisation has transformed city environments through three interrelated features—high-rise morphology, dense building clusters with overcrowded housing, and socioeconomic disparities—compounding heat-health risks. While previous studies have examined these factors individually, few have assessed their combined influence at the building level. This study developed a heat-health risk index for a deprived Hong Kong neighbourhood, integrating hazard, exposure, and vulnerability. Heat hazard was estimated using complete urban surface temperature (CST), the aggregated thermal load across all building surfaces, capturing three-dimensional heat exchange in dense urban environments, derived from Landsat 8 imagery; while the latter two domains were derived from local data from the District Office and population census. Among 1277 buildings analyzed, the heat health risk index ranged from 0.163 to 0.661 during the day and 0.152 to 0.845 at night, with the highest risk concentrated in urban cores where overcrowdedness exceeded 400% and >25% of households were low-income. Our findings enable targeted adaptation measures such as prioritising cooling access and outreach for high-risk buildings, supporting resilience planning in high-density cities.

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Cite This Study

Lai et al. (2026) studied this question.

synapsesocial.com/papers/69c620be15a0a509bde194b2https://doi.org/10.1038/s42949-025-00332-7
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