A grid-scale assessment framework for heat health risks: A case study of the Beijing-Tianjin-Hebei Region, China

The increasing frequency of extreme heat events has resulted in severe and widespread global impacts. Comprehensive heat risk assessment is crucial for providing targeted climate information and services to enhance cities’ adaptation and mitigation capacities. However, the spatial resolution of administrative-level heat health risk assessments is inadequate for identifying intra-urban risk variations. This study developed a risk assessment framework for heat-related health risks integrating hazard, exposure, susceptibility, and adaptability factors. Utilizing geospatial data such as downscaled land surface temperature, gridded socioeconomic data and point of interest data, the heat health risks were evaluated comprehensively at a fine-grained 500-meter grid resolution in the Beijing-Tianjin-Hebei region, China. The results indicated that high-risk profiles were concentrated in the primary urban areas of Beijing and Tianjin. Analysis of Local Climate Zone (LCZ) classifications revealed distinct heat risk patterns across urban morphologies. Compact high-rise built zones (LCZ 1) showed the highest mean heat hazard index (0.82), while natural-type LCZ B areas exhibited the lowest (0.48). LCZ 1 (0.68) and LCZ 2 (0.67) represented the highest heat risk, followed by LCZ 4 (0.60) and LCZ 5 (0.57). To mitigate heat risks, priority measures for reducing ambient temperature and population density should be implemented in LCZs 1 and 2 regions, while LCZs 3, 4, and 5 should prioritize enhancements to healthcare and transportation infrastructure. These fine-scale risk assessment approaches effectively capture local-scale risk hotspots, providing actionable insights for improving heat governance practices and building more thermally resilient cities.