Rapid urbanization and extreme heat events have made heat risk (HR) a prominent environmental challenge in the Yangtze River Delta. Focusing on five cities in the Shanghai–Nanjing urban belt, this study developed a Local Climate Zone (LCZ)-based framework integrating heat hazard (HH), heat exposure (HE), and heat vulnerability (HV) to assess HR using multi-source data, and employed a multi-constraint optimization model to explore LCZ-based HR mitigation strategies. Built-up and natural LCZs accounted for approximately 43% and 57% of the urban belt, respectively, with substantial inter-city differences. Suzhou had the highest HH (0.559), whereas Nanjing had the highest HE (0.330), HV (0.374), and mean HR (1.235), despite having the lowest proportion of built-up LCZs. Optimization yielded modeled HR reductions across all risk levels, with a greater reduction at the extremely high-risk level (6.66%) than at the low-risk level (1.01%). The optimization reduced high-density built-up LCZs, increased open LCZ4, and increased selected blue–green LCZ types. Calculated population-carrying capacity increased by 31.45% at the extremely high-risk level and did not decrease at any risk level. These findings provide a quantitative basis for comparing LCZ-based HR management scenarios under specified constraints, while actual cooling effects and implementation feasibility require further validation.
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Li et al. (2026) studied this question.
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