How do green space cooling benefits align with population needs? A multi-dimensional assessment in a land–water mosaic city

The cooling efficiency of green spaces exhibits intra-urban spatial heterogeneity, yet systematic assessments of how greenness, benefiting population size, and other environmental factors affect this efficiency remain scarce. Taking Wuhan as a case study, this research proposes an integrated framework to elucidate how green space cooling benefits align with population needs and to explain the underlying environmental drivers of spatial variations in cooling efficiency. The coupled WRF-UCM model was employed to measure changes in the Universal Thermal Climate Index (UTCI) between vegetated and non-vegetated scenarios. By integrating population-weighted UTCI and green space fraction, a cooling efficiency matrix was constructed, followed by GWR analysis to explore the factors driving spatial variations in cooling efficiency. Trees exhibited higher cooling efficiency than grass. GWR analysis revealed that the high cooling efficiency of trees was driven by reductions in daytime radiation and nighttime temperature, whereas that of grass was attributable to reductions in temperature throughout the day. Cooling efficiency was highest in upwind southwestern regions and the western Yangtze Riverbank, and was lowest in downwind northwestern areas. Areas characterized by high population and low green space fraction frequently exhibited high cooling efficiency, while their counterparts with low population density and high green space fraction did not necessarily do so. We proposed targeted landscape management strategies for four regions, characterized by a distinct combination of cooling efficiency, population density, and green space fraction. The framework can also be adapted to evaluate and optimize urban green spaces under different climatic and geographical conditions.