Current and future thermal effects and spatial optimization modelling of urban greenspace in megacity

Abstract

<p>Urban greenspace is an important element of nature-based solutions with substantial potential for mitigating residents’ high-heat exposure (HHE). However, comprehensive analyses that incorporate future projections and optimization strategies at high spatial-temporal scale are still limited. This study quantified the thermal effects of urban greenspace on HHE from 2000 to 2040 at 100-m resolution by integrating urban climate modeling, machine learning and multi-intelligence techniques in the Chinese mega-city—Beijing, and proposed future-oriented spatial optimization strategies for the Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). Urban greenspace was found to significantly driven the spatial-temporal patterns of HHE, and spatial aggregation play a more important role than provision. The spatial optimization strategies revealed that a moderate increase in spatial aggregation could mitigate HHE by 2.4 %–24.52 % (mean: 12.95 %), which was higher in the 2020 (6.12 %–21.03 %, mean: 16.58 %), as well as for SSP3–7.0 (8 %–24.52 %, 18.02 %) and SSP5–8.5 (6.56 %–21.75 %, 16.44 %) scenarios. The findings can support urban greening efforts to optimize the spatial configuration by improving greenspace networks to offset the threats of extreme heat.</p>