Optimizing urban brownfields regreening solutions through a multi-objective planning model to balance ecosystem services supply, demands and costs

The issue of urban brownfields has emerged with rapid urbanization and industrial restructuring, attracting global attention from researchers and urban planners. Due to their distinctive locations and long-term abandonment, brownfields possess potential for regreening to promote urban sustainability. Multiple studies have assessed regreening potential by evaluating ecosystem services, neglecting the necessity. So we propose to prove whether brownfields regreening is needed to meet regional ecological demands, and finally build a multi-objective planning model to balance ecosystem services and demands with cost constraints at the macro scale. We first identified existing brownfields and analyzed the correlation between their distribution and ecological demands pattern. Then we established the planning model using NSGA-II, and assessed whether the model outputs provide sustainable benefits through landscape metrics. The results indicate that: (1) 75.52% of brownfields in the study area were located in districts with high ecological demands, most of which provide insufficient benefits with unexpectedly high costs; (2) the regreening solutions generated by our planning model could increase UGS area and connectivity, providing sustainable benefits that could be further reinforced by supportive brownfields-to-UGS policies. Our multi-objective planning model effectively balances benefits, demands and costs in brownfield regreening. The implementation of regreening solutions contributes to UGS pattern enhancement, which can be amplified with long-term promoting policies. Our study aims to provide a practical and flexible decision-support tool for urban planners, guiding cost-effective investments toward sustainable and stable urban development.