Multi-Objective Optimisation of Sponge City LID Facilities Incorporating Carbon Trading Mechanism

Urban stormwater management is a critical component of sustainable city development, yet conventional low impact development (LID) layout optimisation often neglects life-cycle carbon emissions and carbon-trading opportunities. This study developed an integrated multi-objective optimisation framework for sponge city LID facilities that embedded life-cycle carbon accounting and carbon trading into conventional hydrological-economic decision-making. The methodology coupled the storm water management model (SWMM) for hydrological simulation with life cycle assessment (LCA) and life cycle cost (LCC) models. The non-dominated sorting genetic algorithm III (NSGA-III) and entropy-weighted VIKOR method were utilized to solve the multi-objective problem and evaluate optimal schemes. Applied to the Fenghuangcheng pilot sponge city area in Shenzhen, China, the results showed that incorporating carbon constraints and trading drove a fundamental structural reconfiguration. The optimal layout shifted from being permeable-pavement-dominated (approximately 70%) to vegetation-based facilities. Green roofs increased to 48–50% and rain gardens to 29–41%, while permeable pavements dropped below 1%. Consequently, net life-cycle carbon emissions shifted from positive values to a net-negative balance of approximately −1.2 to −1.4 Mt CO2e. Carbon trading revenue acted as an economic compensator, reducing net costs by up to 11%. The proposed framework provided a quantitative decision-support tool for transforming LID facilities into tradable ecological assets, supporting sustainable low-carbon sponge city planning.