High-carbon sink landscape design of urban small and micro green spaces based on digital twin technology under the dual-carbon goals

Urban small and micro green spaces play an increasingly important role in enhancing urban carbon sequestration capacity and optimizing carbon budgets. To address the limitations of static assessment methods, this study developed a dynamic carbon-budget assessment and high-carbon-sequestration landscape optimization method by integrating digital twin (DT) technology with life cycle assessment. A street-corner green space in Changsha was selected as the study area. Multi-source spatial, ecological, environmental, material, and operation and maintenance data were integrated to construct a DT model with periodic data updating and parameter calibration. Based on this model, a 20-year carbon-budget simulation was conducted under a baseline scenario and four optimization scenarios involving plant configuration, low-carbon materials, operation and maintenance, and comprehensive optimization. The results showed that operation and maintenance gradually became the dominant source of carbon emissions over the life cycle. Under the comprehensive optimization scenario, total carbon emissions decreased from 150.01 t to 92.34 t, representing a reduction of 38.45%, while total carbon sequestration increased from 136.46 t to 182.57 t, representing an increase of 33.78%. The net carbon balance increased from − 13.55 t to 90.23 t, and carbon balance was achieved in the sixth year. The comprehensive optimization scenario achieved the highest average carbon-efficiency improvement rate of 39.64%, outperforming the individual optimization scenarios. The proposed method supported dynamic carbon-budget assessment through periodic state updating, model calibration, and iterative scenario optimization, providing quantitative support for high-carbon-sequestration landscape design and refined low-carbon management of urban small and micro green spaces.