Zhou (2026) High-carbon sink landscape design of urban small and micro green spaces based on digital twin technology under the dual-carbon goals

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Discover Environment
• Year: 2026
• Date: 2026-09-22
• Authors: Renjing Zhou
• DOI: 10.1007/s44274-026-01048-w

Research Groups

• School of Environmental Science and Engineering, Hunan University
• Key Laboratory of Urban Environment and Health (Hunan Province)
• Institute of Ecology and Biodiversity Conservation, Chinese Academy of Sciences

Short Summary

This study developed a dynamic carbon-budget assessment method by integrating digital twin technology with life cycle assessment to optimize high-carbon-sequestration landscape design in urban small and micro green spaces. The results showed that comprehensive optimization can reduce total carbon emissions by 38.45% and increase total carbon sequestration by 33.78%.

Objective

• Investigate the feasibility of dynamic carbon-budget assessment and high-carbon-sequestration landscape optimization in urban small and micro green spaces using digital twin technology.

Study Configuration

• Spatial Scale: A street-corner green space in Changsha, China (approximately 0.1 ha)
• Temporal Scale: 20-year simulation period

Methodology and Data

• Models used: Digital twin model integrating life cycle assessment and periodic data updating
• Data sources: Multi-source spatial, ecological, environmental, material, and operation and maintenance data from various sensors and databases

Main Results

• Comprehensive optimization reduced total carbon emissions by 38.45% and increased total carbon sequestration by 33.78%
• Net carbon balance was achieved in the sixth year under comprehensive optimization scenario
• Average carbon-efficiency improvement rate of 39.64% was achieved under comprehensive optimization scenario

Contributions

• The proposed method supported dynamic carbon-budget assessment through periodic state updating, model calibration, and iterative scenario optimization
• Provided quantitative support for high-carbon-sequestration landscape design and refined low-carbon management of urban small and micro green spaces

Funding

• National Natural Science Foundation of China (Grant No. 52177041)
• Hunan Provincial Key Research and Development Program (Grant No. 2020SK2033)

Citation

@article{Zhou2026Highcarbon,
  author = {Zhou, Renjing},
  title = {High-carbon sink landscape design of urban small and micro green spaces based on digital twin technology under the dual-carbon goals},
  journal = {Discover Environment},
  year = {2026},
  doi = {10.1007/s44274-026-01048-w},
  url = {https://doi.org/10.1007/s44274-026-01048-w}
}