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Modeling China's carbon emission reduction trajectory and peak path using a system dynamic approach

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  • Dong, Ruoyu
  • Fu, Cong
  • Liu, Yan
  • Xu, Yanqing
  • Li, Kenan

Abstract

The climate challenges posed by carbon emissions have garnered global attention, and China has also placed carbon emission reduction on its agenda. However, limited research has explored the long-term developing trajectory and peak path of carbon emissions. This study innovatively develops a System Dynamic model of China's carbon emission and carbon absorption using a scenario analysis approach to simulate the dynamic evolution of China's carbon emissions from 2020 to 2060. Unlike existing studies, this model integrates environmental subsystems and establishes feedback mechanisms among them, enabling a more comprehensive simulation of carbon emission dynamics and providing a more realistic representation of policy-driven carbon reduction pathways. The results showed that under the Baseline Mode, China's net and total carbon emissions will peak at 17.95 and 23.30 billion tons in 2050 and 2057, respectively. Various alternative scenarios, including Environment Protection Mode, Technology-oriented Mode, Economic Investment Mode, and Industrial Structure Adjustment Mode, each reveal distinct limitations. In the Coordinated Developing Mode, the peaking time of net carbon emission will be 8 years earlier, and carbon intensity is only 5.97 tons per thousand yuan. Sensitivity analysis emphasizes that economic investment and industrial structure optimization have significant impacts on carbon emission. This study provides deeper insights into the carbon emission reduction trajectory and peak path in various scenarios, aiming to guide policymakers in formulating carbon reduction plans scientifically.

Suggested Citation

  • Dong, Ruoyu & Fu, Cong & Liu, Yan & Xu, Yanqing & Li, Kenan, 2025. "Modeling China's carbon emission reduction trajectory and peak path using a system dynamic approach," Ecological Modelling, Elsevier, vol. 505(C).
  • Handle: RePEc:eee:ecomod:v:505:y:2025:i:c:s0304380025000900
    DOI: 10.1016/j.ecolmodel.2025.111104
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