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Metabolic Process Modeling of Metal Resources Based on System Dynamics—A Case Study for Steel in Mainland China

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Listed:
  • Yan Shi

    (School of Geosciences and Info-Physics, Central South University, Changsha 410083, China)

  • Shanshan Shao

    (School of Geosciences and Info-Physics, Central South University, Changsha 410083, China)

  • Xuexi Yang

    (School of Geosciences and Info-Physics, Central South University, Changsha 410083, China)

  • Da Wang

    (School of Geosciences and Info-Physics, Central South University, Changsha 410083, China)

  • Bingrong Chen

    (School of Geosciences and Info-Physics, Central South University, Changsha 410083, China)

  • Min Deng

    (School of Geosciences and Info-Physics, Central South University, Changsha 410083, China)

Abstract

Rapid urbanization has promoted the development in human production and living standards, and the metabolic rhythm of metal resources has accelerated. Grasping the metabolic processes of metal resources and predicting their future development trends can help the country refine the formulation and adaptability of metal resource production and the recycling strategies for sustainable development. In this study, from the perspective of the entire life cycle of steel resources as an example, a system dynamics-based metal resource metabolism prediction model was established to predict the steel resources in the three stages, including production, in-use and end-of-life recycling. The trend in changes in steel resources production, in-use stock, end-of-life and recycling in mainland China from 1990 to 2020 were also analyzed. The results show that the volume of all stages of steel resource metabolism in mainland China from 1990 to 2020 has shown an increasing trend, and will reach a peak around 2040 and then remain stable. The steel resources in all the metabolism stages in mainland China were predominantly distributed in buildings. In mainland China, steel resource production efficiency reached above 0.9 and the steel resource outflow rate was 0.079, within which the domestic scrap rate reached 0.022 and the recycling rate reached above 0.8.

Suggested Citation

  • Yan Shi & Shanshan Shao & Xuexi Yang & Da Wang & Bingrong Chen & Min Deng, 2023. "Metabolic Process Modeling of Metal Resources Based on System Dynamics—A Case Study for Steel in Mainland China," Sustainability, MDPI, vol. 15(13), pages 1-22, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10249-:d:1181686
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    References listed on IDEAS

    as
    1. Augiseau, Vincent & Barles, Sabine, 2017. "Studying construction materials flows and stock: A review," Resources, Conservation & Recycling, Elsevier, vol. 123(C), pages 153-164.
    2. Recalde, Korinti & Wang, Jinlong & Graedel, T.E., 2008. "Aluminium in-use stocks in the state of Connecticut," Resources, Conservation & Recycling, Elsevier, vol. 52(11), pages 1271-1282.
    3. Dai, Tiejun, 2015. "A study on material metabolism in Hebei iron and steel industry analysis," Resources, Conservation & Recycling, Elsevier, vol. 95(C), pages 183-192.
    4. Zhang, L.F. & Xie, M. & Tang, L.C., 2006. "Bias correction for the least squares estimator of Weibull shape parameter with complete and censored data," Reliability Engineering and System Safety, Elsevier, vol. 91(8), pages 930-939.
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