IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i13p10249-d1181686.html
   My bibliography  Save this article

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

Author

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/13/10249/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/13/10249/
    Download Restriction: no
    ---><---

    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huimin Liu & Mengqian Xu & Xuexi Yang & Yan Shi & Min Deng, 2023. "Spatial Layout Assessment of Urban Mining Pilot Bases in China Based on Multi-Source Data Collaboration," Sustainability, MDPI, vol. 15(10), pages 1-21, May.
    2. Starling, James K. & Mastrangelo, Christina & Choe, Youngjun, 2021. "Improving Weibull distribution estimation for generalized Type I censored data using modified SMOTE," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    3. Carine Lausselet & Johana Paola Forero Urrego & Eirik Resch & Helge Brattebø, 2021. "Temporal analysis of the material flows and embodied greenhouse gas emissions of a neighborhood building stock," Journal of Industrial Ecology, Yale University, vol. 25(2), pages 419-434, April.
    4. Acitas, Sukru & Aladag, Cagdas Hakan & Senoglu, Birdal, 2019. "A new approach for estimating the parameters of Weibull distribution via particle swarm optimization: An application to the strengths of glass fibre data," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 116-127.
    5. Yellishetty, Mohan & Ranjith, P.G. & Tharumarajah, A., 2010. "Iron ore and steel production trends and material flows in the world: Is this really sustainable?," Resources, Conservation & Recycling, Elsevier, vol. 54(12), pages 1084-1094.
    6. Huang, Chu-Long & Vause, Jonathan & Ma, Hwong-Wen & Yu, Chang-Ping, 2012. "Using material/substance flow analysis to support sustainable development assessment: A literature review and outlook," Resources, Conservation & Recycling, Elsevier, vol. 68(C), pages 104-116.
    7. Natthanij Soonsawad & Raymundo Marcos‐Martinez & Heinz Schandl, 2024. "City‐scale assessment of the material and environmental footprint of buildings using an advanced building information model: A case study from Canberra, Australia," Journal of Industrial Ecology, Yale University, vol. 28(2), pages 247-261, April.
    8. Zhang, Hanxin & Sun, Wenqiang & Li, Weidong & Ma, Guangyu, 2022. "A carbon flow tracing and carbon accounting method for exploring CO2 emissions of the iron and steel industry: An integrated material–energy–carbon hub," Applied Energy, Elsevier, vol. 309(C).
    9. Jakob Lederer & Johann Fellner & Andreas Gassner & Karin Gruhler & Georg Schiller, 2021. "Determining the material intensities of buildings selected by random sampling: A case study from Vienna," Journal of Industrial Ecology, Yale University, vol. 25(4), pages 848-863, August.
    10. Guo, Xueyi & Zhang, Jingxi & Tian, Qinghua, 2021. "Modeling the potential impact of future lithium recycling on lithium demand in China: A dynamic SFA approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    11. Carlos Mesta & Ramzy Kahhat & Sandra Santa‐Cruz, 2019. "Geospatial Characterization of Material Stock in the Residential Sector of a Latin‐American City," Journal of Industrial Ecology, Yale University, vol. 23(1), pages 280-291, February.
    12. Renyan Jiang, 2022. "A novel parameter estimation method for the Weibull distribution on heavily censored data," Journal of Risk and Reliability, , vol. 236(2), pages 307-316, April.
    13. Niko Heeren & Stefanie Hellweg, 2019. "Tracking Construction Material over Space and Time: Prospective and Geo‐referenced Modeling of Building Stocks and Construction Material Flows," Journal of Industrial Ecology, Yale University, vol. 23(1), pages 253-267, February.
    14. Alessio Miatto & Claudia Sartori & Martina Bianchi & Paolo Borin & Andrea Giordano & Shoshanna Saxe & T.E. Graedel, 2022. "Tracking the material cycle of Italian bricks with the aid of building information modeling," Journal of Industrial Ecology, Yale University, vol. 26(2), pages 609-626, April.
    15. Kronnaphat Khumvongsa & Jing Guo & Suthida Theepharaksapan & Hiroaki Shirakawa & Hiroki Tanikawa, 2023. "Uncovering urban transportation infrastructure expansion and sustainability challenge in Bangkok: Insights from a material stock perspective," Journal of Industrial Ecology, Yale University, vol. 27(2), pages 476-490, April.
    16. Regattieri, A. & Manzini, R. & Battini, D., 2010. "Estimating reliability characteristics in the presence of censored data: A case study in a light commercial vehicle manufacturing system," Reliability Engineering and System Safety, Elsevier, vol. 95(10), pages 1093-1102.
    17. Andreas Mayer & Willi Haas & Dominik Wiedenhofer & Fridolin Krausmann & Philip Nuss & Gian Andrea Blengini, 2019. "Measuring Progress towards a Circular Economy: A Monitoring Framework for Economy‐wide Material Loop Closing in the EU28," Journal of Industrial Ecology, Yale University, vol. 23(1), pages 62-76, February.
    18. Xuan, Yanni & Yue, Qiang, 2017. "Scenario analysis on resource and environmental benefits of imported steel scrap for China’s steel industry," Resources, Conservation & Recycling, Elsevier, vol. 120(C), pages 186-198.
    19. Jan Streeck & Quirin Dammerer & Dominik Wiedenhofer & Fridolin Krausmann, 2021. "The role of socio‐economic material stocks for natural resource use in the United States of America from 1870 to 2100," Journal of Industrial Ecology, Yale University, vol. 25(6), pages 1486-1502, December.
    20. Rafaela Tirado & Adélaïde Aublet & Sylvain Laurenceau & Mathieu Thorel & Mathilde Louërat & Guillaume Habert, 2021. "Component-Based Model for Building Material Stock and Waste-Flow Characterization: A Case in the Île-de-France Region," Sustainability, MDPI, vol. 13(23), pages 1-34, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10249-:d:1181686. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.