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Emission impacts of China’s solid waste import ban and COVID-19 in the copper supply chain

Author

Listed:
  • John Ryter

    (Massachusetts Institute of Technology)

  • Xinkai Fu

    (Massachusetts Institute of Technology)

  • Karan Bhuwalka

    (Massachusetts Institute of Technology)

  • Richard Roth

    (Massachusetts Institute of Technology)

  • Elsa A. Olivetti

    (Massachusetts Institute of Technology)

Abstract

Climate change will increase the frequency and severity of supply chain disruptions and large-scale economic crises, also prompting environmentally protective local policies. Here we use econometric time series analysis, inventory-driven price formation, dynamic material flow analysis, and life cycle assessment to model each copper supply chain actor’s response to China’s solid waste import ban and the COVID-19 pandemic. We demonstrate that the economic changes associated with China’s solid waste import ban increase primary refining within China, offsetting the environmental benefits of decreased copper scrap refining and generating a cumulative increase in CO2-equivalent emissions of up to 13 Mt by 2040. Increasing China’s refined copper imports reverses this trend, decreasing CO2e emissions in China (up to 180 Mt by 2040) and globally (up to 20 Mt). We test sensitivity to supply chain disruptions using GDP, mining, and refining shocks associated with the COVID-19 pandemic, showing the results translate onto disruption effects.

Suggested Citation

  • John Ryter & Xinkai Fu & Karan Bhuwalka & Richard Roth & Elsa A. Olivetti, 2021. "Emission impacts of China’s solid waste import ban and COVID-19 in the copper supply chain," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-23874-7
    DOI: 10.1038/s41467-021-23874-7
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    Cited by:

    1. Karan Bhuwalka & Eunseo Choi & Elizabeth A. Moore & Richard Roth & Randolph E. Kirchain & Elsa A. Olivetti, 2023. "A hierarchical Bayesian regression model that reduces uncertainty in material demand predictions," Journal of Industrial Ecology, Yale University, vol. 27(1), pages 43-55, February.
    2. Marashdeh, Hazem & Dhiaf, Mohamed M. & Atayah, Osama F. & Nasrallah, Nohade & Frederico, Guilherme F. & Najaf, Khakan, 2023. "Sensitivity of market performance to social risk index: Evidence from global listed companies in logistics and transportation industry," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).

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