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Co-production of steel and chemicals to mitigate hard-to-abate carbon emissions

Nature Chemical Engineering volume 1, pages 365–375 (2024)Cite this article

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Abstract

Hard-to-abate sectors emitted ~30% of global CO2 emissions in 2018. As the world’s largest producer of chemicals and steel, China’s mitigation efforts in these sectors are crucial. Here we examine the greenhouse gas mitigation and costs of co-producing steel and chemicals in China by extracting H2 and CO from steelmaking off-gas for chemical production and using a customized optimization model with a life-cycle assessment. Without carbon pricing, co-production reduces greenhouse gas emissions by 36 MtCO2eq yr−1 (−7%) and costs by 1.5 billion CNY per year (−1%) relative to independent production. A carbon price of 350 CNY per tCO2 enhances emissions and cost reductions to 113 MtCO2eq yr−1 (−22%) and 25.5 billion CNY per year (−10%), respectively. Furthermore, 60% of total emissions and cost reductions can be achieved via 24% of connections, ~50% of which are in Hebei, Henan, Shanxi and Shandong provinces. This study demonstrates the cost-effectiveness of using co-production to mitigate these hard-to-abate emissions and the importance of targeting critical connections to obtain the majority of reductions.

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Fig. 1: Changes in GHG emissions and costs per tonne of H2 or CO used for co-production relative to independent production.
Fig. 2: Supply of H2 and CO from steel plants and demand for H2 and CO in coal chemical plants in China.
Fig. 3: GHG mitigation rates and cost reduction rates in co-production relative to independent production across carbon prices and pipeline length limits.
Fig. 4: Changes in GHG emissions and costs by industrial process in co-production relative to independent production.
Fig. 5: Cost-effective supply of H2 and CO in the co-production from origin provinces (rows) to destination provinces (columns).
Fig. 6: Onsite GHG mitigation of H2 and CO connections in co-production relative to independent production.

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Data availability

Source data are provided with this paper. All data and parameters used for this study are provided in Source data and Supplementary Information.

Code availability

Each component of our model is detailed in Supplementary Information with parameterizations provided for each step. The codes for the optimization algorithms and mapping of grid boxes are available via GitHub at https://github.com/indsyn/Steel-chemical (ref. 43).

Change history

  • 03 May 2024

    In the version of the article initially published, the graphical abstract was missing and has now been added.

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Acknowledgements

The authors thank Princeton University for financial support. Y.G. acknowledges the support from the Schmidt Science Fellows, in partnership with the Rhodes Trust. The funders had no role in study design, data collection and analysis, or decision to publish or preparation of the manuscript.

Author information

Author notes

  1. Yang Guo

    Present address: College of Design and Engineering, National University of Singapore, Singapore, Singapore

  2. These authors contributed equally: Yang Guo, Jieyi Lu.

Authors and Affiliations

  1. Princeton School of Public and International Affairs, Princeton University, Princeton, NJ, USA

    Yang Guo, Jieyi Lu & Denise L. Mauzerall

  2. State Environmental Protection Key Laboratory of Eco-Industry, Northeastern University, Shenyang, China

    Qi Zhang

  3. Peking University Pioneer Technology Co. Ltd, Beijing, China

    Yunling Cao

  4. School of Environment, Tsinghua University, Beijing, China

    Lyujun Chen

  5. Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA

    Denise L. Mauzerall

Authors
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Contributions

Y.G. and D.L.M. conceived the research idea. Y.G., J.L. and D.L.M. designed the study procedures; Y.G. and J.L. compiled the database and configured the scenarios; Y.G. conducted the parameterizations and modeling; Y.G. and J.L. made the figures and tables; J.L., Q.Z., Y.C. and L.C. contributed to parameterizations; Y.G., J.L., Q.Z., Y.C., L.C. and D.L.M. analyzed the results; Y.G., J.L. and D.L.M. wrote the paper with contributions from all authors.

Corresponding authors

Correspondence to Yang Guo or Denise L. Mauzerall.

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Peer review information

Nature Chemical Engineering thanks the anonymous reviewers for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Notes 1–7, Tables 1–11, Figs. 1–4 and References.

Reporting Summary

Supplementary Data

Source data for supplementary figures and the inventory of steel and coal chemical plants.

Source data

Source Data Fig. 1

Changes in GHG emissions and costs per tonne of H2 or CO used for co-production relative to independent production.

Source Data Fig. 2

Supply of H2 and CO from steel plants and demand for H2 and CO in coal chemical plants in China.

Source Data Fig. 3

GHG mitigation rates and cost reduction rates in co-production relative to independent production across carbon prices and pipeline length limits.

Source Data Fig. 4

Changes in GHG emissions and costs by industrial process in co-production relative to independent production.

Source Data Fig. 5

Cost-effective supply of H2 and CO in the co-production from origin provinces (rows) to destination provinces (columns).

Source Data Fig. 6

Onsite GHG mitigation of H2 and CO connections in co-production relative to independent production.

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Guo, Y., Lu, J., Zhang, Q. et al. Co-production of steel and chemicals to mitigate hard-to-abate carbon emissions. Nat Chem Eng 1, 365–375 (2024). https://doi.org/10.1038/s44286-024-00061-1

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