IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i17p12738-d1222960.html
   My bibliography  Save this article

Carbon Emission Prediction Model for the Underground Mining Stage of Metal Mines

Author

Listed:
  • Gaofeng Ren

    (School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430074, China
    Key Laboratory of Green Utilization of Key Non-Metallic Mineral Resources, Ministry of Education, Wuhan University of Technology, Wuhan 430074, China)

  • Wei Wang

    (School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430074, China
    Key Laboratory of Green Utilization of Key Non-Metallic Mineral Resources, Ministry of Education, Wuhan University of Technology, Wuhan 430074, China
    Hubei Sanxin Gold-Copper Co., Ltd., Daye 435100, China)

  • Wenbo Wu

    (School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430074, China
    Key Laboratory of Green Utilization of Key Non-Metallic Mineral Resources, Ministry of Education, Wuhan University of Technology, Wuhan 430074, China)

  • Yong Hu

    (Hubei Sanxin Gold-Copper Co., Ltd., Daye 435100, China)

  • Yang Liu

    (Hubei Carbon Emission Trading Center Co., Ltd., Wuhan 430070, China)

Abstract

At present, the carbon emissions in China’s metal mining industry can be calculated based on the amount of energy consumed in the mining process. However, it is still difficult to predict the carbon emissions before implementation of mining engineering. There are no effective approaches that could reasonably estimate the amount of carbon emissions before mining. To this end, based on the ‘Top–down’ carbon emission accounting method recommended by the Intergovernmental Panel on Climate Change (IPCC), this study proposes a model to predict the greenhouse gases emitted in seven carbon-intensive mining stages, namely, drilling, blasting, ventilation, drainage, air compression, transportation, and backfilling. The contribution of this model is to enable a prediction of the accumulation of greenhouse gases based on the mining preliminary design of mine, rather than on the consumption of energy and materials commonly used in recent research. It also establishes the amount of carbon emissions generated by mining per unit cubic meter of ore rock as the minimum calculation unit for carbon emissions, which allows for the cost and footprint of carbon emissions in the mining process to become clearer. Then, a gold–copper mine is involved as a case study, and the greenhouse gas emissions were predicted employing its preliminary design. Among all the predicted results, the carbon emissions from air compression and ventilation are larger than others, reaching 22.00 kg CO 2 /m 3 and 10.10 kg CO 2 /m 3 , respectively. By contrast, the carbon emissions of rock drilling, drainage, and backfilling material pumping are 5.87 kg CO 2 /m 3 , 6.80 kg CO 2 /m 3 , and 7.79 kg CO 2 /m 3 , respectively. To validate the proposed model, the calculation results are compared with the actual energy consumption data of the mine. The estimated overall relative error is only 5.08%. The preliminary predictions of carbon emissions and carbon emission costs in mining before mineral investment were realized, thus helping mining companies to reduce their investment risk.

Suggested Citation

  • Gaofeng Ren & Wei Wang & Wenbo Wu & Yong Hu & Yang Liu, 2023. "Carbon Emission Prediction Model for the Underground Mining Stage of Metal Mines," Sustainability, MDPI, vol. 15(17), pages 1-19, August.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:17:p:12738-:d:1222960
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/17/12738/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/17/12738/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guoyu Wang & Jinsheng Zhou, 2022. "Multiobjective Optimization of Carbon Emission Reduction Responsibility Allocation in the Open-Pit Mine Production Process against the Background of Peak Carbon Dioxide Emissions," Sustainability, MDPI, vol. 14(15), pages 1-21, August.
    2. Benzheng Li & Yongkui Shi & Jian Hao & Chengyun Ma & Chuming Pang & Huidi Yang, 2022. "Research on a Carbon Emission Calculation Model and Method for an Underground Fully Mechanized Mining Process," Energies, MDPI, vol. 15(8), pages 1-15, April.
    3. Liu, Yang & Zhang, Congrui & Xu, Xiaochuan & Ge, Yongxiang & Ren, Gaofeng, 2022. "Assessment of energy conservation potential and cost in open-pit metal mines: Bottom-up approach integrated energy conservation supply curve and ultimate pit limit," Energy Policy, Elsevier, vol. 163(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ye Yang & Zegen Wang & Ying Zhang & Jiulin Jiang & Jiwu He, 2023. "Spatial and Temporal Patterns of Green Energy Development in China," Sustainability, MDPI, vol. 15(22), pages 1-15, November.

    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. Aubaid Ullah & Nur Awanis Hashim & Mohamad Fairus Rabuni & Mohd Usman Mohd Junaidi, 2023. "A Review on Methanol as a Clean Energy Carrier: Roles of Zeolite in Improving Production Efficiency," Energies, MDPI, vol. 16(3), pages 1-35, February.
    2. Svetlana Ivanova & Anna Vesnina & Nataly Fotina & Alexander Prosekov, 2022. "An Overview of Carbon Footprint of Coal Mining to Curtail Greenhouse Gas Emissions," Sustainability, MDPI, vol. 14(22), pages 1-22, November.
    3. Agnieszka Saramak & Daniel Saramak, 2022. "Coal Modeling Investigations in International Collaboration in the Light of Bibliometric Analysis of the Problem," Energies, MDPI, vol. 15(16), pages 1-20, August.

    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:17:p:12738-:d:1222960. 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.