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Accounting CO 2 Emissions of the Cement Industry: Based on an Electricity–Carbon Coupling Analysis

Author

Listed:
  • Chunlei Zhou

    (Big Data Center of State Grid Corporation of China, Beijing 100052, China)

  • Donghai Xuan

    (Big Data Center of State Grid Corporation of China, Beijing 100052, China)

  • Yuhan Miao

    (Sichuan Energy Internet Research Institute, Tsinghua University, Chengdu 610042, China
    Beijing Circular Sound Energy Technology Co., Ltd., Beijing 100012, China)

  • Xiaohu Luo

    (Beijing Circular Sound Energy Technology Co., Ltd., Beijing 100012, China)

  • Wensi Liu

    (Big Data Center of State Grid Corporation of China, Beijing 100052, China)

  • Yihong Zhang

    (Big Data Center of State Grid Corporation of China, Beijing 100052, China)

Abstract

Since the cement industry acts as a significant contributor to carbon emissions in China, China’s national emission trading system has announced that it should be included in the system soon. However, current cement carbon accounting methods require high-resolution data from various processes on the production line, making it a cumbersome and costly process. To address this issue, this study explores the feasibility and reliability of using machine learning algorithms to develop electricity–carbon models. These models estimate carbon emissions based solely on electricity data, enabling faster and more cost-effective accounting of carbon in cement production. This study investigates the correlations between electricity data and carbon emissions for a large cement manufacturer in southern China. It compares the performance of models based on the supply of electricity (purchased electricity and waste heat electricity) with those based on the consumption of electricity (electricity used on the grinding machines in the production lines) to identify the key factor for carbon emission calculations. The identified best performing model showed high accuracy, with an R 2 of 0.96, an RMSPE of 3.88%, and a MAPE of 2.56%. Based on this, the novel electricity–carbon model has the potential to act as one of the optional methods for carbon emissions accounting in the cement industry and to support carbon emissions data promotion within China’s national emission trading systems.

Suggested Citation

  • Chunlei Zhou & Donghai Xuan & Yuhan Miao & Xiaohu Luo & Wensi Liu & Yihong Zhang, 2023. "Accounting CO 2 Emissions of the Cement Industry: Based on an Electricity–Carbon Coupling Analysis," Energies, MDPI, vol. 16(11), pages 1-13, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:11:p:4453-:d:1160897
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    References listed on IDEAS

    as
    1. Tan, Chang & Yu, Xiang & Guan, Yuru, 2022. "A technology-driven pathway to net-zero carbon emissions for China's cement industry," Applied Energy, Elsevier, vol. 325(C).
    2. World Bank, "undated". "State and Trends of Carbon Pricing 2020 [Situación y tendencias de la fijación del precio al carbono 2020]," World Bank Publications - Reports 33809, The World Bank Group.
    3. Zhang, Xuehua & Schreifels, Jeremy, 2011. "Continuous emission monitoring systems at power plants in China: Improving SO2 emission measurement," Energy Policy, Elsevier, vol. 39(11), pages 7432-7438.
    4. Li, Wei & Gao, Shubin, 2018. "Prospective on energy related carbon emissions peak integrating optimized intelligent algorithm with dry process technique application for China's cement industry," Energy, Elsevier, vol. 165(PB), pages 33-54.
    5. Jinying Li & Xin Tan & Jinchao Li, 2018. "Research on Dynamic Facility Layout Problem of Manufacturing Unit Considering Human Factors," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-13, January.
    6. Iman Junianto & Sunardi & Dadan Sumiarsa, 2023. "The Possibility of Achieving Zero CO 2 Emission in the Indonesian Cement Industry by 2050: A Stakeholder System Dynamic Perspective," Sustainability, MDPI, vol. 15(7), pages 1-16, March.
    7. Zhu Liu & Dabo Guan & Wei Wei & Steven J. Davis & Philippe Ciais & Jin Bai & Shushi Peng & Qiang Zhang & Klaus Hubacek & Gregg Marland & Robert J. Andres & Douglas Crawford-Brown & Jintai Lin & Hongya, 2015. "Reduced carbon emission estimates from fossil fuel combustion and cement production in China," Nature, Nature, vol. 524(7565), pages 335-338, August.
    8. Chou, Jui-Sheng & Tran, Duc-Son, 2018. "Forecasting energy consumption time series using machine learning techniques based on usage patterns of residential householders," Energy, Elsevier, vol. 165(PB), pages 709-726.
    9. Xu, Jin-Hua & Fleiter, Tobias & Eichhammer, Wolfgang & Fan, Ying, 2012. "Energy consumption and CO2 emissions in China's cement industry: A perspective from LMDI decomposition analysis," Energy Policy, Elsevier, vol. 50(C), pages 821-832.
    10. Lean, Hooi Hooi & Smyth, Russell, 2010. "CO2 emissions, electricity consumption and output in ASEAN," Applied Energy, Elsevier, vol. 87(6), pages 1858-1864, June.
    11. Jiang, Qingquan & Khattak, Shoukat Iqbal & Rahman, Zia Ur, 2021. "Measuring the simultaneous effects of electricity consumption and production on carbon dioxide emissions (CO2e) in China: New evidence from an EKC-based assessment," Energy, Elsevier, vol. 229(C).
    12. Song, Dan & Yang, Jin & Chen, Bin & Hayat, Tasawar & Alsaedi, Ahmed, 2016. "Life-cycle environmental impact analysis of a typical cement production chain," Applied Energy, Elsevier, vol. 164(C), pages 916-923.
    13. Ofosu-Adarkwa, Jeffrey & Xie, Naiming & Javed, Saad Ahmed, 2020. "Forecasting CO2 emissions of China's cement industry using a hybrid Verhulst-GM(1,N) model and emissions' technical conversion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    14. Fan, Junliang & Zheng, Jing & Wu, Lifeng & Zhang, Fucang, 2021. "Estimation of daily maize transpiration using support vector machines, extreme gradient boosting, artificial and deep neural networks models," Agricultural Water Management, Elsevier, vol. 245(C).
    15. Talaei, Alireza & Pier, David & Iyer, Aishwarya V. & Ahiduzzaman, Md & Kumar, Amit, 2019. "Assessment of long-term energy efficiency improvement and greenhouse gas emissions mitigation options for the cement industry," Energy, Elsevier, vol. 170(C), pages 1051-1066.
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