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Based on the Time-Spatial Power-Based Cryptocurrency Miner Driving Force Model, Establish a Global CO 2 Emission Prediction Framework after China Bans Cryptocurrency

Author

Listed:
  • Xuejia Sang

    (School of Software Engineering, Chengdu University of Information Technology, Chengdu 610225, China)

  • Xiaopeng Leng

    (Computer and Cyber Security College, Chengdu University of Technology, Chengdu 610059, China)

  • Linfu Xue

    (College of Earth Science, Jilin University, Changchun 130061, China
    Technology Innovation Center of Big Data Analysis and Application of Earth Science, Ministry of Natural Resources, Changchun 130061, China)

  • Xiangjin Ran

    (College of Earth Science, Jilin University, Changchun 130061, China
    Technology Innovation Center of Big Data Analysis and Application of Earth Science, Ministry of Natural Resources, Changchun 130061, China)

Abstract

The energy consumption and carbon footprint of cryptocurrencies have always been a popular topic. However, most of the existing studies only focus on one cryptocurrency, Bitcoin, and there is a lack of long-term monitoring studies that summarize all cryptocurrencies. By constructing a time series hash rate/power model, this research obtained the 10-year time series data on energy consumption dataset of global top-25 cryptocurrencies for the first time. Both the temporal coverage and the spatiotemporal resolution of the data exceed previous studies. The results show that Bitcoin’s power consumption only accounts for 58% of the top-25 cryptocurrencies. After China bans cryptocurrencies, the conservative change in global CO 2 emissions from 2020 will be between −0.4% and 4.4%, and Central Asian countries such as Kazakhstan are likely to become areas of rapid growth in carbon emissions from cryptocurrencies.

Suggested Citation

  • Xuejia Sang & Xiaopeng Leng & Linfu Xue & Xiangjin Ran, 2022. "Based on the Time-Spatial Power-Based Cryptocurrency Miner Driving Force Model, Establish a Global CO 2 Emission Prediction Framework after China Bans Cryptocurrency," Sustainability, MDPI, vol. 14(9), pages 1-18, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5332-:d:804564
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    References listed on IDEAS

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    Cited by:

    1. Junwu Wang & Yinghui Song & Wei Wang & Suikuan Wang & Feng Guo & Jiequn Lu, 2022. "Marine Construction Waste Recycling Mechanism Considering Public Participation and Carbon Trading: A Study on Dynamic Modeling and Simulation Based on Sustainability Policy," Sustainability, MDPI, vol. 14(16), pages 1-22, August.
    2. Zhi Yang & Wenping Li & Liangning Li & Shaogang Lei & Jiawei Tian & Gang Wang & Xuejia Sang, 2022. "Spatiotemporal Variation and Influencing Factors of Vegetation Growth in Mining Areas: A Case Study in a Colliery in Northern China," Sustainability, MDPI, vol. 14(15), pages 1-19, August.

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