IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i16p10316-d892273.html
   My bibliography  Save this article

A Novel Credible Carbon Footprint Traceability System for Low Carbon Economy Using Blockchain Technology

Author

Listed:
  • Chunhua Ju

    (Department of Modern Business Research Center, Zhejiang Gongshang University, Hangzhou 310018, China
    School of Management Engineering and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China)

  • Zhonghua Shen

    (School of Management Engineering and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China)

  • Fuguang Bao

    (Department of Modern Business Research Center, Zhejiang Gongshang University, Hangzhou 310018, China
    School of Management Engineering and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China
    Academy of Zhejiang Culture Industry Innovation and Development, Zhejiang Gongshang University, Hangzhou 310018, China)

  • Pengtong Weng

    (School of Management Engineering and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China)

  • Yihang Xu

    (School of Management Engineering and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China)

  • Chonghuan Xu

    (Academy of Zhejiang Culture Industry Innovation and Development, Zhejiang Gongshang University, Hangzhou 310018, China
    School of Business Administration, Zhejiang Gongshang University, Hangzhou 310018, China)

Abstract

To achieve the goal of carbon neutrality, many countries have established regional carbon emission trading markets and tried to build a low-carbon economic system. At present, the implementation of carbon emission trading and low-carbon economic systems faces many challenges such as manipulation, corruption, opacity, lack of trust, and lack of data tracking means. The application of blockchain technology can perfectly solve the above problems. However, the data recorded on a blockchain are often multi-type and heterogeneous, and users at different levels such as regulators, enterprises, and consumers have different requirements for data types and granularity. This requires a quick and trustworthy method for monitoring the carbon footprint of enterprises and products. In this paper, the carbon footprint traceability of enterprises and products is taken as an application scenario, and the distributed traceability concept of “traceability off the chain and verification on the chain” is adopted. By reconstructing the pointer of the file structure of the distributed storage, an interactive traceability structure supporting type filtering is constructed, which enables fast retrieval and locating of carbon emission data in the mixed data on the chain. The experimental results show that using the interactive traceability structure that supports type filtering for traceability not only releases the computing power of full nodes but also greatly improves the traceability efficiency of the long-span transaction chain. The proposed carbon footprint traceability system can rapidly trace and track data on an enterprise’s and a product’s carbon footprint, as well as meet the needs of users at all levels for traceability. It also offers more advantages when handling large amounts of data requests.

Suggested Citation

  • Chunhua Ju & Zhonghua Shen & Fuguang Bao & Pengtong Weng & Yihang Xu & Chonghuan Xu, 2022. "A Novel Credible Carbon Footprint Traceability System for Low Carbon Economy Using Blockchain Technology," IJERPH, MDPI, vol. 19(16), pages 1-16, August.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:16:p:10316-:d:892273
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/16/10316/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/16/10316/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guillaume Chapron, 2017. "The environment needs cryptogovernance," Nature, Nature, vol. 545(7655), pages 403-405, May.
    2. Michael Wang & Bill Wang & Ahmad Abareshi, 2020. "Blockchain Technology and Its Role in Enhancing Supply Chain Integration Capability and Reducing Carbon Emission: A Conceptual Framework," Sustainability, MDPI, vol. 12(24), pages 1-17, December.
    3. Liobikienė, Genovaitė & Butkus, Mindaugas, 2019. "Scale, composition, and technique effects through which the economic growth, foreign direct investment, urbanization, and trade affect greenhouse gas emissions," Renewable Energy, Elsevier, vol. 132(C), pages 1310-1322.
    4. Fangyuan Zhao & Wai Kin (Victor) Chan, 2020. "When Is Blockchain Worth It? A Case Study of Carbon Trading," Energies, MDPI, vol. 13(8), pages 1-28, April.
    5. Changping Zhao & Juanjuan Sun & Yu Gong & Zhi Li & Peter Zhou, 2022. "Research on the Blue Carbon Trading Market System under Blockchain Technology," Energies, MDPI, vol. 15(9), pages 1-17, April.
    6. Hua, Weiqi & Jiang, Jing & Sun, Hongjian & Wu, Jianzhong, 2020. "A blockchain based peer-to-peer trading framework integrating energy and carbon markets," Applied Energy, Elsevier, vol. 279(C).
    7. Chonghuan Xu & Dongsheng Liu & Xinyao Mei, 2021. "Exploring an Efficient POI Recommendation Model Based on User Characteristics and Spatial-Temporal Factors," Mathematics, MDPI, vol. 9(21), pages 1-17, October.
    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. Hanghang Dong & Jun Yang & Xiaoming Li & Lan Xu, 2024. "Explore the Impact Mechanism of Block Chain Technology on China's Carbon Market," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 105-135, July.
    2. Chen Zhang & Yaoqun Xu & Yi Zheng, 2024. "Blockchain Traceability Adoption in Low-Carbon Supply Chains: An Evolutionary Game Analysis," Sustainability, MDPI, vol. 16(5), pages 1-23, February.

    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. Arsenii Vilkov & Gang Tian, 2023. "Blockchain’s Scope and Purpose in Carbon Markets: A Systematic Literature Review," Sustainability, MDPI, vol. 15(11), pages 1-27, May.
    2. Rui Sun & Dayi He & Jingjing Yan & Li Tao, 2021. "Mechanism Analysis of Applying Blockchain Technology to Forestry Carbon Sink Projects Based on the Differential Game Model," Sustainability, MDPI, vol. 13(21), pages 1-18, October.
    3. Rahel Mandaroux & Chuanwen Dong & Guodong Li, 2021. "A European Emissions Trading System Powered by Distributed Ledger Technology: An Evaluation Framework," Sustainability, MDPI, vol. 13(4), pages 1-21, February.
    4. Hanghang Dong & Jun Yang & Xiaoming Li & Lan Xu, 2024. "Explore the Impact Mechanism of Block Chain Technology on China's Carbon Market," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 105-135, July.
    5. Xiangyang Yu & Xiaojing Wang, 2023. "Research on Carbon-Trading Model of Urban Public Transport Based on Blockchain Technology," Energies, MDPI, vol. 16(6), pages 1-21, March.
    6. Emrah Kocak & Hayriye Hilal Baglitas, 2022. "The path to sustainable municipal solid waste management: Do human development, energy efficiency, and income inequality matter?," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(6), pages 1947-1962, December.
    7. Wang, Dongxue & Fan, Ruguo & Yang, Peiwen & Du, Kang & Xu, Xiaoxia & Chen, Rongkai, 2024. "Research on floating real-time pricing strategy for microgrid operator in local energy market considering shared energy storage leasing," Applied Energy, Elsevier, vol. 368(C).
    8. Ling Bai & Tianran Guo & Wei Xu & Kang Luo, 2022. "The Spatial Differentiation and Driving Forces of Ecological Welfare Performance in the Yangtze River Economic Belt," IJERPH, MDPI, vol. 19(22), pages 1-21, November.
    9. Büttgen, Marion & al.,, 2021. "Blockchain in Service Management and Service Research - Developing a Research Agenda and Managerial Implications," SMR - Journal of Service Management Research, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 5(2), pages 71-102.
    10. Vincent Carrières & Andrée-Anne Lemieux & Manuele Margni & Robert Pellerin & Sylvain Cariou, 2022. "Measuring the Value of Blockchain Traceability in Supporting LCA for Textile Products," Sustainability, MDPI, vol. 14(4), pages 1-15, February.
    11. Erna Farina Mohamed & Azlina Abdullah & Amar Hisham Jaaffar, 2024. "Energy Efficiency in Developing Countries: A Systematic Review of Current Findings and Directions towards a Net Zero Economy," International Journal of Energy Economics and Policy, Econjournals, vol. 14(5), pages 495-508, September.
    12. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Zhao, Yunlong & Gao, Chong, 2023. "A stochastic hierarchical optimization and revenue allocation approach for multi-regional integrated energy systems based on cooperative games," Applied Energy, Elsevier, vol. 350(C).
    13. Magdalena Rusch & Josef‐Peter Schöggl & Rupert J. Baumgartner, 2023. "Application of digital technologies for sustainable product management in a circular economy: A review," Business Strategy and the Environment, Wiley Blackwell, vol. 32(3), pages 1159-1174, March.
    14. Guanghui Qiao & Liu Ding & Keheng Xiang & Bruce Prideaux & Jinyi Xu, 2022. "Understanding the Value of Tourism to Seniors’ Health and Positive Aging," IJERPH, MDPI, vol. 19(3), pages 1-17, January.
    15. Wang, Juan & Zheng, Junjun & Yu, Liukai & Goh, Mark & Tang, Yunying & Huang, Yongchao, 2023. "Distributed Reputation-Distance iterative auction system for Peer-To-Peer power trading," Applied Energy, Elsevier, vol. 345(C).
    16. Li, Ruizhi & Yan, Xiaohe & Liu, Nian, 2022. "Hybrid energy sharing considering network cost for prosumers in integrated energy systems," Applied Energy, Elsevier, vol. 323(C).
    17. Pavel Ciaian & Andrej Cupak & Pirmin Fessler & d'Artis Kancs, 2022. "Environmental-Social-Governance Preferences and Investments in Crypto-Assets (Pavel Ciaian, Andrej Cupak, Pirmin Fessler, d’Artis Kancs)," Working Papers 243, Oesterreichische Nationalbank (Austrian Central Bank).
    18. Xu, Yingying & Dai, Yifan & Guo, Lingling & Chen, Jingjing, 2024. "Leveraging machine learning to forecast carbon returns: Factors from energy markets," Applied Energy, Elsevier, vol. 357(C).
    19. Sara Khan & Uzma Amin & Ahmed Abu-Siada, 2024. "P2P Energy Trading of EVs Using Blockchain Technology in Centralized and Decentralized Networks: A Review," Energies, MDPI, vol. 17(9), pages 1-17, April.
    20. Kangyin Dong & Xiucheng Dong & Qingzhe Jiang, 2020. "How renewable energy consumption lower global CO2 emissions? Evidence from countries with different income levels," The World Economy, Wiley Blackwell, vol. 43(6), pages 1665-1698, June.

    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:jijerp:v:19:y:2022:i:16:p:10316-:d:892273. 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.