IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-256-9_79.html

Research on Energy Carbon Emission Situation Prediction Technology: A Case Study of Fujian Province

In: Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023)

Author

Listed:
  • Bidan Qiu

    (Quanzhou Electric Power Skill Institute)

  • Yusong Sun

    (State Grid Shanghai Electric Power Company Marketing Service Center)

  • Yiqiu Zheng

    (State Grid Anxi County Power Supply Company)

Abstract

In this paper, Fujian Province was taken as an example to build a general analysis framework for urban carbon emission analysis. Firstly, carbon emission was measured, and then the LMDI method was used to decompose the influencing factors of carbon emission from the aspects of energy structure, industrial structure, social and economic development level, etc. On this basis, the carbon emission trend was analyzed and predicted. A data mining method for carbon emission situation prediction of energy and electric power is proposed.

Suggested Citation

  • Bidan Qiu & Yusong Sun & Yiqiu Zheng, 2024. "Research on Energy Carbon Emission Situation Prediction Technology: A Case Study of Fujian Province," Advances in Economics, Business and Management Research, in: Suhaiza Hanim Binti Dato Mohamad Zailani & Kosga Yagapparaj & Norhayati Zakuan (ed.), Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023), pages 780-796, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-256-9_79
    DOI: 10.2991/978-94-6463-256-9_79
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:spr:advbcp:978-94-6463-256-9_79. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.