IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v394y2025ics0306261925008888.html
   My bibliography  Save this article

Advanced optimization algorithms for enhanced urban block-scale carbon accounting: A case study from Beijing, China

Author

Listed:
  • Zhao, Jing
  • Ren, Yujie
  • Tang, Xiaolan

Abstract

Urban carbon emissions have garnered significant attention following the establishment and implementation of global carbon neutrality goals. Accurate carbon accounting in urban areas is crucial for formulating effective emission reduction strategies and assessing their effectiveness. However, the mixed-use nature of urban land presents significant challenges to precise carbon accounting. This study adopts the perspective of urban community living circles and leverages optimization algorithms and the inventory method to propose a novel carbon accounting method that addresses these challenges. Furthermore, this method's reliability was validated through an analysis of eight land parcels with varying spatial configurations in the Beijing area, along with comprehensive sensitivity analyses, while its practical applications were also explored. The findings are as follows: (1) The urban block-scale carbon accounting method optimizes population allocation across industries and incorporates land-use policies into objective function constraints, enhancing both accuracy and applicability. (2) In Beijing's functional core area, annual carbon emissions within the 5–15-min standard-scale living circles were 8.43 ktC, 24.95 ktC, and 151.95 ktC, respectively, with an emission intensity of 810.42 tC/ha in the 10–15-min zone. (3) Urban functional and residential land collectively accounted for approximately 97 % of total emissions, with urban functional land exerting a greater impact. This study presents a reliable, robust, and systematic urban block-scale carbon accounting method that integrates carbon management with land-use policies, demonstrating significant practical value.

Suggested Citation

  • Zhao, Jing & Ren, Yujie & Tang, Xiaolan, 2025. "Advanced optimization algorithms for enhanced urban block-scale carbon accounting: A case study from Beijing, China," Applied Energy, Elsevier, vol. 394(C).
  • Handle: RePEc:eee:appene:v:394:y:2025:i:c:s0306261925008888
    DOI: 10.1016/j.apenergy.2025.126158
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261925008888
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2025.126158?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:eee:appene:v:394:y:2025:i:c:s0306261925008888. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.