IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v226y2024ics0960148124004038.html
   My bibliography  Save this article

Thermogravimetric analysis of co-combustion characteristics of sewage sludge and bamboo scraps combined with artificial neural networks

Author

Listed:
  • Liu, Xiang
  • Bi, Haobo
  • Tian, Junjian
  • Ni, Zhanshi
  • Shi, Hao
  • Yao, Yurou
  • Meng, Kesheng
  • Wang, Jian
  • Lin, Qizhao

Abstract

The increasing amount of sludge resources has brought great challenges to the ecological environment and sustainable development. Co-combustion of low calorific value sewage sludge and biosolid waste has become a new and effective way to treat sludge. The co-combustion characteristics of sewage sludge and bamboo scraps in air were studied by thermogravimetric mass spectrometry and artificial neural network. The thermogravimetric analysis of combustion at three different heating rates was performed with five different mixing ratios. Through comprehensive combustion index and cooperative analysis, it is concluded that the co-burning effect and cooperative effect of sludge and bamboo are better. Flynn-Wall-Ozawa and Kissinger-Akahira-Sunose were used to calculate the apparent activation energy. The average activation energy of the sludge mixed with 75% bamboo scraps was the lowest (126.3 kJ mol−1) under the co-combustion condition. The ion current of combustion gas products during combustion was studied by mass spectrometry. Co-combustion can increase NOx and reduce SO2, and 75% bamboo slag mixed sludge has the least gas production. Finally, the prediction model of sludge co-combustion is established by artificial neural network, which provides a prospective guidance for the resource utilization of solid waste.

Suggested Citation

  • Liu, Xiang & Bi, Haobo & Tian, Junjian & Ni, Zhanshi & Shi, Hao & Yao, Yurou & Meng, Kesheng & Wang, Jian & Lin, Qizhao, 2024. "Thermogravimetric analysis of co-combustion characteristics of sewage sludge and bamboo scraps combined with artificial neural networks," Renewable Energy, Elsevier, vol. 226(C).
  • Handle: RePEc:eee:renene:v:226:y:2024:i:c:s0960148124004038
    DOI: 10.1016/j.renene.2024.120338
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124004038
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2024.120338?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:renene:v:226:y:2024:i:c:s0960148124004038. 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.journals.elsevier.com/renewable-energy .

    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.