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Laboratory investigation of the spontaneous combustion characteristics and mechanisms of typical vegetable oils

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  • Guo, Qian
  • Tang, Yibo

Abstract

To effectively prevent and control the autoignition of vegetable oil, the spontaneous combustion characteristics and oxidation mechanisms of three typical vegetable oils were investigated. Microcal, TG-DSC, Raman spectroscopy and GC-MS were used to analyze the self-ignition characteristics of the samples at both macro- and micro-scales. The results showed that the initial exothermic temperatures were between 65 and 90 °C, after which vigorous oxidation began to release abundant heat. DSC data showed that the entire combustion process of the samples includes 4 typical stages: low-temperature oxidation stage, thermal decomposition stage, combustion stage, and after-combustion stage. The activation energy of the low-temperature oxidation stage reached as low as 33.13 kJ/mol, indicating that the vegetable oil is extremely prone to self-oxidation even when the temperature <200 °C. And the self-ignition tendency was in the order linseed oil > perilla seed oil > safflower seed oil. Based on analysis of the organic molecular structures, it was found that the unsaturated groups in vegetable oil are responsible for its autoignition behavior. Taking linseed oil as an example, 3 peroxide intermediates, namely 10,12-Octadecadienoicacid,9-hydroperoxy-, (10E,12Z)-;9,11-Octadecadienoicacid, 13-hydroperoxy-, (9Z,11E, 13S)-, and 9-Octadecenoic acid, 13-hydroperoxy-, (Z)-(8CI, 9CI) were marked as significant indicators to trace the low temperature oxidation reaction path of the oil samples.

Suggested Citation

  • Guo, Qian & Tang, Yibo, 2022. "Laboratory investigation of the spontaneous combustion characteristics and mechanisms of typical vegetable oils," Energy, Elsevier, vol. 241(C).
    • Handle: RePEc:eee:energy:v:241:y:2022:i:c:s0360544221031364
    DOI: 10.1016/j.energy.2021.122887
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    References listed on IDEAS

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    1. Bi, Haobo & Wang, Chengxin & Lin, Qizhao & Jiang, Xuedan & Jiang, Chunlong & Bao, Lin, 2020. "Combustion behavior, kinetics, gas emission characteristics and artificial neural network modeling of coal gangue and biomass via TG-FTIR," Energy, Elsevier, vol. 213(C).
    2. Fang, Peiwen & Gong, Zhiqiang & Wang, Zhenbo & Wang, Zhentong & Meng, Fanzhi, 2019. "Study on combustion and emission characteristics of microalgae and its extraction residue with TG-MS," Renewable Energy, Elsevier, vol. 140(C), pages 884-894.
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    1. Kijo-Kleczkowska, Agnieszka & Gnatowski, Adam & Krzywanski, Jaroslaw & Gajek, Marcin & Szumera, Magdalena & Tora, Barbara & Kogut, Krzysztof & Knaś, Krzysztof, 2024. "Experimental research and prediction of heat generation during plastics, coal and biomass waste combustion using thermal analysis methods," Energy, Elsevier, vol. 290(C).

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