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大兴安岭地表死可燃物热解燃烧动力学的热重分析。

Thermogravimetric analysis of the pyrolysis and combustion kinetics of surface dead combustibles in the Daxing'an Mountains.

机构信息

Forestry College of Inner Mongolia Agricultural University, Hohhot, China.

National Orientation Observation and Research Station of Saihanwula Forest Ecosystem in Inner Mongolia, Chifeng, China.

出版信息

PLoS One. 2021 Dec 2;16(12):e0260790. doi: 10.1371/journal.pone.0260790. eCollection 2021.

DOI:10.1371/journal.pone.0260790
PMID:34855872
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8638970/
Abstract

In boreal regions, the frequency of forest fires is increasing. In this study, thermogravimetric analysis was used to analyze the pyrolysis kinetics of dead surface combustibles in different forest types within the Daxing'an Mountains, China. The results show that the combustible material load of forest types, the Larix forest (LG) is relatively high. Base on the E of kinetic parameters, the LG, and Quercus forest (QM) forest types had relatively high combustibility values and comprehensive combustibility values for 1-, 10-, and 100-h time lags. According to the obtained P values, the pyrolysis of dead surface fuels with 1-, 10-, and 100-h time lags is relatively difficult in the Larix / Betula mixed forest (L-B) and QM forest types. Therefore, mixed forests of the LG, L-B, and QM tree species can be established as fire-resistant forests to establish a fire barrier, reduce the combustibility of forest stands, and reduce the possibility of forest fires.

摘要

在北方地区,森林火灾的频率正在增加。本研究采用热重分析方法,分析了大兴安岭不同森林类型地表可燃物的热解动力学特性。结果表明,森林类型的可燃物负荷,落叶松林(LG)相对较高。基于动力学参数的 E 值,LG 和栎树林(QM)森林类型的 1-、10-和 100-h 时滞的可燃性值和综合可燃性值相对较高。根据获得的 P 值,在落叶松/桦木混交林(L-B)和 QM 森林类型中,具有 1-、10-和 100-h 时滞的地表死燃料的热解相对困难。因此,可以将 LG、L-B 和 QM 树种的混交林建立为防火林带,降低林分的可燃性,减少森林火灾的可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/810c/8638970/cf49dab25cb5/pone.0260790.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/810c/8638970/f93ef12450e3/pone.0260790.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/810c/8638970/7a95be586afc/pone.0260790.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/810c/8638970/4e2dce85995c/pone.0260790.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/810c/8638970/4f8beb14e4f9/pone.0260790.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/810c/8638970/cf49dab25cb5/pone.0260790.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/810c/8638970/f93ef12450e3/pone.0260790.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/810c/8638970/7a95be586afc/pone.0260790.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/810c/8638970/4e2dce85995c/pone.0260790.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/810c/8638970/4f8beb14e4f9/pone.0260790.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/810c/8638970/cf49dab25cb5/pone.0260790.g005.jpg

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