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Greenhouse gas emission in the whole process of forest fire including rescue: a case of forest fire in Beibei District of Chongqing.

Sihan JiYugang WangLei HeZhixiao ZhangFanqiang MengXiru LiYi ChenDongmei WangZhengjun Gong
Published in: Environmental science and pollution research international (2023)
In the context of global high temperature, the harm of greenhouse gases (GHG) emissions caused by frequent forest fires to the environment cannot be ignored. Existing research only calculates the GHG generated by the burning of forest vegetation, ignoring the GHG generated by the fire-driven social rescue activities. Taking the forest fire in Beibei District, Chongqing City, China , as an example, this paper studies and establishes the GHG emission accounting method for the whole process of forest fire from ignition to fire extinguishing through three processes: vegetation burning, rescue transportation, and on-site fire extinguishing. It covers three GHG calculation types: biomass burning, traffic activity level comprehensive energy consumption, and machine energy consumption. Among them, the CO 2 produced by the burning of coniferous forest, the support transportation of rescue teams in Yunnan province, and the motorcycle transportation at the fire extinguishing site accounted for a relatively high proportion in the corresponding processes, reaching 12,761.445 t, 118.750 t, and 1056.980 t, respectively. Finally, through data analysis, suggestions on GHG emission reduction related to forest tree regulation and optimization of rescue and fire extinguishing management are put forward, which provides a direction for future research on carbon reduction in the whole process of forest fire events.
Keyphrases
  • climate change
  • data analysis
  • south africa
  • mental health
  • healthcare
  • air pollution
  • machine learning
  • high temperature
  • wastewater treatment
  • drug induced