Preprints
https://doi.org/10.5194/gmd-2024-170
https://doi.org/10.5194/gmd-2024-170
Submitted as: model description paper
 | 
27 Sep 2024
Submitted as: model description paper |  | 27 Sep 2024
Status: this preprint is currently under review for the journal GMD.

China Wildfire Emission (ChinaWED v1) for the period 2012–2022

Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang

Abstract. During the past decades, wildfires have undergone rapid changes while both the extent of fire activities and the resulting greenhouse gas (GHG) emissions from wildfires in China remain inadequately quantified. To explore national wildfire-induced emissions, we employed satellite-based data on burned vegetation to generate the China Wildfire Emission Dataset (ChinaWED). This dataset is constructed at monthly and kilometer scale under a consistent and quantifiable calculation framework, providing an average annual estimates of wildfire-induced GHG emissions of 78.13 ± 22.46 Tg CO2, 279.47 ± 82.01 Gg CH4, and 6.26 ± 1.67 Gg N2O for the past decade. We observed significant decreases in both wildfire occurrences and emissions within forests and grasslands. This trend, however, is counteracted by increasing agricultural fires, which constitute the primary type accounting for at least half of the national total fire emissions. The seasonal cycle of wildfire GHG emissions show an evident apex occurring during the transition from mid-spring to early-summer. At the regional scale, Northeast, Southwest and East China emerge as hotspots for wildfire-induced emissions. Our study offers new insights into understanding China's wildfire dynamics and provides a detailed regional model for the wildfire greenhouse gas emissions over China.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang

Status: open (until 22 Nov 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2024-170', Anonymous Referee #1, 22 Oct 2024 reply
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang

Viewed

Total article views: 262 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
158 49 55 262 11 1 5
  • HTML: 158
  • PDF: 49
  • XML: 55
  • Total: 262
  • Supplement: 11
  • BibTeX: 1
  • EndNote: 5
Views and downloads (calculated since 27 Sep 2024)
Cumulative views and downloads (calculated since 27 Sep 2024)

Viewed (geographical distribution)

Total article views: 257 (including HTML, PDF, and XML) Thereof 257 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 14 Nov 2024
Download
Short summary
Wildfires release large amounts of greenhouse gases, contributing to global warming. We developed a new model that provides near-real-time estimates of wildfire emissions in China. Our model improves the accuracy of burned area measurements and incorporates advanced data in fuel loads and emission factors. We found that most emissions come from agricultural fires, while emissions from forests and grasslands are decreasing. This model will help reduce the environmental impacts of wildfires.