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

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

doi:https://doi.org/10.5194/gmd-18-2509-2025

Articles | Volume 18, issue 9

https://doi.org/10.5194/gmd-18-2509-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-18-2509-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 9

Model description paper

|

06 May 2025

Model description paper |

| 06 May 2025

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

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

Supplement

https://doi.org/10.5194/gmd-18-2509-2025-supplement

Data sets

Code for China Wildfire Emission Dataset (ChinaWED) [Data set] Zhengyang Lin and Xuhui Wang https://doi.org/10.5281/zenodo.13800556

MODIS/Terra+Aqua Burned Area Monthly L3 Global 500 m SIN Grid V061 [Data set] L. Giglio et al. https://doi.org/10.5067/MODIS/MCD64A1.061

High-resolution distribution maps of single-season rice in China from 2017 to 2022[DS/OL], V7 Ruoque Shen et al. https://doi.org/10.57760/sciencedb.06963

A 30-m resolution distribution map of maize for China based on Landsat and Sentinel images Ruoque Shen et al. https://doi.org/10.6084/m9.figshare.17091653.v4

30 m winter wheat distribution map of China for four years (2016-2019) Jie Dong et al. https://doi.org/10.6084/m9.figshare.12003990.v2

Short summary

The China Wildfire Emission Dataset (ChinaWED v1) estimated wildfire emissions in China during 2012–2022 as 78.13 Tg CO₂, 279.47 Gg CH₄, and 6.26 Gg N₂O annually. Agricultural fires dominated emissions, while forest and grassland emissions decreased. Seasonal peaks occurred in late spring, with hotspots in northeast, southwest, and east China. The model emphasizes the importance of using localized emission factors and high-resolution fire estimates for accurate assessments.