Publications

Song, R; Wang, TJ; Han, JC; Xu, BY; Ma, DY; Zhang, M; Li, S; Zhuang, BL; Li, MM; Xie, M (2022). Spatial and temporal variation of air pollutant emissions from forest fires in China. ATMOSPHERIC ENVIRONMENT, 281, 119156.

Abstract
Warm and dry climate conditions favor the occurrence of forest fires. Forest burning leads to the discharge of large amounts of particles and trace gases that play an important role in air quality degradation and have impact on human health. To date, most studies on China's forest fire emissions have concentrated in certain regions, also with a relatively coarse temporal resolution. In this study, we used the INteractive Fire and Emission algoRithm for Natural envirOnments (INFERNO), as well as high-resolution land cover data to compile a forest fire emission inventory for China in 2020. The variations of forest combustion emissions were then analyzed at the provincial and seasonal level. The results show that forest fires were concentrated in southern China and northeastern China, which are in agreement with MODIS observations. Total CO2, CO, CH4, NOx, SO2, PM2.5, OC, and BC emissions were estimated to be 3.06 x 10(4), 1.87 x 10(3), 96.92, 34.95, 13.84, 208, 116.03, and 9.95 Gg, respectively. Provinces with higher emissions were found in Yunnan, Guangdong, Hunan, and Sichuan. Peak emission from forest fire occurred in spring and winter, mainly from January to April, during which contributed 70% of the total forest fire contaminants emissions. The algorithm used in this study can be easily coupled in the meteorological model and air quality model to estimate the occurrence of fire and calculate pollutant emission online. This study updated emissions information that may support future research and policy development on greenhouse gas reduction and air pollution control.

DOI:
10.1016/j.atmosenv.2022.119156

ISSN:
1873-2844