Estimation of emissions from biomass burning in China (2003–2017) based on MODIS fire radiative energy data

Biomass burning plays a significant role in air pollution and climate change. In this study, we used the method based on fire radiative energy (FRE) to develop a biomass burning emission inventory for China from 2003 to 2017. Daily fire radiative power (FRP) data in 1 km MODIS Thermal Anomalies/Fire products (MOD14/MYD14) were used to calculate FRE and combusted biomass. Available emission factors were assigned to four land-cover types: forest, cropland, grassland and shrubland. The farming system and crop types in different climate zones were taken into account in this research. Compared with traditional methods, the FRE method was found to provide a more reasonable estimates of emissions from small fires. The estimated average annual emission ranges, with a 90 % confidence interval, were 94.2 (78.7–117.6) Tg CO2 yr−1, 4.9 (2.5–8.3) Tg CO yr−1, 0.19 (0.05–0.51) Tg CH4 yr−1, 0.52 (0.18–0.81) Tg NMHC yr−1, 0.18 (0.04–0.39) Tg NOx yr−1, 0.07 (0.02–0.17) Tg NH3 yr−1, 0.03 (0.01–0.06) Tg SO2 yr−1, 0.04 (0.01–0.08) Tg BC yr−1, 0.3 (0.08–0.53) Tg OC yr−1, 0.49 (0.20–0.88) Tg PM2.5 yr−1, 0.56 (0.16–1.11) Tg PM10 yr−1. Forest fire was identified as the major source of the biomass burning emissions, and crop residue burning was the second highest contributor. In the 15-year study period, emissions from forest fires showed a significant downward trend. Crop residue emissions continued to rise until 2014, and then began to decline. Emissions from grassland and shrubland were little changed. Forest, grassland, and shrubland fires are mostly located in regions with high vegetation coverage, where the occurrence of fires is concentrated in arid seasons (spring and autumn). Plain areas with high crop yields, such as the North China Plain, experienced high agricultural fire emissions in harvest seasons. The resolution (daily, 1 km) of our inventory is much higher than previous inventories, such as GFED4s and GFASv1.0. It could be used in global and regional air quality modeling.