Remote Sensing-based Field-Level Open Biomass Burning NOx Emission Inventory of China

Accurate estimation of nitrogen oxide (NOx) emissions from biomass combustion is of great significance for ecological protection and climate change prediction in China. In this study, an emission factor (EF) weighting strategy considering the prior probability of the elaborate crop distribution within the fire pixels was proposed. under the assumption of Gaussian distribution of diurnal cycle of FRP (fire radiative power), we estimate the emission inventory of NOx from biomass combustion on field-level of China. To validate the assumptions of Gaussian distribution of diurnal cycle of FRP, we compared our results with the Himawari-8 satellite observations, the Pearson correlation coefficient reached 0.65. Meanwhile, in order to evaluate the emission inventory, we compared our estimation with global fire emission database (GFED), in-situ observations and ozone monitoring instrument (OMI) product, the result shows that our emission inventory with high spatiotemporal resolution agreed well with GFED database and in-situ observations in general. In conclusion, the method proposed in this study can compensate the shortage of previous studies on lacking elaborate landcovers, especially crop types while estimating the emissions, which is of great significance for countermeasure of controlling agricultural-source air pollution