## 5 Conclusions  
In this paper, we used a new approach to improve the estimation of fire pollutant emissions by combining VIIRS and Himawari-8 FRP products and produced a more accurate fire emission inventory for the period of November 2019 to 15 January 2020 in southeast Australia. We have adopted the medium resolution satellite VIIRS with more superior performance and improved monitoring capacity for small fires. Compared with the results obtained by MODIS, we found that the results based on Himawari-8 are more accurate. We also found that there are significant spatial changes in the fire diurnal cycle. The peak time of fire usually occurs after 15:00, but as the fire moves southward, the peak time is delayed. For example, for the fire in northeastern Victoria in January 2020, the peak time is usually after 19:00. \(\sigma\) is mostly 1-3.5 h, and the fire duration varies from region to region. The fire diurnal cycle characteristics determined by using the Gaussian law with VIIRS and Himawari-8 datasets can constrain the observations of fire behavior more consistent with the actual burning process, which makes the calculation error of FRE smaller. The detailed comparison with the existing inventory shows that in terms of spatial distribution, our emission inventory is in good agreement with the existing inventory, the main burning cities distributed along the Great Dividing Range. In terms of time change of emission results, our emission inventory is 0.5-3.1 times that reported by the GFAS. The MODIS data used by the GFAS have been confirmed to have a large number of small fire omissions, which makes the GFAS underestimate the emission results to some extent. [PERSON] et al. discussed the shortcomings of the GFAS in more detail [58]. The total emissions shown in the emission inventory of this study are 1.5-4 times lower than those obtained using the burned-area-based approach (FINN). Studies have shown that the FINN often overestimates the burn rate of a fire or uses an outdated or inappropriate burn rate, which may be the source of the reason why the FINN result is higher [58]. This shows the need  
Figure 7: Total emissions of CO\({}_{2}\), CO, PM\({}_{2.5}\) and BC from the three main land-use burning types (temperate forest, agriculture and shrubland) in southeast Australia from November 2019 to January 2020 estimated based on VIIRS and Himawari-8 data. (**a**) Total emissions of CO2. (**b**) Total emissions of CO. (**c**) Total emissions of PM2.5. (**d**) Total emissions of BC. for great care in estimating the inventory based on the burned area, and the uncertainty of this method is relatively large. The satellite remote sensing method based on FRP can clearly express the intensity of fire, and combined with the remote sensing observation of a geostationary satellite, can observe the dynamic nature of fire more accurately, which is a recommended fire emission estimation method. [PERSON] and [PERSON] designed the experiment. [PERSON] provided data and supported the data analysis. [PERSON] and [PERSON] carried out experiments and verification. [PERSON] drafted the paper. [PERSON], [PERSON] and [PERSON] helped with editing and finalizing the paper. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Key Research and Development Program of China, grant number 2018 YFC0213600, and the Strategic Priority Research Program of the Chinese Academy of Sciences, grant number Gran XDA1900000. **Data Availability Statement**: Not applicable. **Acknowledgments:** VIIIRS and MODIS data were obtained from FIRMS. FIRMS is part of NASA's Land, Atmosphere Near Real-Time Capability for EOS. [[https://firms2.modaps.eosdis.nasa.gov/download/create.php](https://firms2.modaps.eosdis.nasa.gov/download/create.php)]([https://firms2.modaps.eosdis.nasa.gov/download/create.php](https://firms2.modaps.eosdis.nasa.gov/download/create.php)) (accessed on 5 November 2020; Himawari-8 data were obtained from the JAXA Himawari Monitor P-Tree System.