## 2 Study Area and Data
### FINN and GFAS Emissions Inventory Data  
We used two state-of-the-art global fire emission databases (Fire Inventory from NCAR and Global Fire Assimilation System) to compare the results of this study. FINNv2.2 infers the combustion zone based on MODIS and VIIRS active fire detection data. Since the dataset does not have the combined data of MODIS and VIIRS in 2020, we only use FINNv2.2 based on MODIS data. The FINN assumes that each active fire detection has a pixel area of one square kilometer, and the burning area is further scaled according to the exposed coverage percentage of the VCF (MODIS vegetation continuous field) product at the fire point [49]. FINNv2.2 provides estimates of global fire emissions with a resolution of 1 km per day, including trace gases and aerosols. The emissions are calculated as follows:  
\[\rm E_{i}=A_{x,t}\times B_{X}\times FB\times EF_{i} \tag{1}\]  
where \(\rm E_{i}\) is the emission of species i, \(\rm A_{x,t}\) the area burned at location x and moment t, \(\rm B_{X}\) the biomass loading, FB the fraction of that biomass that is burned in the fire (burning ratio)  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **MODIS** & **VIIRS (Suomi NPP)** \\ \hline Orbit altitude & \(\sim\)705 km & \(\sim\)804 km \\ Equator crossing time & 1:30 AM, PM;10:30 AM, PM (local time) & 1:30 AM, PM (local time) \\ Scan angle range & \(\pm\)55\({}^{\circ}\) & \(\pm\)56.28\({}^{\circ}\) \\ Swath width & 2340 km & 3000 km \\  & & I-band:375 m(nadir)-800 m (along track), \\ Pixel dimensions & 1 km(nadir)–2.01 km (along track), & 375 m(nadir)–800 m (along scan) \\  & 1 km(nadir)–4.83 km (along scan) & M-band:750 m(nadir)–1.60 km(along track), \\  & & 750 m(nadir)–1.60 km (along scan) \\ Primary bands for fire detection and & B21 (3.929–3.989 μm) & 14 (3.550–3.930 μm) \\ FRP retrieval & B22 (3.940–4.001 μm) & M13 (3.987–4.145 μm) \\  & B31 (10.780–11.280 μm) & M15 (10.234–11.248 μm) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison between MODIS and VIIRS data in sensing geometry.  
and EF\({}_{\rm i}\) the emission factor. The biomass loading is assumed to be based on a specific land cover type, using the estimation method of [PERSON] et al. (2010), and a small number of updates are described by [PERSON] et al. (2017). According to the theory found by [PERSON] and [PERSON] (2019), the fraction of biomass burned (FB) is related to vegetation cover, which is further described by [PERSON] et al. (2017, 2018)., and the emission factor comes from the literature investigation by [PERSON] et al. (2018).  
In contrast to the FINN, the GFAS calculates biomass combustion emissions by assimilating fire radiative power observations from the MODIS instruments onboard the Terra and Aqua satellites (2018). The GFAS forms a fire database based on active fire (AF) detection and integrates into the Copernicus Atmosphere Monitoring Service (CAMS) system for near-real-time atmospheric composition monitoring and forecasting. Using the Kalman filtering algorithm developed by [PERSON] (2018), the FRP data observed by MODIS four times a day are integrated into daily FRE. Then, DMB can be calculated by multiplying FRE by a conversion factor. Finally, DMB is linearly transformed into emission fluxes of 40 smoke constituents (0.1\({}^{\circ}\) grid cell) using emission factors derived from field measurements ([PERSON] et al., 2017).