## 1 Introduction  
Biomass combustion is an important global source of atmospheric emissions [1, 2], which has a significant impact on air quality, climate change and human health [2, 3, 4, 5, 6]. Estimating the pollutants emitted into the atmosphere by biomass combustion is very important for studying its impact on air quality and climate change. Greenhouse gases produced by biomass combustion include carbon dioxide, carbon monoxide, methane, nitric oxide and atmospheric particulate matter, etc. [7]. Modeling studies indicate that these emissions can lead to severe regional air pollution events. [PERSON] et al. [8] suggest that PM\({}_{10}\) concentrations in some cities may reach 600 ug\(\cdot\)m\({}^{-3}\) during such events, which is six times higher than the WHO 24 h average PM\({}_{10}\) air quality guidelines for human health [9]. During the 2019-20 fire season in Australia, the daily concentration of PM2.5 in some densely populated areas exceeded 1000 ug\(\cdot\)m\({}^{-3}\)[6]. Although efforts to quantify emissions from biomass combustion have improved over the past few decades, inaccuracies in input data and differences in methods used can lead to at least 50 percent uncertainty in emission estimates [10; 11; 12; 13]. Early combustion estimates are based on fuel loads, combustion factors and fire return intervals, which vary with vegetation type [14]. While the spatio-temporal variations in fuel load and combustion factor are difficult to assess [10], the method based on remote sensing satellite observation has been paid more and more attention [15]. At present, there are two main methods to estimate biomass combustion emissions based on satellite observations in domestic and foreign studies: (1) method based on burned area [16; 17; 18; 19; 20; 21; 22]; (2) method based on fire radiative power [23; 24; 25; 26; 27; 28; 29; 30]. Estimation of biomass combustion emissions based on the burned-area method is the product of the burned area, the density of the above-ground biomass burned, the burning efficiency and the emission factor for each emitted species [16; 17; 18]. In general, uncertainty in emission assessments arises from all of the above factors. For example, [PERSON] and [PERSON] [19], using the SPOT satellite's global burned area (GBA) product, estimated that fires emitted 1428 Tg of carbon in 2000. For comparison, [PERSON] et al. [20], using the ATSR-satellite-generated global burned area product, estimated the carbon for the same year at 1741 Tg. This is surprising, as the estimated GBA by [PERSON] and [PERSON] [19] is almost twice as large as the GLOBSCAR used by [PERSON] et al. [20]. [PERSON] et al. [21] show that estimates of the area burned can vary widely between different acreage burning algorithms, resulting in a more than twofold variation in biomass consumed when the type of land cover being burned is added. This difference has serious influences for accurately quantifying fire emissions [22]. [PERSON] and [PERSON] [11] suggested that in addition to the burned area, the difference between fuel load estimation and burning factors is also the reason for the inconsistency in the emission estimations. The difficulty of accurately measuring these variables results in at least 50% uncertainty in emission estimates [10; 12; 15; 21]. Although the dataset for this application is constantly improving, due to the uncertainty of current estimates, it is worth exploring other methods [31; 32]. Compared with the traditional method based on burned area, another new promising method based on FRP observed from satellites may bring lower uncertainty to the estimation of combustion emissions. [PERSON] [23] found that these FRE (fire radiative energy) estimates scale directly to dry matter burned. It is possible to circumvent the uncertainty associated with the estimated burned area, fuel load and burned integrity. In addition, FRP observations can be observed and processed in near real-time [24; 25; 26]. For example, the GFAS is used to estimate global near-real-time daily fire emissions.