Abstract: This work explored the emission structure, spatial distribution, and uncertainty of the primary PM_2.5 emission inventory of 1 km × 1 km anthropogenic sources in Linfen City in 2020 by field research, data acquisition from the municipal departments, and obtaining of activity level data from the statistical yearbook. The reliability and comprehensiveness of the emission inventory were elaborated by comparison and analysis of the results with satellite remote sensing data, China Multiscale Emission Inventory Model (MEIC), and China High-Resolution Carbon and Air Pollutant Emission Database (CHRED 3.0A). The findings reveal that the total primary emissions of anthropogenic sources of PM_2.5 in Linfen City are about 26375.7 t, of which road dust sources and iron and steel sources have the largest proportion, 33.5% and 16.1%, respectively. The emission composition of the districts and counties is significantly differentiated, among which approximately 90% come from Houma City process sources, approximately 70% from Jixian County fossil fuel stationary combustion sources, approximately 15% from Pu County biomass combustion sources, approximately 93% from Daining County dust sources, and approximately 13% from Yicheng County mobile sources. The iron, steel, and coking industries in Linfen City emit a total of 6916.9 t of PM_2.5, with the largest shares for Quwo County (69.1%) and Xiangfen County (20.81%), where the main sources of pollution in the iron and steel industry come from the sintering and converter processes and those in the coking industry mainly come from the stacks of the coke ovens. The PM_2.5 emissions in Linfen City are concentrated in seven districts and counties in the Linfen Basin, and the emission intensity is much higher than the districts and counties with mountainous terrain on both sides, and that in the western districts and counties is lower than that in the eastern districts and counties of Linfen, among which the top 3 by PM_2.5 emissions are Quwo County, Houma City, and Xiangfen County; the uncertainty results of different emission sources are between −27.1% and 34.5%. For the total amount of emissions, the PM_2.5 emissions in this paper do not differ much from them (MEIC: 30905t; CHRED 3.0A: 19604.3 t; this study: 23498 t); for the spatial distribution, there is a high degree of consistency with the concentration of the remotely sensed inversions, and the high values are concentrated in the Linfen Basin. The iron, steel, and coking industries should further boost the management and monitoring of organized/unorganized emissions and control pollutant emissions from the source and the end.