Satellite-based fast inversion for nitrogen oxides (NO _x =NO+NO₂) emissions at low computational costs and high resolutions (≤5 km or finer) can provide timely, detailed data to support targeted pollution control. To date, a variety of low-cost fast inversion methods have been developed, such as the Exponentially Modified Gaussian (EMG), Divergence (DIV), and the PHLET (Peking University High-resolution Lifetime-Emission-Transport) models. However, quantitative comparisons of these methods and their emission results are lacking. This study compares the above three inversion methods for the Beijing-Tianjin-Hebei region during the summer of 2019. We found that the EMG model, which was designed for point source emission inversion, performs poorly in Beijing-Tianjin-Hebei due to dense emission sources even within each city. The DIV considers the horizontal transport of NO _x with a predetermined (fixed) lifetime and can quickly identify the locations of emission sources; however, it tends to underestimate the emission amounts and even leads to negative emissions in many places. PHLET algorithm considers the horizontal transport of NO₂, the nonlinear relationship between local NO₂ concentrations and lifetimes, and the two-way matching between irregular satellite pixels and regular model grid cells, resulting in more reliable emission estimates. Filling in missing satellite data through data fusion, improving wind data resolution and accuracy, and improving NO _x chemical loss estimation will significantly enhance the quality of emission inversion.