## 3 Results
### Performance of Different Spatial Resolutions  
The diffusion of a gas plume is primarily in the form of turbulence, and high spatial resolution is the key to accurately detecting their diffusion patterns. In addition, with a finer spatial resolution, the emitted gas concentration is more likely to fill the detection pixels.  
Figure 5: With the emission rate of 1000 kg/h, (**a–d**) retrieved \(\Delta\)XCH\({}_{4}\) images with different spectral resolutions (2 nm, 5 nm, 10 nm, 15 nm, respectively); (**e–h**) scatterplots comparing simulated and retrieved \(\Delta\)XCH\({}_{4}\) with different spectral resolutions (2 nm, 5 nm, 10 nm, 15 nm, respectively). The solid line is the linear regression of these scattered points. The dashed line is the line with a slope of 1.  
It could enhance the satellite's ability to capture anomalous enhancements, resulting in a more precise depiction of plume details. The radiance received by the satellite is generally a hybrid signal from different XCH4. It would result in attenuating fine-scale turbulent features, smearing high-concentration areas, and obscuring critical details of the plume's complex structure. Figure 6a depicts the continuous spectral information at a 5 nm spectral resolution of the pixel where the emission is located within different spatial resolutions. With more surrounding grids included in the detection pixel, the spectrum is increasingly affected by unrelated information. Notable variations in the spectrum are represented near the absorption peak of methane as spatial resolution degraded, which in turn affects the subsequent retrieval results.  
Figure 6b-f show the 1000 kg/h emission rate scene retrieval results with the background. It can be seen that the turbulent structure becomes gradually blurred as spatial resolution decreases, highlighting the impact of high resolution on capturing fine-scale details. Notably, the XCH4 where the emission is located decreased significantly due to the influence of mixed pixels in the coarsening spatial resolution process. This decline follows a nonlinear trend; as the spatial resolution degrades from 10 m to 30 m, the XCH4 at the detection pixel declines by 1481.44 ppb, and further decreases by 2357.00 ppb at 60 m. At the spatial resolution of 120 m, it is even difficult to determine the location of the emission pixel based on the XCH4 distribution. Then, it suggests that high spatial resolution is effective in identifying the location of point source emissions, as mentioned in previous studies where high spatial resolution is effective in distinguishing between point source emissions from multiple distinct locations at neighboring regions [39]. When the spatial resolution is degraded to 250 m and 500 m scale, the plume's complete morphology is no longer intact, with only a few high XCH4 pixels discernible. Nevertheless, the influence of resolution degradation on XCH4 diminishes slightly as emission rate levels increase. At an emission rate of 10,000 kg/h, the XCH4 of pixels remains higher than the background field even at a spatial resolution of 500 m (See Supplementary Materials Figure S1). Conversely, for a smaller emission rate (100 kg/h), coarser spatial resolution causes the \(\Delta\)XCH4 signal to blend with the background, making it challenging to separate from the irrelevant noise. Regardless of the emission levels, the continued spatial resolution degradation would lead to a gradual disappearance of the turbulent structure and a Gaussian-resembling distribution of the plume morphology.  
Figure 6: With the emission rate of 1000 kg/h, **(a)** simulated TOA radiance at different spatial resolutions; **(b–f)** scenes retrieval at spatial resolutions of 30 m, 60 m, 120 m, 250 m, 500 m. All simulations were conducted with a spectral resolution of 5 nm and SNR of 600.