## 4 Discussion  
As the range of simulated instrument parameters does not fully cover all satellites, interpolation was applied to the estimated matrix to address these gaps. The pseudo-observation radiance spectrum was generated using the current on-orbit satellite instrument parameters, which are listed in Table 1. The same was ensured in reflectivity and SZA across all simulations. The analysis focused on the currently leading hyperspectral imagers: PRISMA, EnMAP, EMIT, and GF5B-AHSI. These different hyperspectral imagers respond differently to the methane absorption spectrum, as shown in Figure 4b. Taking the plume of 1000 kg/h as an example, by comparing the interpolation results with the pseudo-observation retrieval results, the two types of data have a certain consistency. This suggests that the parameter matrix we established is representative of the selection of instrument parameters. However, the estimated results of the true satellite instrument parameters are still slightly different from the interpolation results. This discrepancy may be attributed to the spectral sampling in the SRF, which is one in our experiment, but varies across the selected hyperspectral imagers. In addition, this difference could also come from the error caused by the interpolation. Moreover, existing satellites underestimate the emission rate to a certain extent. It is possible that under the current algorithms, the limited spectral resolution hinders the ability to separate the methane absorption features from the mixed signals, and the estimation process by the plume model also introduces errors. A similar underestimation was found in EMIT in estimating the CO\({}_{2}\) plume emission rate [40]. We present a range of satellite instrument parameter options for methane plume monitoring, but do not incorporate instruments with finer spectral resolution (such as GHGSats, MethaneSat, etc.) Additionally, from the perspective of noise sources, only instrument noise is considered, and the impact of surface type is not included. All of these will be addressed in our future work. However, our conclusions still have some guidance for the current detection needs of methane plumes. Scientific instrument parameters are important prerequisites for achieving high-precision plume detection. Regarding instrument design, the spatial resolution can be improved by increasing the aperture of the optical system or optimizing the instrument's orbit. This is consistent with our experimental hypothesis that the instrument aperture can obtain sufficient radiance intensity regardless of the parameters. In addition, the optical system, detector parameters, and exposure time of the instrument collectively impact the SNR of the instrument. Since the estimation accuracy is more effectively improved by spectral resolution than SNR, the design of the instrument could focus on improving the spectral resolution. Optimizing the design of the optical system is crucial to the spectral resolution. Both dispersion spectroscopy and interference imaging spectrometers can achieve good spectroscopic effects. The dispersive spectroscopic systems can be further divided into prism and grating type. Prism spectrometers, used in missions such as PRISMA and EnMAP [12; 42], are widely adopted and straightforward techniques for spectral imaging. In such systems, the spectral resolution is inversely proportional to the width of the incident slit. It would reduce detection sensitivity and has a negative impact on the SNR in pursuit of high spectral resolution. The grating spectrom