Simulation analysis of the effects of aerosol and surface albedo on the remote sensing detection of greenhouse gases in the short-wave infrared 1.6 μm

Aerosols and surface albedo are major sources of error in retrieving greenhouse gas concentrations using high-resolution shortwave infrared spectroscopy. This study employs a high-precision atmospheric radiative transfer model to simulate the influence of aerosols and six different surface types on satellite-observed spectra in the 1594 nm~1624 nm and 1662 nm~1672 nm bands. The results indicate that as aerosol optical depth (AOD) increases, radiance generally increases, with the most significant change observed over vegetated surfaces, which show a 13.26% variation. Within the CO2 and CH4 absorption bands, the increments of CO2/CH4 under equivalent radiation corresponding to the six surface types are ranked: vegetation, metal material, building material, sedimentary finerock, soil, and sedimentary coarserock. Taking soil surface as an example, the study finds that radiance decreases by approximately 0.41 W/m2/μm/sr for every 1 ppm increase in CO2 concentration and by about 0.86 W/m2/μm/sr for every 1 ppb increase in CH4 concentration. Further analysis shows a near-parabolic relationship between AOD and radiance, with consistent trends for CO2 and CH4. As AOD increases, the concentration of both gases exhibit continuous growth. Vegetated surfaces demonstrate the largest concentration changes, with CO2 and CH4 varying by approximately 40.96 ppm and 137.87 ppb, respectively. Explorations under mixed surface conditions indicate that spectral radiance increases with surface albedo, reaching maximum values of 7.7 W/m2/μm/sr for CO2 and 7.45 W/m2/μm/sr for CH4. These findings underscore the critical roles of aerosols and surface albedo in satellite-based greenhouse gas retrievals, offering valuable theoretical guidance for enhancing the accuracy of remote sensing measurements.