Spectroscopic Verification and Exclusion of Non-biological Causes of Sulfur-Based Biosignature Gases in Exoplanet Life Detection

Sulfur-based volatile compounds are regarded as a key candidate to break the deadlock of traditional oxygen-methane biological signal detection due to their unique metabolic specificity. However, their spectral signals face the challenge of high degeneracy caused by geological and photochemical origins. To address this core bottleneck, this paper proposes a systematic detection framework based on the "exclusion-verification" dual mechanism. Firstly, a flux threshold model for volcanic degassing and non-biological synthesis pathways was established, systematically defining the physical and chemical boundaries of non-biological causes, secondly, a high-resolution radiative transfer model was used to analyze the spectral fingerprints of key sulfur molecules, proposing an observation strategy for the mid-infrared window region to counteract the shading effect and a ground-based high-dispersion cross-correlation verification scheme, finally, a context-dependent Bayesian inference framework was constructed, achieving a logical loop from spectral feature identification to quantification of biological cause probability through marginal integration of non-biological model parameters. The research provides a robust theoretical criterion for the confirmation of exoplanetary life.