Frequency-Comb-Based LiDAR Architecture for Greenhouse Gas Sensing

This work presents a numerical analysis of two LiDAR architectures for greenhouse gas sensing, with a focus on the detection of CO2 and CH4. The simulations were performed using the Lumerical Interconnect software. The first architecture evaluates a conventional IPDA LiDAR system, in which the laser wavelength is switched between spectral regions inside and outside the gas absorption bands. The second architecture proposes the use of an optical frequency comb, enabling the simultaneous investigation of different wavelengths associated with the spectral signatures of the gases. The results indicate that both topologies allow the effects of gas absorption on the received signal to be identified. Furthermore, in the frequency-comb-based architecture, cross-correlation analysis enabled the simultaneous differentiation between CH4 and CO2, demonstrating the poten tial of the proposed approach for multispectral LiDAR systems applied to environmental monitoring.