Total atmospheric carbon detection by LIBS with multivariate physicochemical model based on transition and collision mechanism

Abstract

The importance of total atmospheric carbon (TAC) has been increasingly recognized in light of the growing significance of global climate change. The concept of TAC has expanded beyond its previous focus solely on CO₂ to encompass additional novel components. Here, a promising detection-analysis system for TAC quantitative detection is self-developed using LIBS and a multivariate physicochemical model based on transition and collision mechanism (MP-TC model). Spectral signals under different compositions were analyzed based on static detection. Then, a MP-TC model was developed by incorporating particle collisions and transition mechanisms. Subsequently, three dynamic monitoring were conducted analyzing the dynamic spectra obtained when CO₂, CO, and CH₄ were the different primary components of TAC. Interestingly, an anomalous CN transition was observed in Fuel combustion and the inhibited low vibrational transitions in symmetric molecules can be explored in CH₄ gradient concentration. Additionally, each dynamic process was fitted using the MP-TC model, confirming its reliability in TAC detection and its better alignment with the observed trends.