Abstract
Monitoring the solubility of carbon dioxide (CO(2)) in water under high-pressure and -temperature conditions is critical for industrial processes. Although the solubility behavior of CO(2) is well-established in the literature, most conventional methods rely on offline, invasive, or indirect measurements. In this study, a methodology was developed to monitor CO(2) solubility in water using near-infrared (NIR) spectroscopy due to its sensitivity to molecular interactions and ability to detect structural changes in the aqueous matrix in real time. The experimental system consisted of an apparatus similar to the static synthetic method coupled with an NIR spectrophotometer, enabling noninvasive spectral data acquisition during the dissolution of CO(2) in ultrapure water under varying temperature (40 to 60 °C) and pressure (0.15 to 2.35 MPa) conditions. Spectral data were preprocessed and correlated with CO(2) solubility using partial least-squares (PLS) regression. The PLS model was calibrated using solubility values obtained from a thermodynamic model based on the Peng-Robinson equation of state (PR-EoS) and the NRTL activity coefficient model, which was parametrized using experimental data from the literature. The developed model showed high predictive performance (R (2) > 0.99) with an average external prediction error of 9.91%. In comparison, the thermodynamic model yielded a mean absolute deviation of 0.073% in pressure predictions. The results demonstrate that NIR spectroscopy is sensitive to spectral variations associated with molecular interactions between CO(2) and water, enabling the construction of robust predictive models. This integrated approach provides a reliable and real-time method for indirectly estimating CO(2) solubility from spectral data. It thus represents an alternative tool for industrial and environmental monitoring of dissolved gases.