Accurate prediction of carbon monoxide in aqueous solutions for geological sequestration applications

• Published in: Applied geochemistry Vol. 187; p. 106414
• Main Authors: Sun, Li, Liang, Jierong
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2025
• Subjects: Aqueous solution; Carbon monoxide; Equation of state; Gas solubility; Carbon monoxide; Aqueous solution; Gas solubility; Equation of state
• ISSN: 0883-2927
• DOI: 10.1016/j.apgeochem.2025.106414

Accurate prediction of solubilities in aqueous solutions is crucial for the geological sequestration of carbon monoxide (CO). This study utilizes the electrolyte version of the Cubic-Plus-Association (CPA) Equation of State to calculate the saturated properties including saturated vapor pressure, saturated liquid-phase density, and saturated vapor-phase density of pure CO, its solubilities in pure water, and its solubilities in aqueous sodium chloride solutions. The model accuracy is validated against experimental data, showing relative average deviations within 3.0 % for saturated liquid-phase density, within 1.0 % for both saturated vapor pressure and saturated vapor-phase density, 4.7 % for CO solubilities in pure water, and 1.3 % for CO solubilities in aqueous sodium chloride solutions. This work not only analyzes the phase behavior of CO in aqueous solutions but also provides an in-depth discussion on the dissolution mechanisms of CO in these solutions. The results demonstrate that the electrolyte version of the CPA Equation of State is a robust model capable of accurately predicting CO solubilities and the complex phase behavior of CO in aqueous solutions across a wide range of temperatures, pressures, and salt concentrations. •Accurate prediction of carbon monoxide solubilities in pure water and aqueous sodium chloride solutions.•Exploration of dissolution mechanisms of carbon monoxide in aqueous solutions.•Comprehensive analysis of factors affecting carbon monoxide solubility.•Validation of model accuracy against experimental data, demonstrating high reliability and precision.