Updated e-NRTL model for high-concentration MEA aqueous solution by regressing thermodynamic experimental data at high temperatures

Takao Nakagaki, Hirotaka Isogai, Hiroshi Sato, Jun Arakawa

    Research output: Contribution to journalArticle

    1 Citation (Scopus)

    Abstract

    Chemical absorption using amine solutions is a promising technology for post combustion CO2 Capture (PCC) from flue gas. Monoethanolamine (MEA) aqueous solution has been used in many projects as a benchmark solution and the experimental and analytical results are available in the literature for diverse operating conditions. Aspen Plus® is a widely used computational simulation software for design of PCC systems including operating conditions. Two example files of rate-based MEA models using electrolyte non-random two liquid (e-NRTL) methods are included in Aspen Plus. Basically, e-NRTL models can provide relatively accurate results by fitting parameters to experimental data within a limited temperature and concentration range. However, there are a non-negligible difference between experimental and calculation results, especially in regard to the vapor-liquid equilibrium (VLE) at high temperatures and high MEA concentrations. This paper updates the e-NRTL model for the solutions with 30 wt% and higher MEA by data regression of the specific heat capacity, the heat of CO2 absorption, and VLE experimental data obtained at high temperatures. Since these thermodynamic properties are mutually dependent and affected by internal model parameters such as activity coefficients, standard enthalpy change of formation of principal ions, all properties in the MEA-H2O-CO2 ternary system that are consistent with the MEA-H2O binary system were fitted by using a combination of the built-in data regression functionality and external spread-sheet software. The updated model more accurately simulates thermodynamic properties of high concentration MEA solutions at high temperatures.

    Original languageEnglish
    Pages (from-to)117-126
    Number of pages10
    JournalInternational Journal of Greenhouse Gas Control
    Volume82
    DOIs
    Publication statusPublished - 2019 Mar 1

    Keywords

    • Activity coefficient
    • Experimental data regression
    • Heat of reaction
    • Specific heat capacity
    • Vapor liquid equilibrium

    ASJC Scopus subject areas

    • Pollution
    • Energy(all)
    • Industrial and Manufacturing Engineering
    • Management, Monitoring, Policy and Law

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