Modeling of Vacuum Temperature Swing Adsorption for Direct Air Capture Using Aspen Adsorption
Thomas Deschamps,
Mohamed Kanniche,
Laurent Grandjean and
Olivier Authier
Additional contact information
Thomas Deschamps: EDF R&D Lab Chatou, 78400 Chatou, France
Mohamed Kanniche: EDF R&D Lab Chatou, 78400 Chatou, France
Laurent Grandjean: EDF R&D Lab Chatou, 78400 Chatou, France
Olivier Authier: EDF R&D Lab Chatou, 78400 Chatou, France
Clean Technol., 2022, vol. 4, issue 2, 1-18
Abstract:
The paper evaluates the performance of an adsorption-based technology for CO 2 capture directly from the air at the industrial scale. The approach is based on detailed mass and energy balance dynamic modeling of the vacuum temperature swing adsorption (VTSA) process in Aspen Adsorption software. The first step of the approach aims to validate the modeling thanks to published experimental data for a lab-scale bed module in terms of mass transfer and energy performance on a packed bed using amine-functionalized material. A parametric study on the main operating conditions, i.e., air velocity, air relative moisture, air temperature, and CO 2 capture rate, is undertaken to assess the global performance and energy consumption. A method of up-scaling the lab-scale bed module to industrial module is exposed and mass transfer and energy performances of the industrial module are provided. The scale up from lab scale to the industrial size is conservative in terms of thermal energy consumption while the electrical consumption is very sensitive to the bed design. Further study related to the engineering solutions available to reach high global gas velocity are required. This could be offered by monolith-shape adsorbents.
Keywords: adsorption; CO 2 capture; modeling (search for similar items in EconPapers)
JEL-codes: Q2 Q3 Q4 Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jcltec:v:4:y:2022:i:2:p:15-275:d:789405
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