Bingcheng Liu1, Xuan Yang 1, Ting Wang1, Mengmeng Zhang1, Pen-Chi Chiang2


Qingdao University of Science and Technology, Qingdao 266061, China
Carbon Cycle Research Center, National Taiwan University, Taipei 10672, Taiwan


Received: October 21, 2019
Revised: November 4, 2019
Accepted: November 8, 2019
Download Citation: ||https://doi.org/10.4209/aaqr.2019.10.0519  

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Cite this article:
Liu, B., Yang, X., Wang, T., Zhang, M. and Chiang, P.C. (2019). CO2 Separation by Using a Three-stage Membrane Process. Aerosol Air Qual. Res. 19: 2917-2928. https://doi.org/10.4209/aaqr.2019.10.0519


Highlights

  • A new membrane process of CO2 capture from CO2-EOR extraction gas was displayed.
  • Matlab software used to simulate the new membrane process.
  • The important parameters of the system are obtained.

 

ABSTRACT


In this work, a three-stage membrane process for CO2 separation was proposed and optimized. The results of this study revealed that the proposed technology is a suitable process for the CO2 separation at higher concentrations. In addition, MATLAB was used to simulate and obtain the optimal operational parameters for a three-stage membrane process. A partial cycle was established, and the CO2 was recovered from the permeation side of the second-stage membrane, which enhanced the purity of the CO2 gas stream. The results of this study indicated that when the CO2 concentration was higher than 50% at a flow rate of 100000 Nm3 d–1, CO2 separation could be achieved under optimal operating conditions. Under conditions where the membrane areas were 2400, 3800, and 1800 m2 for the first-, second-, and third-stage membranes, respectively, and where the operational pressure at the first- and third stage membranes were 3.0 and 2.5 MPa, respectively, the CO2 separation fraction was higher than 90%, and the CH4 loss rate was less than 5%. The results of this study indicate a high potential for practical application.


Keywords: Optimal design; CO2-EOR extraction gas; CO2 capture; Multi-stage membrane separator.




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5-Year Impact Factor: 2.827


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