IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v351y2023ics0306261923011510.html
   My bibliography  Save this article

Electrochemical condition optimization and techno-economic analysis on the direct CO2 electroreduction of flue gas

Author

Listed:
  • Tian, Di
  • Qu, Zhiguo
  • Zhang, Jianfei

Abstract

Direct CO2 electroreduction of flue gas is a technology that simplifies CO2 capture and purification process and directly utilizes CO2 in flue gas. Low CO2 reduction reaction selectivity caused by the low CO2 partial pressure and side reactions competition is the challenge. In this study, a direct CO2 electroreduction system for multicomponent flue gases was established. A two-dimensional steady model was developed by considering major electrode reactions of flue gas in CuxO-based catalysts. General influence criteria and optimum operation window for the potential, temperature, and pressure were proposed. In addition, a techno-economic analysis of the flue gas electrolysis system was conducted. The results demonstrated that the CO2 electroreduction reaction performances are weak at atmospheric pressure owing to the side reaction competition and small reactant concentration. A method involving pressurization and catholyte inlet temperature declination is proposed to break the stalemate of tiny reactant concentrations and ensure the dominance of the CO2 electroreduction reaction. The selectivity and current density of the CO2 reduction reaction were 71% and − 148 mA/cm2 at −1.17 V vs. reversible hydrogen electrode potential (RHE), respectively, under the conditions of an inlet electrolyte temperature of 273 K and an operating pressure of 20 atm. C1 products with excellent yields are the dominant products. Furthermore, the techno-economic analysis showed that the flue gas electrolysis system has higher profitability and lower cost than the purified CO2 electrolysis system. The present results can be used to optimize the electrolyzer operating parameters and construct CO2 reduction systems.

Suggested Citation

  • Tian, Di & Qu, Zhiguo & Zhang, Jianfei, 2023. "Electrochemical condition optimization and techno-economic analysis on the direct CO2 electroreduction of flue gas," Applied Energy, Elsevier, vol. 351(C).
  • Handle: RePEc:eee:appene:v:351:y:2023:i:c:s0306261923011510
    DOI: 10.1016/j.apenergy.2023.121787
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923011510
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2023.121787?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chanyeon Kim & Justin C. Bui & Xiaoyan Luo & Jason K. Cooper & Ahmet Kusoglu & Adam Z. Weber & Alexis T. Bell, 2021. "Tailored catalyst microenvironments for CO2 electroreduction to multicarbon products on copper using bilayer ionomer coatings," Nature Energy, Nature, vol. 6(11), pages 1026-1034, November.
    2. Wang, Huizhi & Leung, Dennis Y.C. & Xuan, Jin, 2013. "Modeling of a microfluidic electrochemical cell for CO2 utilization and fuel production," Applied Energy, Elsevier, vol. 102(C), pages 1057-1062.
    3. Li, Sheying & Cai, Yang-Hui & Schäfer, Andrea I. & Richards, Bryce S., 2019. "Renewable energy powered membrane technology: A review of the reliability of photovoltaic-powered membrane system components for brackish water desalination," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    4. Yue, Pengtao & Kang, Zhongyin & Fu, Qian & Li, Jun & Zhang, Liang & Zhu, Xun & Liao, Qiang, 2021. "Life cycle and economic analysis of chemicals production via electrolytic (bi)carbonate and gaseous CO2 conversion," Applied Energy, Elsevier, vol. 304(C).
    5. Karasu, Seçkin & Altan, Aytaç & Bekiros, Stelios & Ahmad, Wasim, 2020. "A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series," Energy, Elsevier, vol. 212(C).
    6. Karasu, Seçkin & Altan, Aytaç, 2022. "Crude oil time series prediction model based on LSTM network with chaotic Henry gas solubility optimization," Energy, Elsevier, vol. 242(C).
    7. Li, Kangkang & Leigh, Wardhaugh & Feron, Paul & Yu, Hai & Tade, Moses, 2016. "Systematic study of aqueous monoethanolamine (MEA)-based CO2 capture process: Techno-economic assessment of the MEA process and its improvements," Applied Energy, Elsevier, vol. 165(C), pages 648-659.
    8. Danielle A. Salvatore & Christine M. Gabardo & Angelica Reyes & Colin P. O’Brien & Steven Holdcroft & Peter Pintauro & Bamdad Bahar & Michael Hickner & Chulsung Bae & David Sinton & Edward H. Sargent , 2021. "Designing anion exchange membranes for CO2 electrolysers," Nature Energy, Nature, vol. 6(4), pages 339-348, April.
    9. Feiyan Xu & Kai Meng & Bei Cheng & Shengyao Wang & Jingsan Xu & Jiaguo Yu, 2020. "Unique S-scheme heterojunctions in self-assembled TiO2/CsPbBr3 hybrids for CO2 photoreduction," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mao, Yuanhao & Sultan, Sayd & Fan, Huifeng & Yu, Yunsong & Wu, Xiaomei & Zhang, Zaoxiao, 2024. "Stability improvement of the advanced electrochemical CO2 capture process with high-capacity polyamine solvents," Applied Energy, Elsevier, vol. 369(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xu, Yuxin & Gao, Fei, 2024. "A novel higher-order Deffuant–Weisbuch networks model incorporating the Susceptible Infected Recovered framework," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    2. Yu, Xihong & Bao, Han & Chen, Mo & Bao, Bocheng, 2023. "Energy balance via memristor synapse in Morris-Lecar two-neuron network with FPGA implementation," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    3. Chaerusani, Virdi & Ramli, Yusrin & Zahra, Aghietyas Choirun Az & Zhang, Pan & Rizkiana, Jenny & Kongparakul, Suwadee & Samart, Chanatip & Karnjanakom, Surachai & Kang, Dong-Jin & Abudula, Abuliti & G, 2024. "In-situ catalytic upgrading of bio-oils from rapid pyrolysis of torrefied giant miscanthus (Miscanthus x giganteus) over copper‑magnesium bimetal modified HZSM-5," Applied Energy, Elsevier, vol. 353(PA).
    4. Kanakadhurga, Dharmaraj & Prabaharan, Natarajan, 2022. "Peer-to-Peer trading with Demand Response using proposed smart bidding strategy," Applied Energy, Elsevier, vol. 327(C).
    5. Wei, Dongmei & Liu, Hailing & Li, Yongmei & Wan, Linchun & Qin, Sujuan & Wen, Qiaoyan & Gao, Fei, 2024. "Non-Markovian dynamics of time-fractional open quantum systems," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    6. Yu, Chuanjin & Li, Yongle & Chen, Qian & Lai, Xiaopan & Zhao, Liyang, 2022. "Matrix-based wavelet transformation embedded in recurrent neural networks for wind speed prediction," Applied Energy, Elsevier, vol. 324(C).
    7. Fu, Jianqin & Wang, Huailin & Sun, Xilei & Bao, Huanhuan & Wang, Xun & Liu, Jingping, 2024. "Multi-objective optimization for impeller structure parameters of fuel cell air compressor using linear-based boosting model and reference vector guided evolutionary algorithm," Applied Energy, Elsevier, vol. 363(C).
    8. Shabani, Masoume & Wallin, Fredrik & Dahlquist, Erik & Yan, Jinyue, 2022. "Techno-economic assessment of battery storage integrated into a grid-connected and solar-powered residential building under different battery ageing models," Applied Energy, Elsevier, vol. 318(C).
    9. Yao, Qijia & Alsaade, Fawaz W. & Al-zahrani, Mohammed S. & Jahanshahi, Hadi, 2023. "Fixed-time neural control for output-constrained synchronization of second-order chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    10. Li, Zhengmao & Wu, Lei & Xu, Yan & Wang, Luhao & Yang, Nan, 2023. "Distributed tri-layer risk-averse stochastic game approach for energy trading among multi-energy microgrids," Applied Energy, Elsevier, vol. 331(C).
    11. Patrón, Gabriel D. & Ricardez-Sandoval, Luis, 2022. "An integrated real-time optimization, control, and estimation scheme for post-combustion CO2 capture," Applied Energy, Elsevier, vol. 308(C).
    12. Qiu, Dawei & Wang, Yi & Zhang, Tingqi & Sun, Mingyang & Strbac, Goran, 2023. "Hierarchical multi-agent reinforcement learning for repair crews dispatch control towards multi-energy microgrid resilience," Applied Energy, Elsevier, vol. 336(C).
    13. Li, Fuxiang & Wu, Wei, 2022. "Coupled electrical-thermal performance estimation of photovoltaic devices: A transient multiphysics framework with robust parameter extraction and 3-D thermal analysis," Applied Energy, Elsevier, vol. 319(C).
    14. Shi, Changfeng & Zhi, Jiaqi & Yao, Xiao & Zhang, Hong & Yu, Yue & Zeng, Qingshun & Li, Luji & Zhang, Yuxi, 2023. "How can China achieve the 2030 carbon peak goal—a crossover analysis based on low-carbon economics and deep learning," Energy, Elsevier, vol. 269(C).
    15. Solomon Aforkoghene Aromada & Nils Henrik Eldrup & Fredrik Normann & Lars Erik Øi, 2020. "Techno-Economic Assessment of Different Heat Exchangers for CO 2 Capture," Energies, MDPI, vol. 13(23), pages 1-27, November.
    16. A.S., Remya Ajai & N.B., Harikrishnan & Nagaraj, Nithin, 2023. "Analysis of logistic map based neurons in neurochaos learning architectures for data classification," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    17. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    18. Isogai, Hirotaka & Nakagaki, Takao, 2024. "Power-to-heat amine-based post-combustion CO2 capture system with solvent storage utilizing fluctuating electricity prices," Applied Energy, Elsevier, vol. 368(C).
    19. Zhou, Yuzhou & Zhao, Jiexing & Zhai, Qiaozhu, 2021. "100% renewable energy: A multi-stage robust scheduling approach for cascade hydropower system with wind and photovoltaic power," Applied Energy, Elsevier, vol. 301(C).
    20. Yihua Zhang & Guyang Peng & Shuankui Li & Haijun Wu & Kaidong Chen & Jiandong Wang & Zhihao Zhao & Tu Lyu & Yuan Yu & Chaohua Zhang & Yang Zhang & Chuansheng Ma & Shengwu Guo & Xiangdong Ding & Jun Su, 2024. "Phase interface engineering enables state-of-the-art half-Heusler thermoelectrics," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:351:y:2023:i:c:s0306261923011510. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.