LAPSE:2025.0602
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LAPSE:2025.0602
Data-Driven Optimisation of Intermittent Methanol Production via Electrocatalytic Reduction of CO2 from Direct Air Capture
Anziel Malandri, Daria Kozyr, Haditya K. Purwanto, Maximilian Bloor, Noof Al Lawati
September 11, 2025
Abstract
To create useful products from carbon dioxide, electrochemical reduction is of the most promising approaches. Electrochemical reduction can use renewable energy to directly produce useful products such as formic acid, carbon monoxide, methanol or other C2 products. Specifically in Greece, methanol has been proven as a promising alternative for marine fuel, and it has been increasing in demand recently. As such, the proposed design is aimed to target this market. This paper will focus on the production of methanol using direct CO2 electro-reduction using Direct Air Capture (DAC) for the CO2 feed. A mathematical model of the electrolyser was created and implemented in Python. This model was then used alongside renewable energy production data from Open Power Systems [1] to optimise the total annualised cost with the constraint that the plant could only use renewable energy and must produce a minimum methanol flowrate. A combined stochastic search and derivative-free optimisation method were used to solve this problem. The results of the optimisation show that a minimum production flowrate of 11,400 kg/year could be successfully produced. However, this required significant CO2 storage of 900 m2 to consistently provide this flowrate. Since the proposed design utilises renewable sources and the methanol product possesses low toxicity and less environmental waste compared to the other alternative fuels, therefore this process is in compliance with the principles of Green Chemistry. A breakeven price of 8.6 $/kg was obtained for methanol from the economic evaluation which is higher than the competing fuels in the market. Once the price of renewable electricity reduces, this will make the CO2 electrocatalytic reduction to methanol a feasible pathway to solve the problem of renewable energy intermittency.
Keywords
data-driven optimisation, direct air capture, Electroreduction of CO2, mathematical modelling, process systems engineering
Suggested Citation
Malandri A, Kozyr D, Purwanto HK, Bloor M, Al Lawati N. Data-Driven Optimisation of Intermittent Methanol Production via Electrocatalytic Reduction of CO2 from Direct Air Capture. (2025). LAPSE:2025.0602
Author Affiliations
Malandri A: Department of Chemical Engineering, Imperial College London, UK
Kozyr D: Department of Chemical Engineering, Imperial College London, UK
Purwanto HK: Department of Chemical Engineering, Imperial College London, UK
Bloor M: Department of Chemical Engineering, Imperial College London, UK
Al Lawati N: Department of Chemical Engineering, Imperial College London, UK
Year
2023
Publication Date
2023-06-01
Issuing Institution
Imperial College London
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Runner-up for the EURECHA Process Design Contest 2023
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Sep 11, 2025
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CC BY-NC-ND 4.0
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Sep 11, 2025
 
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Thomas A. Adams II