A Stochastic Techno-Economic Assessment of Emerging Artificial Photosynthetic Bio-Electrochemical Systems for CO2 Conversion

Artificial Photosynthetic Bio-Electrochemical Systems (AP-BES) offer a promising approach for converting CO2 to valuable bioproducts, addressing carbon mitigation and sustainable production. This study employs a stochastic techno-economic assessment (TEA) to estimate the viability of rhodopsin driven AP-BES, from carbon capture to product purification. Unlike traditional deterministic TEAs, this approach uses Monte Carlo simulations to model uncertainties in key technoeconomic parameters, including energy consumption, CO2 conversion efficiency, and bioproduct market prices. The analysis generates probability distributions for economic metrics such as Operational Expenditure (OPEX), Capital Expenditure (CAPEX), and profit. Enhancements in light-harvesting efficiency and advancements in reactor materials were predicted to reduce the payback period to just one year, thereby making large-scale deployment a feasible option.

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Publication Details

Journal
Systems and Control Transactions
Published
2025-06-30
DOI
https://doi.org/10.69997/sct.186579
Citations
1
Primary Topic
Microbial Fuel Cells and Bioremediation
Type
article
Field-Weighted Citation Impact
0.80

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article

A Stochastic Techno-Economic Assessment of Emerging Artificial Photosynthetic Bio-Electrochemical Systems for CO2 Conversion

Wei Huang, Aidong Yang, Haris Saeed
1 citations
Systems and Control Transactions
Microbial Fuel Cells and Bioremediation
0.80
article

A Stochastic Techno-Economic Assessment of Emerging Artificial Photosynthetic Bio-Electrochemical Systems for CO2 Conversion

Wei Huang, Aidong Yang, Haris Saeed
article en
1 citations

Abstract

Artificial Photosynthetic Bio-Electrochemical Systems (AP-BES) offer a promising approach for converting CO2 to valuable bioproducts, addressing carbon mitigation and sustainable production. This study employs a stochastic techno-economic assessment (TEA) to estimate the viability of rhodopsin driven AP-BES, from carbon capture to product purification. Unlike traditional deterministic TEAs, this approach uses Monte Carlo simulations to model uncertainties in key technoeconomic parameters, including energy consumption, CO2 conversion efficiency, and bioproduct market prices. The analysis generates probability distributions for economic metrics such as Operational Expenditure (OPEX), Capital Expenditure (CAPEX), and profit. Enhancements in light-harvesting efficiency and advancements in reactor materials were predicted to reduce the payback period to just one year, thereby making large-scale deployment a feasible option.

Systems and Control TransactionsVol. 4
University of Oxford (GB), Science Oxford (GB)
Biotechnology and Biological Sciences Research Council
Openalex Percentile: Top 28%
Microbial Fuel Cells and Bioremediation
0.80
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