Optimization‐based identification of CO 2 capture and utilization processing paths for life cycle greenhouse gas reduction and economic benefits
This paper introduces a mathematical formulation to identify promising CO 2 capture and utilization (CCU) processing paths and assess their production rates by solving an optimization problem. The problem is cast as a multi‐objective one by simultaneously maximizing a net profit and life cycle green...
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Veröffentlicht in: | AIChE journal 2019-07, Vol.65 (7) |
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creator | Roh, Kosan Al‐Hunaidy, Ali S. Imran, Hasan Lee, Jay H. |
description | This paper introduces a mathematical formulation to identify promising CO
2
capture and utilization (CCU) processing paths and assess their production rates by solving an optimization problem. The problem is cast as a multi‐objective one by simultaneously maximizing a net profit and life cycle greenhouse gas (GHG) reduction. Three case studies are illustrated using an exemplary CCU processing network. The results indicate the optimal solution is greatly influenced by the scale of CO
2
emission source, market demand, and hydrogen availability. Moreover, with the current system of measuring the GHG reduction regarding a business‐as‐usual level, if the aim is to achieve a GHG reduction within a national boundary, the question of whether CCU plants producing a product of same functionality through conventional means, which the CO
2
‐based product can replace, exists in the country can come into consideration. This systematic identification will assist decision‐making regarding future R&D investment and construction of large‐scale CCU plants. |
doi_str_mv | 10.1002/aic.16580 |
format | Article |
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2
capture and utilization (CCU) processing paths and assess their production rates by solving an optimization problem. The problem is cast as a multi‐objective one by simultaneously maximizing a net profit and life cycle greenhouse gas (GHG) reduction. Three case studies are illustrated using an exemplary CCU processing network. The results indicate the optimal solution is greatly influenced by the scale of CO
2
emission source, market demand, and hydrogen availability. Moreover, with the current system of measuring the GHG reduction regarding a business‐as‐usual level, if the aim is to achieve a GHG reduction within a national boundary, the question of whether CCU plants producing a product of same functionality through conventional means, which the CO
2
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2
capture and utilization (CCU) processing paths and assess their production rates by solving an optimization problem. The problem is cast as a multi‐objective one by simultaneously maximizing a net profit and life cycle greenhouse gas (GHG) reduction. Three case studies are illustrated using an exemplary CCU processing network. The results indicate the optimal solution is greatly influenced by the scale of CO
2
emission source, market demand, and hydrogen availability. Moreover, with the current system of measuring the GHG reduction regarding a business‐as‐usual level, if the aim is to achieve a GHG reduction within a national boundary, the question of whether CCU plants producing a product of same functionality through conventional means, which the CO
2
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2
capture and utilization (CCU) processing paths and assess their production rates by solving an optimization problem. The problem is cast as a multi‐objective one by simultaneously maximizing a net profit and life cycle greenhouse gas (GHG) reduction. Three case studies are illustrated using an exemplary CCU processing network. The results indicate the optimal solution is greatly influenced by the scale of CO
2
emission source, market demand, and hydrogen availability. Moreover, with the current system of measuring the GHG reduction regarding a business‐as‐usual level, if the aim is to achieve a GHG reduction within a national boundary, the question of whether CCU plants producing a product of same functionality through conventional means, which the CO
2
‐based product can replace, exists in the country can come into consideration. This systematic identification will assist decision‐making regarding future R&D investment and construction of large‐scale CCU plants.</abstract><doi>10.1002/aic.16580</doi><orcidid>https://orcid.org/0000-0002-4918-4782</orcidid></addata></record> |
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title | Optimization‐based identification of CO 2 capture and utilization processing paths for life cycle greenhouse gas reduction and economic benefits |
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