Carbon dioxide is the leading anthropogenic greenhouse gas in terms of emissions from carbon-intensive industries, such as cement plants, steel mills and refineries. The deployment of CO2 (carbon) capture and sequestration (CCS) technologies plays an important role in reducing CO2 emissions on a global scale. When optimizing the CCS supply chains for the Italian peninsula, additional complexity is brought up by the Country seismic profile. This contribution provides a techno-economic assessment and optimization of a comprehensive CCS from Italian industrial stationary sources by aim of a multi-objective mixed-integer linear programming modeling framework. In particular, the model is conceived to simultaneously optimize the economic (i.e., minimum cost) and seismic (i.e., minimum risk) performance of a CCS system in the geographic setting of Italy. In this work, a case study aiming at a carbon reduction target of 50 % is presented by discussing the corresponding set of Pareto optimal solutions. Results show a trade-off between the two conflicting objectives, where the configuration with the minimum specific CO2 avoidance cost (68.8 €/t) is characterized by the highest value of risk (13.5 ruptures/year).

Optimizing Carbon Capture and Sequestration Chains from Industrial Sources Under Seismic Risk Constraints

Crîstiu Daniel;d'Amore Federico;Mocellin Paolo;Bezzo Fabrizio
2022

Abstract

Carbon dioxide is the leading anthropogenic greenhouse gas in terms of emissions from carbon-intensive industries, such as cement plants, steel mills and refineries. The deployment of CO2 (carbon) capture and sequestration (CCS) technologies plays an important role in reducing CO2 emissions on a global scale. When optimizing the CCS supply chains for the Italian peninsula, additional complexity is brought up by the Country seismic profile. This contribution provides a techno-economic assessment and optimization of a comprehensive CCS from Italian industrial stationary sources by aim of a multi-objective mixed-integer linear programming modeling framework. In particular, the model is conceived to simultaneously optimize the economic (i.e., minimum cost) and seismic (i.e., minimum risk) performance of a CCS system in the geographic setting of Italy. In this work, a case study aiming at a carbon reduction target of 50 % is presented by discussing the corresponding set of Pareto optimal solutions. Results show a trade-off between the two conflicting objectives, where the configuration with the minimum specific CO2 avoidance cost (68.8 €/t) is characterized by the highest value of risk (13.5 ruptures/year).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3464265
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