Screening of carbon dioxide utilization options using hybrid analytic hierarchy process-data envelopment analysis method

• Main Authors: Tapia, John Frederick D., Promentilla, Michael Angelo B., Tseng, Ming Lang, Tan, Raymond Girard R.
• Format: text
• Published: Animo Repository 2017
• Subjects: Multiple criteria decision making; Carbon sequestration; Data envelopment analysis; Monte Carlo method; Chemical Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1656; https://animorepository.dlsu.edu.ph/context/faculty_research/article/2655/type/native/viewcontent
• Institution: De La Salle University

Carbon dioxide capture, utilization, and storage is an emerging strategy that can contribute to the reduction of greenhouse gas emissions. It enables the use of captured carbon dioxide from industrial sources as feedstock for profitable use or sequestration. This strategy simultaneously allows the use of fossil fuel power plants and the reduction of carbon emissions through storage. Options for carbon dioxide utilization include enhanced oil recovery, enhanced coal bed methane and enhanced shale gas recovery, all of which involve its use as an injection fluid for additional product recovery. A significant portion of the injected carbon dioxide is sequestered. Identification and screening of utilization options for project development is important to develop a cost-effective system. In this study, a hybrid Analytic Hierarchy Process-Data Envelopment Analysis framework is developed to select efficient carbon dioxide utilization options. The selection is based on combining available quantitative data and expert judgments on qualitative criteria to come up with efficiency scores as basis for selection. Two case studies based on realistic data are presented to illustrate the framework. Analysis using Monte Carlo simulation is used to determine the effect of uncertainties on the selected options. The case studies demonstrate the applicability of the methodology to practical problems in the planning of low-carbon systems. © 2017 Elsevier Ltd