A graphical cost-screen technique for carbon management
Research involving carbon management has received increased attention over the last decades, due to the threat posed by global warming and increases in the atmospheric Green House Gas (GHG) emission.Improving energy efficiency, use of renewable energy and carbon dioxide(CO2) capture and storage are...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/40531/5/BusariBolajiIbrahimMFKK2013.pdf http://eprints.utm.my/id/eprint/40531/ |
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| Summary: | Research involving carbon management has received increased attention over the last decades, due to the threat posed by global warming and increases in the atmospheric Green House Gas (GHG) emission.Improving energy efficiency, use of renewable energy and carbon dioxide(CO2) capture and storage are among the proposed method for carbon management in the industrial sectors.Previous researchers have used carbon emission pinch analysis (CEPA) techniques to plans for carbon emission in the industry. But the cost effectiveness of the techniques has not been verified.This research is aimed at developing a graphical cost-screening technique for the CO2 emission reduction planning in an industrial site.This method employs the carbon management hierarchy (CMH) as a tool to guide CO2 emission reduction planning. It also extends the Systematic Hierarchical Approach for Resilient Process Screening (SHARPS) graphical cost-screening technique that was developed for water system to guide and screen design options involving process changes in order to obtain a cost effective system that meets a given CO2 emission targets.Application of the SHARPS screening techniques has successfully achievedthe final cost effective minimum CO2 emission target for a stationary site with TPPset (Total payback period set by designer) of 2 years, targeting 29.12 tons/hr of fresh CO2 and 16.74 tons/hr of CO2 emission prior to design. Using the predesign cost estimate method, the system needs approximately a net capital investment of USD 556.21 million,to give a net annual savings of USD 333.7 million with a total payback period of approximately 18 months. |
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