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Technical-Economic Analysis for Ammonia Ocean Transportation Using an Ammonia-Fueled Carrieropen access

Authors
Seo, YoungkyunAn, JiyoungPark, EunyoungKim, JintaeCho, MeangikHan, SeongjongLee, Jinkwang
Issue Date
Jan-2024
Publisher
MDPI
Keywords
ammonia; ammonia transportation; ammonia-fueled carrier; techno-economic; life-cycle cost
Citation
SUSTAINABILITY, v.16, no.2
Indexed
SCIE
SSCI
SCOPUS
Journal Title
SUSTAINABILITY
Volume
16
Number
2
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/69707
DOI
10.3390/su16020827
ISSN
2071-1050
2071-1050
Abstract
This study performed a technical-economic analysis for ship-based ammonia transportation to investigate the feasibility of international ammonia transportation. Ammonia is considered to be a vital hydrogen carrier, so the international trade in ammonia by ship will considerably increase in the future. This study proposed three scenarios for transporting ammonia from the USA, Saudi Arabia, and Australia to South Korea and employed an 84,000 m3 class ammonia carrier. Not only traditional very low sulfur fuel oil (VLSFO)/marine diesel oil (MDO) but also LNG and ammonia fuels were considered as propulsion and power generation fuels in the carrier. A life-cycle cost (LCC) model consisting of capital expenditure (CAPEX) and operational expenditure (OPEX) was employed for the cost estimation. The results showed that the transportation costs depend on the distance. The unit transportation cost from the USA to South Korea was approximately three times higher than that of Australia to South Korea. Ammonia fuel yielded the highest costs among the fuels investigated (VLSFO/MGO, LNG, and ammonia). When using ammonia fuel, the unit transportation cost was approximately twice that when using VLSFO/MDO. The fuel costs occupied the largest portion of the LCC. The unit transportation costs from Australia to South Korea were 23.6 USD/ton-NH3 for the LVSFO/MDO fuel case, 31.6 USD/ton-NH3 for the LNG fuel case, and 42.9 USD/ton-NH3 for the ammonia fuel case. This study also conducted a sensitivity analysis to investigate the influence of assumptions, including assumed parameters.
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