Demand forecasting for liquified natural gas bunkering by country and region using meta-analysis and artificial intelligence SCIE SSCI SCOPUS

DC Field Value Language
dc.contributor.author Chae, Gi Young -
dc.contributor.author An, Seung-Hyun -
dc.contributor.author Lee, Chul-Yong -
dc.date.accessioned 2022-01-19T10:36:49Z -
dc.date.available 2022-01-19T10:36:49Z -
dc.date.created 2021-08-30 -
dc.date.issued 2021-08 -
dc.identifier.issn 2071-1050 -
dc.identifier.uri https://sciwatch.kiost.ac.kr/handle/2020.kiost/42181 -
dc.description.abstract Ship exhaust emission is the main cause of coastal air pollution, leading to premature death from cardiovascular cancer and lung cancer. In light of public health and climate change concerns, the International Maritime Organization (IMO) and several governments are reinforcing policies to use clean ship fuels. In January 2020, the IMO reduced the acceptable sulfur content in ship fuel to 0.5% m/m (mass/mass) for sustainability. The use of liquified natural gas (LNG) as a ship fuel is currently the most likely measure to meet this regulation, and LNG bunkering infrastructure investment and network planning are underway worldwide. Therefore, the aim of this study is to predict the LNG bunkering demand for investment and planning. So far, however, there has been little quantitative analysis of LNG bunkering demand prediction. In this study, first, the global LNG bunkering demand was predicted using meta-regression analysis. Global demand for LNG bunkering is forecast to increase from 16.6 million tons in 2025 to 53.2 million tons in 2040. Second, LNG bunkering prediction by country and region was performed through analogy and artificial intelligence methods. The information and insights gained from this study may facilitate policy implementation and investments. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
dc.description.uri 1 -
dc.language English -
dc.publisher MDPI AG -
dc.subject BOTTOM-UP -
dc.subject TOP-DOWN -
dc.subject MARITIME TRANSPORT -
dc.subject LNG -
dc.subject EMISSIONS -
dc.subject MODELS -
dc.subject FUEL -
dc.title Demand forecasting for liquified natural gas bunkering by country and region using meta-analysis and artificial intelligence -
dc.type Article -
dc.citation.title SUSTAINABILITY -
dc.citation.volume 13 -
dc.citation.number 16 -
dc.contributor.alternativeName 채기영 -
dc.identifier.bibliographicCitation SUSTAINABILITY, v.13, no.16 -
dc.identifier.doi 10.3390/su13169058 -
dc.identifier.scopusid 2-s2.0-85112729121 -
dc.identifier.wosid 000690177900001 -
dc.type.docType Article -
dc.description.journalClass 1 -
dc.description.isOpenAccess N -
dc.subject.keywordPlus BOTTOM-UP -
dc.subject.keywordPlus TOP-DOWN -
dc.subject.keywordPlus MARITIME TRANSPORT -
dc.subject.keywordPlus LNG -
dc.subject.keywordPlus EMISSIONS -
dc.subject.keywordPlus MODELS -
dc.subject.keywordPlus FUEL -
dc.subject.keywordAuthor LNG bunkering -
dc.subject.keywordAuthor demand forecasting -
dc.subject.keywordAuthor shipping industry for sustainability -
dc.subject.keywordAuthor climate change -
dc.subject.keywordAuthor IMO regulation -
dc.relation.journalWebOfScienceCategory Green & Sustainable Science & Technology -
dc.relation.journalWebOfScienceCategory Environmental Sciences -
dc.relation.journalWebOfScienceCategory Environmental Studies -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass ssci -
dc.description.journalRegisteredClass scopus -
dc.relation.journalResearchArea Science & Technology - Other Topics -
dc.relation.journalResearchArea Environmental Sciences & Ecology -
Appears in Collections:
Ocean Law and Policy Institute > Ocean Policy Research Center > 1. Journal Articles
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