Article(id=1263533687778492786, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263533678655881533, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-4653.2026.02.017, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1736784000000, receivedDateStr=2025-01-14, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1779179506486, onlineDateStr=2026-05-19, pubDate=1777046400000, pubDateStr=2026-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1779179506486, onlineIssueDateStr=2026-05-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1779179506486, creator=13701087609, updateTime=1779179506486, updator=13701087609, issue=Issue{id=1263533678655881533, tenantId=1146029695717560320, journalId=1240618002186551303, year='2026', volume='49', issue='2', pageStart='1', pageEnd='163', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1779179504312, creator=13701087609, updateTime=1779179563167, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1263533925629047616, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263533678655881533, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1263533925629047617, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263533678655881533, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=144, endPage=152, ext={EN=ArticleExt(id=1263533693373694366, articleId=1263533687778492786, tenantId=1146029695717560320, journalId=1240618002186551303, language=EN, title=Shipping greenhouse gas emission reduction model and fuel path analysis, columnId=1240655020656489358, journalTitle=Navigation of China, columnName=Green Shipping, runingTitle=null, highlight=null, articleAbstract=

To address global climate change and achieve the greenhouse gas reduction targets set by the International Maritime Organization (IMO), the global fleet faces complex challenges in balancing emission reduction effectiveness and economic feasibility during energy transition and fuel pathway selection, necessitating more systematic assessment and optimization of fleet-level emission reduction pathways. Existing research still lacks comprehensive comparative analysis of multi-fuel pathways, particularly systematic comparisons that balance carbon reduction effects and cost-effectiveness, making it difficult to support scientific decision-making for fleet decarbonization routes. To address these issues, a technology-economic assessment method for evaluating and optimizing shipping greenhouse gas reduction pathways is proposed. First, taking the global fleet as the research object, quantitative modeling and feature extraction of carbon reduction amounts and costs are conducted for each of the 18 preset fuel pathways. Second, a comprehensive evaluation index is established to account for both carbon reduction effects and economic feasibility, enabling coupled comparisons of multiple fuel pathways in terms of emission reduction potential and cost constraints. Combined with scenario analysis and pathway optimization mechanisms, a complete technical assessment framework is formed. The results indicate that pathways primarily based on methanol have the lowest carbon reduction costs, followed by ammonia pathways, while green methanol pathways outperform Liquefied Natural Gas （LNG)-based pathways. Green methanol and ammonia fuel pathways demonstrate the best carbon reduction performance. Considering medium-to long-term perspectives, green methanol and green ammonia can serve as optimal fuel choices, providing a feasible technical pathway for global fleet greenhouse gas reduction route planning and fuel transition decision-making.

, correspAuthors=Zhongqiu Zhao, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Jinfeng Hao, Zhongqiu Zhao, Zhaoxin Qiang, Chengshun Zhang, Zhonggang Li, Yugang Bai), CN=ArticleExt(id=1263533695185633713, articleId=1263533687778492786, tenantId=1146029695717560320, journalId=1240618002186551303, language=CN, title=航运温室气体减排分析模型及燃料路径分析, columnId=1240655020820067227, journalTitle=中国航海, columnName=绿色航运, runingTitle=null, highlight=null, articleAbstract=

为应对全球气候变化，实现国际海事组织（IMO）温室气体减排目标，全球船队在能源转型与燃料路径选择上面临减排效果与经济性平衡的复杂性挑战，对船队级减排路径的系统性评估与优选提出了更高要求。现有研究在面向多燃料路径的综合对比分析方面仍存在不足，尤其缺乏兼顾减碳效果与成本效益的系统性比较，难以有效支撑船队减碳路线的科学决策。针对上述问题，本文提出一种基于技术经济性分析的航运温室气体减排路径评估与优选方法。首先，以全球船队为研究对象，基于预设的18种燃料路径，对各路径下的碳减排量和减碳成本进行量化建模与特征提取；其次，构建兼顾减碳效果与经济性的综合评价指标，以应对多燃料路径之间在减排潜力与成本约束上的耦合比较；并结合情景分析与路径优选机制，形成完整的技术评估框架。结果表明，以甲醇为主的路径减碳成本最低，氨路径略次之，以绿甲醇为主的路径优于液化天然气为主的路径；绿甲醇和氨燃料路径减碳效果最优；基于中远期考虑，绿甲醇和绿氨可作为最优燃料选择，为全球船队温室气体减排路线规划与燃料转型决策提供了可行的技术途径。

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郝金凤（1978—），女，高级工程师，研究方向为船舶与海洋工程。

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郝金凤（1978—），女，高级工程师，研究方向为船舶与海洋工程。

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