{"title":"基于多情景模型的内河港口船舶碳减排探索","authors":"Chunhui Zhou, Wuao Tang, Zongyang Liu, Hongxun Huang, Liang Huang, Changshi Xiao, Lichuan Wu","doi":"10.3390/jmse12091553","DOIUrl":null,"url":null,"abstract":"Assessing carbon emission reduction potential is vital for achieving carbon peak and neutrality in the maritime sector. In this study, we proposed a universal framework for assessing the effectiveness of different measures on carbon emission reduction from ships, including port and ship electrification (PSE), ship speed optimization (SSO), and clean fuel substitution (CFS). Firstly, the projection method of future ship traffic flows and activity levels relies on a neural network, and the ARIMA model was proposed. Then, the potential of various emission reduction measures was detailed and analyzed under different intensity scenarios. The proposed model was applied to Wuhan port, the results indicate that CFS is the most effective for long-term decarbonization, potentially achieving a carbon peak by 2025 under an aggressive scenario. For the short to medium term, PSE is favored due to technical maturity. SSO primarily delays emissions growth, making it a suitable auxiliary measure. These findings guide emission reduction strategies for ports, fostering green and sustainable shipping development.","PeriodicalId":16168,"journal":{"name":"Journal of Marine Science and Engineering","volume":"83 1","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring Carbon Emission Reduction in Inland Port Ship Based on a Multi-Scenario Model\",\"authors\":\"Chunhui Zhou, Wuao Tang, Zongyang Liu, Hongxun Huang, Liang Huang, Changshi Xiao, Lichuan Wu\",\"doi\":\"10.3390/jmse12091553\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Assessing carbon emission reduction potential is vital for achieving carbon peak and neutrality in the maritime sector. In this study, we proposed a universal framework for assessing the effectiveness of different measures on carbon emission reduction from ships, including port and ship electrification (PSE), ship speed optimization (SSO), and clean fuel substitution (CFS). Firstly, the projection method of future ship traffic flows and activity levels relies on a neural network, and the ARIMA model was proposed. Then, the potential of various emission reduction measures was detailed and analyzed under different intensity scenarios. The proposed model was applied to Wuhan port, the results indicate that CFS is the most effective for long-term decarbonization, potentially achieving a carbon peak by 2025 under an aggressive scenario. For the short to medium term, PSE is favored due to technical maturity. SSO primarily delays emissions growth, making it a suitable auxiliary measure. These findings guide emission reduction strategies for ports, fostering green and sustainable shipping development.\",\"PeriodicalId\":16168,\"journal\":{\"name\":\"Journal of Marine Science and Engineering\",\"volume\":\"83 1\",\"pages\":\"\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Marine Science and Engineering\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.3390/jmse12091553\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MARINE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Marine Science and Engineering","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.3390/jmse12091553","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MARINE","Score":null,"Total":0}
Exploring Carbon Emission Reduction in Inland Port Ship Based on a Multi-Scenario Model
Assessing carbon emission reduction potential is vital for achieving carbon peak and neutrality in the maritime sector. In this study, we proposed a universal framework for assessing the effectiveness of different measures on carbon emission reduction from ships, including port and ship electrification (PSE), ship speed optimization (SSO), and clean fuel substitution (CFS). Firstly, the projection method of future ship traffic flows and activity levels relies on a neural network, and the ARIMA model was proposed. Then, the potential of various emission reduction measures was detailed and analyzed under different intensity scenarios. The proposed model was applied to Wuhan port, the results indicate that CFS is the most effective for long-term decarbonization, potentially achieving a carbon peak by 2025 under an aggressive scenario. For the short to medium term, PSE is favored due to technical maturity. SSO primarily delays emissions growth, making it a suitable auxiliary measure. These findings guide emission reduction strategies for ports, fostering green and sustainable shipping development.
期刊介绍:
Journal of Marine Science and Engineering (JMSE; ISSN 2077-1312) is an international, peer-reviewed open access journal which provides an advanced forum for studies related to marine science and engineering. It publishes reviews, research papers and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. Electronic files and software regarding the full details of the calculation or experimental procedure, if unable to be published in a normal way, can be deposited as supplementary electronic material.