Emission Estimation and Spatiotemporal Distribution of Passenger Ships Using Multi-Source Data: A Case from Zhoushan (China)
Quantifying and estimating shipping emissions is a critical component of global emission reduction research and has become a growing area of interest in recent years. However, emissions from short-distance passenger ships operating on inter-island routes and their environmental impacts have received...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/1/168 |
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| author | Xubiao Xu Xingyu Liu Lin Feng Wei Yim Yap Hongxiang Feng |
| author_facet | Xubiao Xu Xingyu Liu Lin Feng Wei Yim Yap Hongxiang Feng |
| author_sort | Xubiao Xu |
| collection | DOAJ |
| description | Quantifying and estimating shipping emissions is a critical component of global emission reduction research and has become a growing area of interest in recent years. However, emissions from short-distance passenger ships operating on inter-island routes and their environmental impacts have received limited attention. This contribution investigated the temporal and spatial distribution characteristics of pollutants emitted by short-distance passenger ships at Zhoushan (China) using Automatic Identification System (AIS) data and the bottom–up emission model integrated with multi-source meteorological data. A year-long emission inventory was investigated. The results indicated that high-speed passenger ships contributed to the largest share of the emissions. The emissions were predominantly concentrated during daytime hours, with the routes between Zhoushan Island and Daishan, Daishan and Shengsi, and Zhoushan Island and Liuheng Island accounting for most of the emissions. Furthermore, intra-port waterways were identified as the primary emission areas for short-distance passenger ships. This study provides essential data support and references for the relevant authorities to understand the emission patterns of short-distance passenger ships, thereby facilitating the formulation of targeted emission reduction strategies for the maritime passenger transport sector. |
| format | Article |
| id | doaj-art-2cad7e989c3f450c85dc8a950ef57c1a |
| institution | Kabale University |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-2cad7e989c3f450c85dc8a950ef57c1a2025-01-24T13:37:06ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-01-0113116810.3390/jmse13010168Emission Estimation and Spatiotemporal Distribution of Passenger Ships Using Multi-Source Data: A Case from Zhoushan (China)Xubiao Xu0Xingyu Liu1Lin Feng2Wei Yim Yap3Hongxiang Feng4Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, ChinaFaculty of Governance and Global Affairs, Leiden University, 2311 EZ Leiden, The NetherlandsDepartment of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong TU428, ChinaSchool of Business, Singapore University of Social Sciences, Singapore 599494, SingaporeFaculty of Maritime and Transportation, Ningbo University, Ningbo 315832, ChinaQuantifying and estimating shipping emissions is a critical component of global emission reduction research and has become a growing area of interest in recent years. However, emissions from short-distance passenger ships operating on inter-island routes and their environmental impacts have received limited attention. This contribution investigated the temporal and spatial distribution characteristics of pollutants emitted by short-distance passenger ships at Zhoushan (China) using Automatic Identification System (AIS) data and the bottom–up emission model integrated with multi-source meteorological data. A year-long emission inventory was investigated. The results indicated that high-speed passenger ships contributed to the largest share of the emissions. The emissions were predominantly concentrated during daytime hours, with the routes between Zhoushan Island and Daishan, Daishan and Shengsi, and Zhoushan Island and Liuheng Island accounting for most of the emissions. Furthermore, intra-port waterways were identified as the primary emission areas for short-distance passenger ships. This study provides essential data support and references for the relevant authorities to understand the emission patterns of short-distance passenger ships, thereby facilitating the formulation of targeted emission reduction strategies for the maritime passenger transport sector.https://www.mdpi.com/2077-1312/13/1/168emission estimationspatiotemporal distributionautomatic identification system (AIS) datapassenger shipbottom–up emission model |
| spellingShingle | Xubiao Xu Xingyu Liu Lin Feng Wei Yim Yap Hongxiang Feng Emission Estimation and Spatiotemporal Distribution of Passenger Ships Using Multi-Source Data: A Case from Zhoushan (China) Journal of Marine Science and Engineering emission estimation spatiotemporal distribution automatic identification system (AIS) data passenger ship bottom–up emission model |
| title | Emission Estimation and Spatiotemporal Distribution of Passenger Ships Using Multi-Source Data: A Case from Zhoushan (China) |
| title_full | Emission Estimation and Spatiotemporal Distribution of Passenger Ships Using Multi-Source Data: A Case from Zhoushan (China) |
| title_fullStr | Emission Estimation and Spatiotemporal Distribution of Passenger Ships Using Multi-Source Data: A Case from Zhoushan (China) |
| title_full_unstemmed | Emission Estimation and Spatiotemporal Distribution of Passenger Ships Using Multi-Source Data: A Case from Zhoushan (China) |
| title_short | Emission Estimation and Spatiotemporal Distribution of Passenger Ships Using Multi-Source Data: A Case from Zhoushan (China) |
| title_sort | emission estimation and spatiotemporal distribution of passenger ships using multi source data a case from zhoushan china |
| topic | emission estimation spatiotemporal distribution automatic identification system (AIS) data passenger ship bottom–up emission model |
| url | https://www.mdpi.com/2077-1312/13/1/168 |
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