Maritime greenhouse gas emission estimation and forecasting through AIS data analytics: a case study of Tianjin port in the context of sustainable development
文献类型：期刊论文
| 作者 | Xie, Wenxin4; Li, Yong4; Yang, Yang3; Wang, Peng2; Wang, Zhishan4; Li, Zhaoxuan4; Mei, Qiang1; Sun, Yaqi4 |
| 刊名 | FRONTIERS IN MARINE SCIENCE
 |
| 出版日期 | 2023-12-01 |
| 卷号 | 10页码:17 |
| 关键词 | greenhouse gas emission inventory AIS transformer emission prediction |
| DOI | 10.3389/fmars.2023.1308981 |
| 英文摘要 | The escalating greenhouse gas (GHG) emissions from maritime trade present a serious environmental and biological threat. With increasing emission reduction initiatives, such as the European Union's incorporation of the maritime sector into the emissions trading system, both challenges and opportunities emerge for maritime transport and associated industries. To address these concerns, this study presents a model specifically designed for estimating and projecting the spatiotemporal GHG emission inventory of ships, particularly when dealing with incomplete automatic identification system datasets. In the computational aspect of the model, various data processing techniques are employed to rectify inaccuracies arising from incomplete or erroneous AIS data, including big data cleaning, ship trajectory aggregation, multi-source spatiotemporal data fusion and missing data complementation. Utilizing a bottom-up ship dynamic approach, the model generates a high-resolution GHG emission inventory. This inventory contains key attributes such as the types of ships emitting GHGs, the locations of these emissions, the time periods during which emissions occur, and emissions. For predictive analytics, the model utilizes temporal fusion transformers equipped with the attention mechanism to accurately forecast the critical emission parameters, including emission locations, time frames, and quantities. Focusing on the sea area around Tianjin port-a region characterized by high shipping activity-this study achieves fine-grained emission source tracking via detailed emission inventory calculations. Moreover, the prediction model achieves a promising loss function of approximately 0.15 under the optimal parameter configuration, obtaining a better result than recurrent neural network (RNN) and long short-term memory network (LSTM) in the comparative experiments. The proposed method allows for a comprehensive understanding of emission patterns across diverse vessel types under various operational conditions. Coupled with the prediction results, the study offers valuable theoretical and data-driven support for formulating emission reduction strategies and optimizing resource allocation, thereby contributing to sustainable maritime transformation. |
| 资助项目 | National Natural Science Foundation of China[71804059] ; Natural Science Foundation of Fujian Province[2021J01821] ; Shanghai Science and Technology Committee[18DZ1206300] ; National Key Research and Development Program of China[2018YFC1407400] |
| WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology |
| 语种 | 英语 |
| WOS记录号 | WOS:001124539000001 |
| 出版者 | FRONTIERS MEDIA SA |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/38435]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Li, Yong; Mei, Qiang |
| 作者单位 | 1.Jimei Univ, Nav Inst, Xiamen, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 3.East China Normal Univ, Sch Geog Sci, Shanghai, Peoples R China 4.Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xie, Wenxin,Li, Yong,Yang, Yang,et al. Maritime greenhouse gas emission estimation and forecasting through AIS data analytics: a case study of Tianjin port in the context of sustainable development[J]. FRONTIERS IN MARINE SCIENCE,2023,10:17. |
| APA | Xie, Wenxin.,Li, Yong.,Yang, Yang.,Wang, Peng.,Wang, Zhishan.,...&Sun, Yaqi.(2023).Maritime greenhouse gas emission estimation and forecasting through AIS data analytics: a case study of Tianjin port in the context of sustainable development.FRONTIERS IN MARINE SCIENCE,10,17. |
| MLA | Xie, Wenxin,et al."Maritime greenhouse gas emission estimation and forecasting through AIS data analytics: a case study of Tianjin port in the context of sustainable development".FRONTIERS IN MARINE SCIENCE 10(2023):17. |
入库方式： OAI收割
来源：计算技术研究所
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