Big data-driven carbon emission traceability list and characteristics of ships in maritime transportation-a case study of Tianjin Port
文献类型:期刊论文
作者 | Wang, Peng1,3; Hu, Qinyou3; Xie, Wenxin4; Wu, Lin1; Wang, Fei1; Mei, Qiang2,3 |
刊名 | ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
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出版日期 | 2023-05-09 |
页码 | 17 |
关键词 | Marine environment protection Ship pollutants Automatic identification system (AIS) Data mining |
ISSN号 | 0944-1344 |
DOI | 10.1007/s11356-023-27104-z |
英文摘要 | As Chi na's shipping industry continues to develop, ship emissions have become a significant source of pollutants. Consequently, it has become imperative to comprehend accurately the nature and attributes of ship pollutant emissions and understand their causation and effect as a crucial aspect of pollution control and legislation. This paper employs high-precision automatic identification system (AIS) dynamic and static data, along with pollutant emission parameters, to estimate the pollutant emissions from a ship's main engine, auxiliary engine, and boiler using a dynamic approach. Additionally, the study considers the sailing state and trajectory of the vessel and analyzes the characteristics of ship carbon emissions. Taking Tianjin Port as an example, this study conducts a multi-dimensional analysis of pollutant emissions to gain insight into the causation and effect of pollutants based on the collected big AIS data. The results show that the pollutant emissions in this region are mainly concentrated in the vicinity of Tianjin Port land port area, Dagusha Channel, and the Main Shipping Channel of Tianjin Xingang Fairway. Carbon emissions peak in September and are lower in June and December. Through accurate analysis of pollutant emission sources and emission characteristics in the region, this paper establishes the regular relationship between pollutant emissions and possible influencing factors and provides data support for China to formulate accurate pollutant emission reduction policies and regulate ship construction technology and carbon trading. |
资助项目 | National Key Research and Development Program of China[2018YFC1407400] ; NSFC[61902376] ; Major Projects of Shanghai Municipal Commission of Science and Technology[18DZ1206300] ; Natural Science Foundation of Fujian Province[2021J01821] ; Natural Science Foundation of Fujian Province[2020J05143] |
WOS研究方向 | Environmental Sciences & Ecology |
语种 | 英语 |
WOS记录号 | WOS:000985453800009 |
出版者 | SPRINGER HEIDELBERG |
源URL | [http://119.78.100.204/handle/2XEOYT63/21431] ![]() |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Mei, Qiang |
作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Jimei Univ, Xiamen 361021, Peoples R China 3.Shanghai Maritime Univ, Merchant Marine Acad, Shanghai 200210, Peoples R China 4.Beijing Univ Technol, Beijing 100124, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Peng,Hu, Qinyou,Xie, Wenxin,et al. Big data-driven carbon emission traceability list and characteristics of ships in maritime transportation-a case study of Tianjin Port[J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,2023:17. |
APA | Wang, Peng,Hu, Qinyou,Xie, Wenxin,Wu, Lin,Wang, Fei,&Mei, Qiang.(2023).Big data-driven carbon emission traceability list and characteristics of ships in maritime transportation-a case study of Tianjin Port.ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,17. |
MLA | Wang, Peng,et al."Big data-driven carbon emission traceability list and characteristics of ships in maritime transportation-a case study of Tianjin Port".ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2023):17. |
入库方式: OAI收割
来源:计算技术研究所
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