Articles | Volume 17, issue 1
https://doi.org/10.5194/essd-17-277-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-277-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
28 Jan 2025
Data description paper |
| 28 Jan 2025
| 28 Jan 2025
The high-resolution global shipping emission inventory by the Shipping Emission Inventory Model (SEIM)
Wen Yi
State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China
Xiaotong Wang
Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
Tingkun He
State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China
State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China
Zhenyu Luo
State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China
Zhaofeng Lv
State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China
Kebin He
State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China
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Short summary
This study presents a detailed global dataset on ship emissions, covering the years 2013 and 2016–2021, using advanced modeling techniques. The dataset includes emissions data for four types of greenhouse gases and five types of air pollutants. The data, available for research, offer valuable insights into ship emission spatiotemporal patterns by vessel type and age, providing a solid data foundation for fine-scale scientific research and shipping emission mitigation.
This study presents a detailed global dataset on ship emissions, covering the years 2013 and...
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