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 article
| 
28 Jan 2025
Data description article |
| 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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Cited
27 citations as recorded by crossref.
- Global shipping pollutant emissions from 1970 to 2022: spatiotemporal changes and exposures Q. Tang et al. https://doi.org/10.1016/j.jclepro.2026.148852
- Rethinking Ship Emission Hotspots: A 100 m Resolution AIS-Based Inventory for Coastal Chinese Waters S. Sun et al. https://doi.org/10.3390/jmse14100875
- Pathways and geographical patterns of international shipping CO2 emissions in the future W. Yi et al. https://doi.org/10.1016/j.scib.2026.03.004
- Impacts of shipping emissions on ozone pollution in China Z. Luo et al. https://doi.org/10.5194/acp-25-13635-2025
- Improving the global prediction of shipping emissions by modelling the effects of ambient conditions E. Majamäki et al. https://doi.org/10.1016/j.scitotenv.2025.180126
- Filterable and Condensable Particulate Nitrate Emissions from Plumes over North China Y. Ni et al. https://doi.org/10.1021/acs.est.6c02120
- The role of reduced aerosol masking from air pollutant emission reductions in recent global warming acceleration (2013–2023) X. Wang et al. https://doi.org/10.1073/pnas.2534130123
- Ship Air Emission and Their Air Quality Impacts in the Panama Canal Area: An Integrated AIS-Based Estimation During Hotelling Mode in Anchorage Zone Y. Lee et al. https://doi.org/10.3390/jmse13101888
- Atmospheric nitrogen deposition fluxes into coastal wetlands and their impacts on ecosystem carbon sequestration in East Asia J. Liu et al. https://doi.org/10.5194/bg-23-709-2026
- AIS-driven vessel activity and emissions modelling for offshore decommissioning activities in the North Sea K. Gormley et al. https://doi.org/10.3389/fmars.2026.1749962
- Quantifying operational variability across ship types and size classes in the North and Baltic Seas J. Hobbie et al. https://doi.org/10.1080/17445302.2026.2656938
- Carbon intensity assessment and fuel pathway optimization under the international maritime Organization's new regulations T. He et al. https://doi.org/10.1016/j.jclepro.2026.148465
- Building the I/SVOC Emission Inventory for Ocean-Going Ships: A Case Study on the Southeast Coast of China X. Chang et al. https://doi.org/10.3390/su17188310
- Load-Dependent Shipping Emission Factors Considering Alternative Fuels, Biofuels and Emission Control Technologies A. Grigoriadis et al. https://doi.org/10.3390/atmos17020122
- Deep learning driven spatiotemporal prediction of global carbon emissions from container shipping H. Yu et al. https://doi.org/10.1016/j.trd.2025.105169
- The ELK global emission inventory for the transport sectors M. Righi et al. https://doi.org/10.5194/essd-18-1619-2026
- Physics-informed multi-objective optimization for fuel consumption and air-pollutant exposure in ship operations J. Yun et al. https://doi.org/10.1016/j.oceaneng.2026.126293
- Onshore winds amplify shipping PM2.5 exposure in a coastal megaport city: Insights from source apportionment and machine learning L. Li et al. https://doi.org/10.1016/j.jhazmat.2026.141752
- A Clean Alternative or a New Environmental Challenge? A Perspective on Downstream Emissions and Environmental Trade-Offs of Ammonia-Diesel as a Low-Carbon Future Fuel H. Czech https://doi.org/10.1021/acs.est.5c04158
- Green hydrogen pathways for energy security: assessment for global renewable transformation Q. Alkhawlani et al. https://doi.org/10.1007/s42108-026-00519-3
- Deep learning-based reconstruction of high-resolution satellite-derived NO2 columns over the Bohai Sea Z. Li et al. https://doi.org/10.1016/j.atmosenv.2026.122243
- Divergence in International Shipping CO2 Emissions across Economies from an Export Perspective X. Wang et al. https://doi.org/10.1021/acs.est.5c07148
- Changes in the impacts of ship emissions on PM2.5 and its components in China under the staged fuel oil policies G. Yu et al. https://doi.org/10.5194/acp-25-9497-2025
- Development of a high-resolution maritime emissions inventory for the Gulf of Mexico (GoM-HEI) based on AIS data M. Cortez-Huerta et al. https://doi.org/10.1016/j.oceaneng.2026.127003
- Trade-linked maritime emissions and ammonia fuel transition in the UAE A. Mohammed et al. https://doi.org/10.1016/j.cstp.2026.101918
- The role of mega ports in climate change (IUPAC Technical Report) F. Sakellariadou et al. https://doi.org/10.1515/pac-2024-0246
- Drivers and environmental impacts of Arctic shipping W. Yi et al. https://doi.org/10.1038/s43017-026-00790-2
27 citations as recorded by crossref.
- Global shipping pollutant emissions from 1970 to 2022: spatiotemporal changes and exposures Q. Tang et al. https://doi.org/10.1016/j.jclepro.2026.148852
- Rethinking Ship Emission Hotspots: A 100 m Resolution AIS-Based Inventory for Coastal Chinese Waters S. Sun et al. https://doi.org/10.3390/jmse14100875
- Pathways and geographical patterns of international shipping CO2 emissions in the future W. Yi et al. https://doi.org/10.1016/j.scib.2026.03.004
- Impacts of shipping emissions on ozone pollution in China Z. Luo et al. https://doi.org/10.5194/acp-25-13635-2025
- Improving the global prediction of shipping emissions by modelling the effects of ambient conditions E. Majamäki et al. https://doi.org/10.1016/j.scitotenv.2025.180126
- Filterable and Condensable Particulate Nitrate Emissions from Plumes over North China Y. Ni et al. https://doi.org/10.1021/acs.est.6c02120
- The role of reduced aerosol masking from air pollutant emission reductions in recent global warming acceleration (2013–2023) X. Wang et al. https://doi.org/10.1073/pnas.2534130123
- Ship Air Emission and Their Air Quality Impacts in the Panama Canal Area: An Integrated AIS-Based Estimation During Hotelling Mode in Anchorage Zone Y. Lee et al. https://doi.org/10.3390/jmse13101888
- Atmospheric nitrogen deposition fluxes into coastal wetlands and their impacts on ecosystem carbon sequestration in East Asia J. Liu et al. https://doi.org/10.5194/bg-23-709-2026
- AIS-driven vessel activity and emissions modelling for offshore decommissioning activities in the North Sea K. Gormley et al. https://doi.org/10.3389/fmars.2026.1749962
- Quantifying operational variability across ship types and size classes in the North and Baltic Seas J. Hobbie et al. https://doi.org/10.1080/17445302.2026.2656938
- Carbon intensity assessment and fuel pathway optimization under the international maritime Organization's new regulations T. He et al. https://doi.org/10.1016/j.jclepro.2026.148465
- Building the I/SVOC Emission Inventory for Ocean-Going Ships: A Case Study on the Southeast Coast of China X. Chang et al. https://doi.org/10.3390/su17188310
- Load-Dependent Shipping Emission Factors Considering Alternative Fuels, Biofuels and Emission Control Technologies A. Grigoriadis et al. https://doi.org/10.3390/atmos17020122
- Deep learning driven spatiotemporal prediction of global carbon emissions from container shipping H. Yu et al. https://doi.org/10.1016/j.trd.2025.105169
- The ELK global emission inventory for the transport sectors M. Righi et al. https://doi.org/10.5194/essd-18-1619-2026
- Physics-informed multi-objective optimization for fuel consumption and air-pollutant exposure in ship operations J. Yun et al. https://doi.org/10.1016/j.oceaneng.2026.126293
- Onshore winds amplify shipping PM2.5 exposure in a coastal megaport city: Insights from source apportionment and machine learning L. Li et al. https://doi.org/10.1016/j.jhazmat.2026.141752
- A Clean Alternative or a New Environmental Challenge? A Perspective on Downstream Emissions and Environmental Trade-Offs of Ammonia-Diesel as a Low-Carbon Future Fuel H. Czech https://doi.org/10.1021/acs.est.5c04158
- Green hydrogen pathways for energy security: assessment for global renewable transformation Q. Alkhawlani et al. https://doi.org/10.1007/s42108-026-00519-3
- Deep learning-based reconstruction of high-resolution satellite-derived NO2 columns over the Bohai Sea Z. Li et al. https://doi.org/10.1016/j.atmosenv.2026.122243
- Divergence in International Shipping CO2 Emissions across Economies from an Export Perspective X. Wang et al. https://doi.org/10.1021/acs.est.5c07148
- Changes in the impacts of ship emissions on PM2.5 and its components in China under the staged fuel oil policies G. Yu et al. https://doi.org/10.5194/acp-25-9497-2025
- Development of a high-resolution maritime emissions inventory for the Gulf of Mexico (GoM-HEI) based on AIS data M. Cortez-Huerta et al. https://doi.org/10.1016/j.oceaneng.2026.127003
- Trade-linked maritime emissions and ammonia fuel transition in the UAE A. Mohammed et al. https://doi.org/10.1016/j.cstp.2026.101918
- The role of mega ports in climate change (IUPAC Technical Report) F. Sakellariadou et al. https://doi.org/10.1515/pac-2024-0246
- Drivers and environmental impacts of Arctic shipping W. Yi et al. https://doi.org/10.1038/s43017-026-00790-2
Saved (final revised paper)
Latest update: 05 Aug 2026
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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