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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Cited articles
Browse, J., Carslaw, K. S., Schmidt, A., and Corbett, J. J.: Impact of future Arctic shipping on high-latitude black carbon deposition, Geophys. Res. Lett., 40, 4459–4463, https://doi.org/10.1002/grl.50876, 2013.
Chen, D., Wang, X., Li, Y., Lang, J., Zhou, Y., Guo, X., and Zhao, Y.: High-spatiotemporal-resolution ship emission inventory of China based on AIS data in 2014, Sci. Total Environ., 609, 776–787, https://doi.org/10.1016/j.scitotenv.2017.07.051, 2017.
Chen, D., Fu, X., Guo, X., Lang, J., Zhou, Y., Li, Y., Liu, B., and Wang, W.: The impact of ship emissions on nitrogen and sulfur deposition in China, Sci. Total Environ., 708, 134636, https://doi.org/10.1016/j.scitotenv.2019.134636, 2020.
Chen, X. and Yang, J.: Analysis of the uncertainty of the AIS-based bottom-up approach for estimating ship emissions, Mar. Pollut. Bull., 199, 115968, https://doi.org/10.1016/j.marpolbul.2023.115968, 2024.
Corbett, J. J., Fischbeck, P. S., and Pandis, S. N.: Global nitrogen and sulfur inventories for oceangoing ships, J. Geophys. Res.-Atmos., 104, 3457–3470, https://doi.org/10.1029/1998jd100040, 1999.
Crippa, M., Guizzardi, D., Solazzo, E., Muntean, M., Schaaf, E., and Monforti-Ferrario, F.: GHG emissions of all world countries – 2021 Report, Luxembourg, https://doi.org/10.2760/173513, 2021.
Diamond, M. S.: Detection of large-scale cloud microphysical changes within a major shipping corridor after implementation of the International Maritime Organization 2020 fuel sulfur regulations, Atmos. Chem. Phys., 23, 8259–8269, https://doi.org/10.5194/acp-23-8259-2023, 2023.
DNV: Maritime Forcast to 2050, Germany, https://www.dnv.com/maritime/publications/maritime-forecast/ (last access: 16 January 2025), 2022.
Emmens, T., Amrit, C., Abdi, A., and Ghosh, M.: The promises and perils of Automatic Identification System data, Expert Syst. Appl., 178, 114975, https://doi.org/10.1016/j.eswa.2021.114975, 2021.
Endresen, O., Sorgard, E., Sundet, J. K., Dalsoren, S. B., Isaksen, I. S. A., Berglen, T. F., and Gravir, G.: Emission from international sea transportation and environmental impact, J. Geophys. Res.-Atmo., 108, 4560, https://doi.org/10.1029/2002jd002898, 2003.
Eyring, V., Isaksen, I. S. A., Berntsen, T., Collins, W. J., Corbett, J. J., Endresen, O., Grainger, R. G., Moldanova, J., Schlager, H., and Stevenson, D. S.: Transport impacts on atmosphere and climate: Shipping, Atmos. Environ., 44, 4735–4771, https://doi.org/10.1016/j.atmosenv.2009.04.059, 2010.
Fu, M., Liu, H., Jin, X., and He, K.: National- to port-level inventories of shipping emissions in China, Environ. Res. Lett., 12, 11, https://doi.org/10.1088/1748-9326/aa897a, 2017.
Fu, X., Chen, D., Guo, X., Lang, J., and Zhou, Y.: Improving the estimation of ship emissions using the high-spatiotemporal resolution wind fields simulated by the Weather Research and Forecast model: A case study in China, J. Ind. Ecol., 26, 1871–1881, https://doi.org/10.1111/jiec.13278, 2022.
Gronholm, T., Makela, T., Hatakka, J., Jalkanen, J. P., Kuula, J., Laurila, T., Laakso, L., and Kukkonen, J.: Evaluation of Methane Emissions Originating from LNG Ships Based on the Measurements at a Remote Marine Station, Environ. Sci. Technol., 55, 13677–13686, https://doi.org/10.1021/acs.est.1c03293, 2021.
Hoesly Rachel, S. S.: CEDS v_2024_04_01 Release Emission Data (v_2024_04_01), Zenodo [data set], https://doi.org/10.5281/zenodo.10904361, 2024.
IMO: Emission Control Areas (ECAs) designated under MARPOL Annex VI., UK, 2023.
IMO: Amendents to the techincal code on control of emission of nitrogen oxides from marine diesel engines, UK, 2008.
IMO: Further technical and operational measures for enhancing the energy efficiency of international shipping, UK, 2015.
Jalkanen, J.-P., Johansson, L., Kukkonen, J., Brink, A., Kalli, J., and Stipa, T.: Extension of an assessment model of ship traffic exhaust emissions for particulate matter and carbon monoxide, Atmos. Chem. Phys., 12, 2641–2659, https://doi.org/10.5194/acp-12-2641-2012, 2012.
Jasper, F., Shinichi, H., Shuang, Z., Paula, P., and Bryan, C.: Forth IMO Greenhouse gas study, London, UK, https://www.imo.org/en/OurWork/Environment/Pages/Fourth-IMO-Greenhouse-Gas-Study-2020.aspx (last access: 16 January 2025), 2020.
Johansson, L., Jalkanen, J.-P., and Kukkonen, J.: Global assessment of shipping emissions in 2015 on a high spatial and temporal resolution, Atmos. Environ., 167, 403–415, https://doi.org/10.1016/j.atmosenv.2017.08.042, 2017.
Kersey, J., Popovich, N. D., and Phadke, A. A.: Rapid battery cost declines accelerate the prospects of all-electric interregional container shipping, Nature Energy, 7, 664–674, https://doi.org/10.1038/s41560-022-01065-y, 2022.
Kramel, D., Muri, H., Kim, Y., Lonka, R., Nielsen, J. B., Ringvold, A. L., Bouman, E. A., Steen, S., and Strømman, A. H.: Global Shipping Emissions from a Well-to-Wake Perspective: The MariTEAM Model, Environ. Sci. Technol., 55, 15040–15050, https://doi.org/10.1021/acs.est.1c03937, 2021.
Liu, H., Fu, M., Jin, X., Shang, Y., Shindell, D., Faluvegi, G., Shindell, C., and He, K.: Health and climate impacts of ocean-going vessels in East Asia, Nat. Clim. Change, 6, 1037–1041, https://doi.org/10.1038/nclimate3083, 2016.
Liu, H., Yi, W., Jalkanen, J.-P., Luo, Z., Majamäki, E., Matthias, V., Moldanová, J., Shi, Z., and He, K.: Atmospheric impacts and regulation framework of shipping emissions: achievements, challenges and frontiers, Fundamental Research, https://doi.org/10.1016/j.fmre.2024.02.013, online first, 2024.
Luo, Z., He, T., Yi, W., Zhao, J., Zhang, Z., Wang, Y., Liu, H., and He, K.: Advancing shipping NOx pollution estimation through a satellite-based approach, PNAS Nexus, 3, pgad430, https://doi.org/10.1093/pnasnexus/pgad430, 2023.
Luo, Z., Lv, Z., Zhao, J., Sun, H., He, T., Yi, W., Zhang, Z., He, K., and Liu, H.: Shipping-related pollution decreased but mortality increased in Chinese port cities, Nature Cities, 1, 295–304, https://doi.org/10.1038/s44284-024-00050-8, 2024.
McDuffie, E. E., Smith, S. J., O'Rourke, P., Tibrewal, K., Venkataraman, C., Marais, E. A., Zheng, B., Crippa, M., Brauer, M., and Martin, R. V.: A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): an application of the Community Emissions Data System (CEDS), Earth Syst. Sci. Data, 12, 3413–3442, https://doi.org/10.5194/essd-12-3413-2020, 2020.
Paolo, F. S., Kroodsma, D., Raynor, J., Hochberg, T., Davis, P., Cleary, J., Marsaglia, L., Orofino, S., Thomas, C., and Halpin, P.: Satellite mapping reveals extensive industrial activity at sea, Nature, 625, 85–91, https://doi.org/10.1038/s41586-023-06825-8, 2024.
Smith, P., Jalkanen, P., Anderson, A., Corbett, J., Faber, J., and Hanayama, S.: Third IMO GHG Study, London, UK, 2014.
Sou, W. S., Goh, T., Lee, X. N., Ng, S. H., and Chai, K.-H.: Reducing the carbon intensity of international shipping – The impact of energy efficiency measures, Energ. Policy, 170, 113239, https://doi.org/10.1016/j.enpol.2022.113239, 2022.
Stephenson, S. R., Wang, W., Zender, C. S., Wang, H., Davis, S. J., and Rasch, P. J.: Climatic Responses to Future Trans-Arctic Shipping, Geophys. Res. Lett., 45, 9898–9908, https://doi.org/10.1029/2018GL078969, 2018.
THE United Nations Conference on Trade and Development (UNCTAD): Review of Maritime Transport, United States, https://unctad.org/publication/review-maritime-transport-2023 (last access: 16 January 2025), 2024.
Wang, X., Yi, W., Lv, Z., Deng, F., Zheng, S., Xu, H., Zhao, J., Liu, H., and He, K.: Ship emissions around China under gradually promoted control policies from 2016 to 2019, Atmos. Chem. Phys., 21, 13835–13853, https://doi.org/10.5194/acp-21-13835-2021, 2021.
Wen, Y., Xiaotong, W., Tingkun, H., Huan, L., Luo, Z., and Kebin, H.: Global shipping emissions for the years 2013 and 2016–2021, Zenodo [data set], https://doi.org/10.5281/zenodo.10869014, 2024.
Yi, W., He, T., Wang, X., Soo, Y. H., Luo, Z., Xie, Y., Peng, X., Zhang, W., Wang, Y., Lv, Z., He, K., and Liu, H.: Ship emission variations during the COVID-19 from global and continental perspectives, Sci. Total Environ., 954, 176633, https://doi.org/10.1016/j.scitotenv.2024.176633, 2024.
Yuan, T., Song, H., Wood, R., Wang, C., Oreopoulos, L., Platnick, S. E., von Hippel, S., Meyer, K., Light, S., and Wilcox, E.: Global reduction in ship-tracks from sulfur regulations for shipping fuel, Sci. Adv., 8, eabn7988, https://doi.org/10.1126/sciadv.abn7988, 2022.
Zhang, C., Shi, Z., Zhao, J., Zhang, Y., Yu, Y., Mu, Y., Yao, X., Feng, L., Zhang, F., Chen, Y., Liu, X., Shi, J., and Gao, H.: Impact of air emissions from shipping on marine phytoplankton growth, Sci. Total Environ., 769, 145488, https://doi.org/10.1016/j.scitotenv.2021.145488, 2021.
Zhang, Q., Wan, Z., Hemmings, B., and Abbasov, F.: Reducing black carbon emissions from Arctic shipping: Solutions and policy implications, J. Clean. Product., 241, 118261, https://doi.org/10.1016/j.jclepro.2019.118261, 2019.
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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