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Shipping-related pollution decreased but mortality increased in Chinese port cities

Nature Cities volume 1, pages 295–304 (2024)Cite this article

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Abstract

The maritime industry boosts the prosperity of port cities but also exacerbates premature death associated with air pollution. In recent years, Chinese port cities have undergone profound multifaceted transformations on emissions control and demographic characteristics, leading to an unclear relationship between shipping emissions and health burden. Here we built a comprehensive evaluation framework to investigate the impacts of ships in Chinese port cities from 2016 to 2020. We found shipping-related fine particulate matter (PM2.5) decreased across all port cities under shipping sulfur emissions control. However, nationwide shipping-related mortality associated with long-term PM2.5 exposure increased by 11.4% to 48,300 deaths in 2020. A trend of mitigation was observed in coastal cities, but a trend of aggravation in port cities along inland rivers due to varying antagonisms between shipping emissions reductions and regional demographic changes. Population clustering in port cities necessitates further locality-specific control of shipping emissions.

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Fig. 1: Geographical scope and city-level migration trends (2016 to 2020) for port city clusters defined in this study.
Fig. 2: Main policy and emissions for Chinese port city clusters.
Fig. 3: Shipping-related PM2.5 pollution and mortality.
Fig. 4: PM2.5 contributions from vessel types and chemical components.
Fig. 5: Contribution decomposition of changes in overall long-term PM2.5 exposure-associated deaths from 2016 to 2020.

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Data availability

Data supporting the main findings in this study are available at https://doi.org/10.5281/zenodo.10643061. The ship automatic identification system big data and ship technical specifications database are restricted to third parties and used under license for this study. The shipping emissions data are available from the corresponding author upon request. The other emissions data are publicly available, with details described in Supplementary Table 1. The population data and cross-sectional mortality rate are publicly available, with details described in Supplementary Information section ‘Excess mortality estimation’.

Code availability

The codes associated with this paper involve Python version 3.7 and R version 4.2.2. Codes used during the current study are available from the corresponding author upon reasonable request.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (grant nos. 42325505 and U2233203) to H.L., National Key Research and Development Program of China (grant no. 2022YFC3704200) to H.L. and the Tsinghua University-Toyota Research Center.

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Author notes

  1. These authors contributed equally: Zhenyu Luo, Zhaofeng Lv.

Authors and Affiliations

  1. State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing, China

    Zhenyu Luo, Zhaofeng Lv, Junchao Zhao, Tingkun He, Wen Yi, Zhining Zhang, Kebin He & Huan Liu

  2. Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK

    Haitong Sun

  3. International Joint Laboratory on Low Carbon Clean Energy Innovation, Ministry of Education, Beijing, China

    Kebin He & Huan Liu

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  1. Zhenyu Luo
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Contributions

Z. Luo, Z. Lv and H.L. designed the research. Z. Luo and Z. Lv performed the air quality and mortality estimation model. J.Z., H.S., T.H., W.Y. and Z.Z. performed the analyses and visualization. H.L. and K.H. provided insights into the scenario design. All authors contributed to the writing.

Corresponding author

Correspondence to Huan Liu.

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Nature Cities thanks Daniele Contini, Elen Twrdy and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary results, methods, Figs. 1–17, Tables 1–8 and References.

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Luo, Z., Lv, Z., Zhao, J. et al. Shipping-related pollution decreased but mortality increased in Chinese port cities. Nat Cities 1, 295–304 (2024). https://doi.org/10.1038/s44284-024-00050-8

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