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Global industrial emissions of chlorinated and brominated polycyclic aromatic hydrocarbons

Nature Sustainability (2025)Cite this article

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Abstract

Chlorinated and brominated polycyclic aromatic hydrocarbons (Cl/BrPAHs) are emerging organic pollutants that pose severe risks to both the natural environment and public health. However, the limited understanding of their global emission sources and levels hinders effective control measures. Here we present a comprehensive global inventory and source attribution analysis of Cl/BrPAH emissions from 11 key industrial sectors. By integrating emission data with machine learning models, we estimate that global industrial Cl/BrPAH emissions in 2018 were 5,143 kg (94.3% ClPAHs and 5.7% BrPAHs) across 184 countries. Emission hotspots, in terms of total estimated Cl/BrPAH emissions, were concentrated in Oceania, East Asia and Latin America, collectively accounting for over 66% of the global total emissions. Iron ore sintering was identified as the largest industrial source (86.1% of total emissions). These findings can facilitate policy-making and the development of mitigation strategies for Cl/BrPAH emissions, and eventually contribute to greener industries.

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Fig. 1: Emission concentrations of ClPAHs and BrPAHs.
Fig. 2: EFs and contribution distributions of ClPAHs and BrPAHs.
Fig. 3: Total emissions of Cl/BrPAHs from ten global industrial sources.
Fig. 4: Global patterns of Cl/BrPAH emissions.
Fig. 5: Cl/BrPAH emissions categorized by types and sources.

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Data availability

The minimum dataset necessary to interpret, verify and extend the work is provided in Supplementary Information. Geospatial maps (Figs. 3 and 4 and Supplementary Figs. 3–6 and 10) were generated using ArcGIS 10.2 on the basis of open-access vector data from GADM (https://gadm.org/). The machine learning datasets of this study are provided in Supplementary Data as a tabular-format spreadsheet, including the datasets required for modelling and prediction. The final modelling data, including Supplementary Data 1 (modeling data), Supplementary Data 2 (forecast data) and Supplementary Data 3 (output data of Monte Carlo simulation), are also provided with this paper. Furthermore, the source dataset for Figs. 1–5 are available via Zenodo at https://doi.org/10.5281/zenodo.15869972.

Code availability

Code used for this study is available via GitHub at https://github.com/123yangyueyao/XGBoost-Forecast-Model-of-XPAHs.

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Acknowledgements

We acknowledge the financial support provided by the National Natural Science Foundation of China (grant no. 22106030), ‘Pioneer’ and ‘Leading Goose’ R&D Program of Zhejiang (grant nos. 2025C02218 and 2023C03157) and the Research Funds of Hangzhou Institute for Advanced Study, UCAS (grant nos. 2023HIAS-Y014 and 2024HIAS-Y005).

Author information

Authors and Affiliations

  1. Zhejiang Key Laboratory of Environment and Health of New Pollutants, School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China

    Yueyao Yang, Yahui Liu, Zhefu Yu, Guohua Zhu, Bingcheng Lin, Yunfeng Ma, Guorui Liu, Rong Jin & Minghui Zheng

  2. State Key Laboratory of Environmental Chemistry and Toxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China

    Yueyao Yang, Yahui Liu, Zhefu Yu & Minghui Zheng

  3. College of Resource and Environment, University of Chinese Academy of Sciences, Beijing, China

    Yueyao Yang, Yahui Liu, Zhefu Yu & Minghui Zheng

  4. College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, China

    Guorui Liu

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Contributions

R.J. conceived and supervised the project. Y.Y. performed the experiments, analysed the data and wrote the paper. Y.L. and Z.Y. contributed to sample analysis and interpretation. R.J., Y.Y., Y.M., G.L. and M.Z. discussed the results. R.J., G.Z., B.L., Y.M. and G.L. collected the samples. All authors revised and approved the final paper.

Corresponding author

Correspondence to Rong Jin.

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The authors declare no competing interests.

Peer review

Peer review information

Nature Sustainability thanks Guofeng Shen, Huizhong Shen and Quang Vuong for their contribution to the peer review of this work. Peer reviewer reports are available.

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Supplementary information

Supplementary Information

Supplementary Discussion 1–7, Notes 1–6, Figs. 1–12, Tables 1–10 and References.

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Peer Review File

Supplementary Data

1, modelling data—no names; 2, modelling data; 3, forecast data—no names; and 4, forecast data.

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Yang, Y., Liu, Y., Yu, Z. et al. Global industrial emissions of chlorinated and brominated polycyclic aromatic hydrocarbons. Nat Sustain (2025). https://doi.org/10.1038/s41893-025-01656-z

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