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Blockchain-based isotopic big data-driven tracing of global PM sources and interventions

Author

Listed:
  • Yuming Huang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Xiangyu Li

    (Chinese Academy of Sciences)

  • Yuehan Wu

    (Chinese Academy of Sciences)

  • Chaoyang Xue

    (Max Planck Institute for Chemistry)

  • Jiashuo Li

    (Shandong University)

  • Yongfeng Lin

    (Chinese Academy of Sciences)

  • Wei Nie

    (Nanjing University)

  • Xian Liu

    (Chinese Academy of Sciences)

  • Qian Liu

    (Chinese Academy of Sciences)

  • Greg Michalski

    (550 Stadium Mall Drive)

  • Jingwei Zhang

    (Yunnan University)

  • Zheng Zong

    (Shandong University)

  • Dawei Lu

    (Chinese Academy of Sciences
    Jianghan University)

  • Guibin Jiang

    (Chinese Academy of Sciences)

Abstract

Tracing sources and assessing intervention effectiveness are crucial for controlling atmospheric particulate matter (PM) pollution. Isotopic techniques enable precise top-down tracing, but the absence of long-term, global-scale multi-compound isotopic data limits comprehensive analysis. Here, we establish a blockchain-based isotopic database, compiling 34,815 isotopic fingerprints of global PM and its emissions from 1,890 pollution events across 66 countries. This allows retrospective analysis and predictions, revealing that PM sources are distinct, dynamically changing over time, and often asynchronous with interventions. Additionally, we estimate source contributions to PM2.5 and its compounds, highlighting the increasing impact of biomass burning. Furthermore, projections indicate that by 2100, PM levels may decline to 5.38 ± 0.16 μg/m³ in the Americas and 13.9 ± 1.82 μg/m³ in Asia under climate mitigation scenarios but will still exceed WHO guidelines without further controls on natural emissions. Guiding future interventions with isotopic big data is essential for addressing air pollution challenges.

Suggested Citation

  • Yuming Huang & Xiangyu Li & Yuehan Wu & Chaoyang Xue & Jiashuo Li & Yongfeng Lin & Wei Nie & Xian Liu & Qian Liu & Greg Michalski & Jingwei Zhang & Zheng Zong & Dawei Lu & Guibin Jiang, 2025. "Blockchain-based isotopic big data-driven tracing of global PM sources and interventions," Nature Communications, Nature, vol. 16(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59220-4
    DOI: 10.1038/s41467-025-59220-4
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    References listed on IDEAS

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