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<p>Air pollution from fine airborne particles remains one of the leading environmental threats to human health, yet it is unclear whether scientific research is concentrated where pollution burdens are greatest. Here we show that global research activity is distributed primarily according to economic capacity rather than environmental need by analyzing more than 55,000 scientific publications published between 1980 and 2025. Using artificial intelligence assisted geographic text analysis, satellite observations of atmospheric aerosol loading, health indicators, and interpretable machine learning, we identify a persistent knowledge exposure gap worldwide. Air quality research is concentrated in economically developed regions, whereas regions including South Asia and sub-Saharan Africa experience some of the highest long term aerosol burdens but conduct disproportionately few studies. Our approach establishes a data-driven framework for understanding how scientific attention is distributed relative to environmental need. These findings reveal a global imbalance between scientific attention and environmental need and highlight the importance of strengthening research capacity in highly affected regions.</p>

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Global particulate pollution research reflects economic capacity more than pollution burden

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月27日

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  • Jiani Yang,
  • Antong Zhang,
  • Xun Jian,
  • Kairui Qiu,
  • Vijay Natraj,
  • Hangyu Gao,
  • Sally Newman,
  • Joseph P. Pinto,
  • Yuk L. Yung

摘要

Air pollution from fine airborne particles remains one of the leading environmental threats to human health, yet it is unclear whether scientific research is concentrated where pollution burdens are greatest. Here we show that global research activity is distributed primarily according to economic capacity rather than environmental need by analyzing more than 55,000 scientific publications published between 1980 and 2025. Using artificial intelligence assisted geographic text analysis, satellite observations of atmospheric aerosol loading, health indicators, and interpretable machine learning, we identify a persistent knowledge exposure gap worldwide. Air quality research is concentrated in economically developed regions, whereas regions including South Asia and sub-Saharan Africa experience some of the highest long term aerosol burdens but conduct disproportionately few studies. Our approach establishes a data-driven framework for understanding how scientific attention is distributed relative to environmental need. These findings reveal a global imbalance between scientific attention and environmental need and highlight the importance of strengthening research capacity in highly affected regions.