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<p>Road dust constitutes a significant source of atmospheric particulate matter (PM), substantially contributing to urban pollution loads. However, systematic source apportionment of road dust remains insufficient, and conventional receptor modeling approaches exhibit notable limitations. This study aims to trace the sources of urban road dust by integrating micro- and macro-scale perspectives. We innovatively developed and applied a methodology that leverages Scanning Electron Microscopy-Energy Dispersive Spectroscopy (SEM-EDS) characterization of particle heterogeneity and regional disparity to constrain Positive Matrix Factorization (PMF) source apportionment. Key findings reveal that: The principal sources of urban road dust were identified as geogenic sources, sea salt, coal combustion, vehicle emissions (further differentiated into exhaust and non-exhaust mechanical wear when the PMF model featured multiple characteristic factors), and industrial activities. The proposed multi-scale integrated approach enables more scientifically robust and precise identification of PM sources, offering a novel methodological framework and valuable reference for researchers in related fields.</p>

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Multi-scale SEM-EDS characterization of road dust particles: integrating heterogeneity and regional disparity to constrain PMF source apportionment

  • 期刊论文

  • 发表日期：

    2026年1月17日

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  • Kaichen Bai,
  • Fumin Ren,
  • Jinming Jia

摘要

Road dust constitutes a significant source of atmospheric particulate matter (PM), substantially contributing to urban pollution loads. However, systematic source apportionment of road dust remains insufficient, and conventional receptor modeling approaches exhibit notable limitations. This study aims to trace the sources of urban road dust by integrating micro- and macro-scale perspectives. We innovatively developed and applied a methodology that leverages Scanning Electron Microscopy-Energy Dispersive Spectroscopy (SEM-EDS) characterization of particle heterogeneity and regional disparity to constrain Positive Matrix Factorization (PMF) source apportionment. Key findings reveal that: The principal sources of urban road dust were identified as geogenic sources, sea salt, coal combustion, vehicle emissions (further differentiated into exhaust and non-exhaust mechanical wear when the PMF model featured multiple characteristic factors), and industrial activities. The proposed multi-scale integrated approach enables more scientifically robust and precise identification of PM sources, offering a novel methodological framework and valuable reference for researchers in related fields.