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<p>China’s underdeveloped ethnic minority regions, though meeting national air quality standards, face large gaps from international benchmarks—an understudied issue in atmospheric governance. This study focuses on Jingzhou Miao and Dong Autonomous County (southwest China), based on 7-year (2018–2024) ground-based PM<sub>2.5</sub> and related data, integrating Ensemble Empirical Mode Decomposition (EEMD), Random Forest (RF)-based meteorological normalization, and partial dependence analysis. Its annual average PM<sub>2.5</sub> ((26 ± 19) µg·m⁻³) meets China’s Grade Ⅱ standard but exceeds the 2021 WHO guideline (5&#xa0;µg·m⁻³) over fivefold, needing an about 81% cut. Monthly concentrations present a “U”-shaped seasonal pattern (winter &gt; autumn &gt; spring &gt; summer), with a slight non-significant interannual decline. EEMD shows long-term monthly variations (55% of variance) dominate, with a significant upward trend of 0.94&#xa0;µg·m⁻³·a⁻¹ (<i>p</i> &lt; 0.05) pre-meteorological correction. RF normalization quantifies opposing effects: emissions reduce PM<sub>2.5</sub> by -5&#xa0;µg·m⁻³·a⁻¹ on average, while meteorology (strongest in winter, + 7&#xa0;µg·m⁻³) increases it by + 4&#xa0;µg·m⁻³. The 60.8% PM<sub>2.5</sub>/PM<sub>10</sub> ratio confirms anthropogenic fine particles dominate; temperature, pressure, and humidity are key meteorological drivers. These findings highlight health disparities, emphasizing targeted control of secondary aerosol precursors (SO<sub>2</sub>, NO<sub>x</sub>, VOCs) and climate-responsive measures. The study supports refined air quality management in similar regions and balanced national atmospheric governance.</p>

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Disentangling meteorological and emission drivers of PM2.5 and bridging the gap to WHO guideline: A case study in an underdeveloped ethnic minority County in Southwest China

  • 期刊论文

  • 发表日期：

    2026年2月21日

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  • Xuling Ma,
  • Yanlin Chu,
  • Yi Li,
  • Ying Wang,
  • Weili Lin

摘要

China’s underdeveloped ethnic minority regions, though meeting national air quality standards, face large gaps from international benchmarks—an understudied issue in atmospheric governance. This study focuses on Jingzhou Miao and Dong Autonomous County (southwest China), based on 7-year (2018–2024) ground-based PM2.5 and related data, integrating Ensemble Empirical Mode Decomposition (EEMD), Random Forest (RF)-based meteorological normalization, and partial dependence analysis. Its annual average PM2.5 ((26 ± 19) µg·m⁻³) meets China’s Grade Ⅱ standard but exceeds the 2021 WHO guideline (5 µg·m⁻³) over fivefold, needing an about 81% cut. Monthly concentrations present a “U”-shaped seasonal pattern (winter > autumn > spring > summer), with a slight non-significant interannual decline. EEMD shows long-term monthly variations (55% of variance) dominate, with a significant upward trend of 0.94 µg·m⁻³·a⁻¹ (p < 0.05) pre-meteorological correction. RF normalization quantifies opposing effects: emissions reduce PM2.5 by -5 µg·m⁻³·a⁻¹ on average, while meteorology (strongest in winter, + 7 µg·m⁻³) increases it by + 4 µg·m⁻³. The 60.8% PM2.5/PM10 ratio confirms anthropogenic fine particles dominate; temperature, pressure, and humidity are key meteorological drivers. These findings highlight health disparities, emphasizing targeted control of secondary aerosol precursors (SO2, NOx, VOCs) and climate-responsive measures. The study supports refined air quality management in similar regions and balanced national atmospheric governance.