<p>Air pollution poses a significant public health risk, as pollutants, emitted from both natural and anthropogenic sources, can penetrate deep into the respiratory system, leading to a wide range of respiratory diseases. While numerous studies have examined the role of meteorological factors in modulating air quality, limited research has focussed specifically on their effectiveness in regions characterized by intensive mineral extraction activities, particularly coal mining zones where emission loads remain persistently high. In this context, the concentration levels of PM<sub>10</sub>, PM<sub>2.5</sub>, SO<sub>2</sub>, and NO<sub>2</sub> were continuously monitored for one year using an automated ambient air quality monitoring system to investigate their seasonal behaviour and meteorological interactions. The recorded concentration ranged from 17.49 to 393.40&#xa0;µg/m<sup>3</sup> for PM<sub>10</sub>, 5.45 to 231.53&#xa0;µg/m<sup>3</sup> for PM<sub>2.5</sub>, 12.3 to 62.05&#xa0;µg/m<sup>3</sup> for NO<sub>2</sub>, and 11.59 to 182&#xa0;µg/m<sup>3</sup> for SO<sub>2</sub>. The pollutant concentrations peaked during winter and declined during summer and monsoon seasons. The trend analysis using Theil–Sen estimator revealed significant negative trends for all four pollutants PM<sub>10</sub> (−&#xa0;181.79 units), PM<sub>2.5</sub> (−&#xa0;106.11 units), SO<sub>2</sub> (−&#xa0;22.76 units), and NO<sub>2</sub> (−&#xa0;29.89 units). The linear regression analysis demonstrated a strong correlation between PM<sub>10</sub> and PM<sub>2.5</sub> (R<sup>2</sup> = 0.89), whereas a weak association (R<sup>2</sup> = 0.01) was observed between NO<sub>2</sub> and SO<sub>2</sub>. Nonlinear regression further indicated temperature as a key influencing factor, showing a strong inverse relationship with NO<sub>2</sub> (−&#xa0;13.218) and a moderate negative impact on PM<sub>2.5</sub> (−&#xa0;1.517). Overall, the findings of this study underscore highlight the seasonal vulnerability of coal mining regions to pollutant accumulation and highlights the limitations of mechanisms under elevated emission scenarios. Furthermore, this study establishes temperature as a boundary-layer control variable and emphasizes that effective air-quality management in coal-mining regions must integrate real-time meteorological forecasting with emission scheduling for sustainable air-quality compliance.</p>

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Seasonal variability and temperature-driven temporal dynamics of air pollutants in a mega coal mining zone of the talcher coalfield

  • Artatrana Mishra,
  • Sarat Chandra Sahu,
  • Manish Yadav,
  • Nitin Kumar Singh,
  • Charu Jhamaria,
  • Amit Karmakar,
  • Sumit Saha

摘要

Air pollution poses a significant public health risk, as pollutants, emitted from both natural and anthropogenic sources, can penetrate deep into the respiratory system, leading to a wide range of respiratory diseases. While numerous studies have examined the role of meteorological factors in modulating air quality, limited research has focussed specifically on their effectiveness in regions characterized by intensive mineral extraction activities, particularly coal mining zones where emission loads remain persistently high. In this context, the concentration levels of PM10, PM2.5, SO2, and NO2 were continuously monitored for one year using an automated ambient air quality monitoring system to investigate their seasonal behaviour and meteorological interactions. The recorded concentration ranged from 17.49 to 393.40 µg/m3 for PM10, 5.45 to 231.53 µg/m3 for PM2.5, 12.3 to 62.05 µg/m3 for NO2, and 11.59 to 182 µg/m3 for SO2. The pollutant concentrations peaked during winter and declined during summer and monsoon seasons. The trend analysis using Theil–Sen estimator revealed significant negative trends for all four pollutants PM10 (− 181.79 units), PM2.5 (− 106.11 units), SO2 (− 22.76 units), and NO2 (− 29.89 units). The linear regression analysis demonstrated a strong correlation between PM10 and PM2.5 (R2 = 0.89), whereas a weak association (R2 = 0.01) was observed between NO2 and SO2. Nonlinear regression further indicated temperature as a key influencing factor, showing a strong inverse relationship with NO2 (− 13.218) and a moderate negative impact on PM2.5 (− 1.517). Overall, the findings of this study underscore highlight the seasonal vulnerability of coal mining regions to pollutant accumulation and highlights the limitations of mechanisms under elevated emission scenarios. Furthermore, this study establishes temperature as a boundary-layer control variable and emphasizes that effective air-quality management in coal-mining regions must integrate real-time meteorological forecasting with emission scheduling for sustainable air-quality compliance.