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<p>Nitrogen dioxide (NO<sub>2</sub>) is a major atmospheric pollutant that threatens human health and environmental quality amid rapid urbanization and industrialization. The Yellow River Basin is a heavily populated and economically significant area that is essential to China’s industrial and agricultural sectors. For this reason, it is especially critical to accurately measure NO<sub>2</sub> concentrations and related dry deposition fluxes. To estimate near-surface NO<sub>2</sub> concentrations throughout the Yellow River Basin from 2015 to 2023, a Random Forest (RF) machine learning model was created using tropospheric NO<sub>2</sub> column data from the Ozone Monitoring Instrument (OMI), ground-based station observations, and auxiliary environmental variables. With an <i>R</i><sup>2</sup> (coefficient of determination) of 0.884 and RMSE (root mean square error) of 4.626 µg/m<sup>3</sup> for the training set and an <i>R</i><sup>2</sup> of 0.777 with RMSE of 6.447 µg/m<sup>3</sup> for the test set, the model demonstrated strong predictive ability. NO<sub>2</sub> levels showed a little downward trend from 2015 to 2021, followed by a modest uptick in 2021–2023, according to spatial and temporal analysis. Seasonally, there was a clear U-shaped pattern with winter peaks and summer troughs in NO<sub>2</sub> concentrations and the associated dry deposition fluxes. Upstream regions like Sichuan and Qinghai had consistently low levels, while industrialized downstream provinces like Shandong, Henan, and Shanxi had high rates. These results offer scientific support for nitrogen load mitigation and air quality management in the Yellow River Basin, as well as crucial insights into the spatial dynamics of NO<sub>2</sub> pollution.</p>

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Spatial–temporal distribution and variation of atmospheric NO2 dry deposition in the Yellow River Basin from 2015 to 2023

  • 期刊论文

  • 发表日期：

    2026年1月10日

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  • Zhenxing Rao,
  • Zhuo Wang,
  • Yicong Liang,
  • Linjing Zhang,
  • Jinke Sun,
  • Shanshan Li

摘要

Nitrogen dioxide (NO2) is a major atmospheric pollutant that threatens human health and environmental quality amid rapid urbanization and industrialization. The Yellow River Basin is a heavily populated and economically significant area that is essential to China’s industrial and agricultural sectors. For this reason, it is especially critical to accurately measure NO2 concentrations and related dry deposition fluxes. To estimate near-surface NO2 concentrations throughout the Yellow River Basin from 2015 to 2023, a Random Forest (RF) machine learning model was created using tropospheric NO2 column data from the Ozone Monitoring Instrument (OMI), ground-based station observations, and auxiliary environmental variables. With an R2 (coefficient of determination) of 0.884 and RMSE (root mean square error) of 4.626 µg/m3 for the training set and an R2 of 0.777 with RMSE of 6.447 µg/m3 for the test set, the model demonstrated strong predictive ability. NO2 levels showed a little downward trend from 2015 to 2021, followed by a modest uptick in 2021–2023, according to spatial and temporal analysis. Seasonally, there was a clear U-shaped pattern with winter peaks and summer troughs in NO2 concentrations and the associated dry deposition fluxes. Upstream regions like Sichuan and Qinghai had consistently low levels, while industrialized downstream provinces like Shandong, Henan, and Shanxi had high rates. These results offer scientific support for nitrogen load mitigation and air quality management in the Yellow River Basin, as well as crucial insights into the spatial dynamics of NO2 pollution.