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<p>In recent years, with the ongoing rise in surface temperatures, heat waves, a frequently occurring extreme weather phenomenon, have manifested within the context of global warming. To investigate the variation of atmospheric pollutants ozone (O<sub>3</sub>), formaldehyde (HCHO), and nitrogen dioxide (NO<sub>2</sub>) and their relationship with meteorological factors during normal weather conditions from March to July 2018–2022, as well as during extreme weather conditions in the Mexican region from March to July 2023. This study utilizes Python, ArcGIS 10.8, and other software to investigate pollutants during two time periods by employing the Geographical Time-Weighted Regression model (GTWR), Random Forest Regression model, Backward Trajectory model, and Ozone Generation Sensitivity Analysis based on daily data from the OMI satellite and meteorological factors. The findings suggest that: (1) O<sub>3</sub> concentrations exhibit an increase, while HCHO concentrations demonstrate a decrease during extreme weather events in the study area; however, NO<sub>2</sub> concentrations do not exhibit significant changes. (2) Extreme weather conditions induce alterations in the correlation between atmospheric pollutants and meteorological factors within the Mexican region. (3) A minor portion of the study area undergoes a shift in Ozone Generation Sensitivity during occurrences of extreme weather.</p>

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Study on correlation between atmospheric pollutants and meteorological factors during extreme weather in Mexico based on GTWR model

  • 期刊论文

  • 发表日期：

    2025年3月10日

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  • Tianzhen Ju,
  • Lanzhi Wang,
  • Bingnan Li,
  • Zhichao Lv,
  • Zhenrong Gu

摘要

In recent years, with the ongoing rise in surface temperatures, heat waves, a frequently occurring extreme weather phenomenon, have manifested within the context of global warming. To investigate the variation of atmospheric pollutants ozone (O3), formaldehyde (HCHO), and nitrogen dioxide (NO2) and their relationship with meteorological factors during normal weather conditions from March to July 2018–2022, as well as during extreme weather conditions in the Mexican region from March to July 2023. This study utilizes Python, ArcGIS 10.8, and other software to investigate pollutants during two time periods by employing the Geographical Time-Weighted Regression model (GTWR), Random Forest Regression model, Backward Trajectory model, and Ozone Generation Sensitivity Analysis based on daily data from the OMI satellite and meteorological factors. The findings suggest that: (1) O3 concentrations exhibit an increase, while HCHO concentrations demonstrate a decrease during extreme weather events in the study area; however, NO2 concentrations do not exhibit significant changes. (2) Extreme weather conditions induce alterations in the correlation between atmospheric pollutants and meteorological factors within the Mexican region. (3) A minor portion of the study area undergoes a shift in Ozone Generation Sensitivity during occurrences of extreme weather.