Analysis of Characteristics and Causes of a Severe Pollution Episode in Henan Province in November 2024

2024年11月,河南省出现了一次强度大、持续时间长、覆盖范围广的污染天气过程。本研究基于天气象诊断和后向轨迹分析等多种方法,探讨了气象条件与污染物输送对此次持续性污染事件的影响机制。主要结论如下:1) 500 hPa偏西气流主导,冷空气活动偏弱,对流层低层(850 hPa)及其以下风速较小是河南此次污染过程环流背景场的主要特征。2) 边界层内逆温层结构及弱辐合作用共同导致污染物积累,垂直扩散受阻,叠加区域污染物传输,加剧了污染程度。3) 后向轨迹聚类分析表明,河南污染气团主要源自东北路径(占比为57.14%),其次为东南路径(占比为42.85%)。潜在源贡献因子分析进一步揭示此次过程PM2.5主要贡献区域为河北南部及山东西南部。本研究可为河南及周边区域污染防控策略制定提供科学依据。In November 2024, Henan Province experienced a severe, prolonged, and extensive pollution episode. This study investigates the mechanisms of meteorological conditions and pollutant transport influencing this persistent pollution event through meteorological diagnostics and backward trajectory analysis. Key findings include: 1) The synoptic background during the pollution episode was dominated by westerly airflow at 500 hPa, significantly weakened cold air activity, and low wind speeds in the lower troposphere (850 hPa and below), which collectively contributed to pollutant accumulation. 2) The combined effects of temperature inversion structures within the boundary layer and weak convergence hindered vertical dispersion and facilitated pollutant aggregation, further exacerbated by regional pollutant transport. 3) Backward trajectory clustering analysis revealed that heavy pollution air masses in Henan primarily originated from northeastern pathways (57.14%) and secondarily from southeastern pathways (42.85%). Potential source contribution function identified southern Hebei and southwestern Shandong as major contributing regions. This study provides a scientific basis for formulating pollution control strategies in Henan and surrounding areas.

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Publication Details

Journal
Advances in Geosciences
Published
2025-01-01
DOI
https://doi.org/10.12677/ag.2025.157093
Primary Topic
Atmospheric chemistry and aerosols
Type
article
Field-Weighted Citation Impact
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article

Analysis of Characteristics and Causes of a Severe Pollution Episode in Henan Province in November 2024

智国 康
Advances in Geosciences
Atmospheric chemistry and aerosols
article

Analysis of Characteristics and Causes of a Severe Pollution Episode in Henan Province in November 2024

智国 康
article en

Abstract

2024年11月,河南省出现了一次强度大、持续时间长、覆盖范围广的污染天气过程。本研究基于天气象诊断和后向轨迹分析等多种方法,探讨了气象条件与污染物输送对此次持续性污染事件的影响机制。主要结论如下:1) 500 hPa偏西气流主导,冷空气活动偏弱,对流层低层(850 hPa)及其以下风速较小是河南此次污染过程环流背景场的主要特征。2) 边界层内逆温层结构及弱辐合作用共同导致污染物积累,垂直扩散受阻,叠加区域污染物传输,加剧了污染程度。3) 后向轨迹聚类分析表明,河南污染气团主要源自东北路径(占比为57.14%),其次为东南路径(占比为42.85%)。潜在源贡献因子分析进一步揭示此次过程PM2.5主要贡献区域为河北南部及山东西南部。本研究可为河南及周边区域污染防控策略制定提供科学依据。In November 2024, Henan Province experienced a severe, prolonged, and extensive pollution episode. This study investigates the mechanisms of meteorological conditions and pollutant transport influencing this persistent pollution event through meteorological diagnostics and backward trajectory analysis. Key findings include: 1) The synoptic background during the pollution episode was dominated by westerly airflow at 500 hPa, significantly weakened cold air activity, and low wind speeds in the lower troposphere (850 hPa and below), which collectively contributed to pollutant accumulation. 2) The combined effects of temperature inversion structures within the boundary layer and weak convergence hindered vertical dispersion and facilitated pollutant aggregation, further exacerbated by regional pollutant transport. 3) Backward trajectory clustering analysis revealed that heavy pollution air masses in Henan primarily originated from northeastern pathways (57.14%) and secondarily from southeastern pathways (42.85%). Potential source contribution function identified southern Hebei and southwestern Shandong as major contributing regions. This study provides a scientific basis for formulating pollution control strategies in Henan and surrounding areas.

Advances in GeosciencesVol. 15(07)
Openalex Percentile: Top 77%
Atmospheric chemistry and aerosols
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Analysis of Characteristics and Causes of a Severe Pollution Episode in Henan Province in November 2024 — 智国 康 · Advances in Geosciences (2025) | TGRS Research Map | TGRS