长江流域资源与环境 >> 2024, Vol. 33 >> Issue (8): 1768-1780.doi: 10.11870/cjlyzyyhj202408014

• 生态环境 • 上一篇    下一篇

干旱事件下PM2.5和臭氧复合污染动力机制及其影响因素

张娇1, 吴波2*, 赵佩1, 王苑博1   

  1. (1.吉首大学数学与统计学院, 湖南 吉首 416000;2. 中南财经政法大学统计与数学学院,湖北 武汉 430073)
  • 出版日期:2024-08-20 发布日期:2024-08-21

Internal Dynamic Mechanism of Atmospheric Composite Pollution and Its Driving Factors During Drought Events

ZHANG Jiao1,WU Bo2,ZHAO Pei1,WANG Yuan-Bo1   

  1. (1.College of Mathematics and Statistics,Jishou University,Jishou 416000,China; 2.School of Statistics and Mathematics,Zhongnan University of Economics and Law,Wuhan 430073,China)
  • Online:2024-08-20 Published:2024-08-21

摘要: 以长株潭城市群3个城市(长沙、株洲和湘潭)干旱期间(2022年7月1日至12月31日)和非干旱期间(2020和2021年同期)PM2.5和O3小时平均浓度序列为研究对象,探究干旱事件对PM2.5-O3复合污染演化的内在动力机制的影响及其影响因素。首先,对研究期间3个城市PM2.5和O3浓度的日变化模式进行分析,结果发现PM2.5浓度均呈现出M型的日变化规律,但干旱期间PM2.5浓度下降,且波峰和波谷时段发生显著变化。O3浓度日变化均呈现出“昼高夜低”单峰型模式,干旱期间O3浓度上升。接下来,应用多重分形去趋势互相关分析法(MF-DCCA)研究PM2.5-O3互相关性的多时间尺度特征。研究结果发现,各年各城市PM2.5-O3互相关关系均呈现出显著地长期持续性特征和多重分形结构,且干旱期间各城市长期持续性指数均降低,多重分形强度增强。进而,应用滑移窗口方法、MF-DCCA以及格兰杰因果检验方法分析PM2.5-O3互相关长期持续性特征演化规律及其影响因素。结果发现,干旱期间各城市PM2.5-O3互相关的长期持续性演化的影响因素主要是气压,而非干旱期间的影响因素主要是气温和风速。最后,基于自组织临界理论(SOC)探讨非干旱期间和干旱期间PM2.5-O3互相关关系的内在动力机制。结果发现,长期持续性特征主要受SOC机制所主导,即SOC机制是驱动PM2.5-O3复合污染演化的主要非线性动力机制,但干旱事件使得主要影响因素由气温和风速变成气压。文章拓展了复合污染的内在动力机制的相关研究,为我国深入推进全球变暖背景下复合污染防控提供了新的启示。

Abstract: The hourly average concentrations of PM2.5 and O3 in the three cities of the Chang-Zhu-Tan urban agglomeration (Changsha,Zhuzhou,and Xiangtan) were analyzed for both drought (July 1 to December 31,2022) and non-drought periods (corresponding periods in 2020 and 2021).The objective was to explore the impact of drought events on the intrinsic dynamic mechanisms of PM2.5-O3 compound pollution and its influencing factors.Initially,the diurnal patterns of PM2.5 and O3 concentrations during the study period were examined.It was observed that PM2.5 concentrations followed an M-shaped diurnal variation pattern,with a decrease during the drought period and significant shifts in the timing of peaks and troughs.Conversely,O3 concentrations showed a unimodal pattern of being higher during the day and lower at night,with an increase during the drought period.Subsequently,Multifractal Detrended Cross-Correlation Analysis (MF-DCCA) was employed to investigate the multi-timescale characteristics of the cross-correlation between PM2.5 and O3.The results revealed significant long-term persistence and multifractal characteristics in the cross-correlation of PM2.5 and O3 across all cities and years,with a decrease in persistence indices and an increase in multifractal intensity during the drought periods.Furthermore,the sliding window method,MF-DCCA,and Granger causality tests were utilized to analyze the evolution and influencing factors of the long-term persistence characteristics of PM2.5-O3 cross-correlation.This study found that atmospheric pressure was the primary factor influencing the evolution of long-term persistence in PM2.5-O3 cross-correlation during the drought periods,while temperature and wind speed were the main factors during the non-drought periods.Finally,the Self-Organized Criticality theory (SOC) was applied to discuss the internal dynamic mechanisms of PM2.5-O3 cross-correlation during both drought and non-drought periods.The findings of this study provided a useful reference for coping with atmospheric composite pollution under the global warming condition.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!