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Purpose <p>High PM<sub>2.5</sub> pollution episodes can affect entire regions around the world and have substantial impacts on climate, visibility, and human health. Understanding the main characteristics, origin, and transport pathways of PM<sub>2.5</sub> episodes is crucial for determining the episodes causes, alleviating episodic pollution, and regional joint emission control strategies. We used daily average PM<sub>2.5</sub> data as well as related meteorological data.</p> Methods <p>The STL (Seasonal-Trend decomposition based on Loess) method was utilized for the identification of PM<sub>2.5</sub> episodes during January to December (2015-2021) in Tehran, Iran. The trends in the duration, frequency, and number of PM<sub>2.5</sub> episodes were assessed and the PM<sub>2.5</sub> baseline trends compared with these trends. Additionally, the characteristics of episodes were investigated using three categories.</p> Results <p>The results showed an all-site annual severity of PM<sub>2.5</sub> pollution episodes durations as being more than 50% higher than the seasonal trend. The PM<sub>2.5</sub> episode frequency trends indicated a reverse relationship between the episode frequency and their duration. The PM<sub>2.5</sub> episodes with longer duration showed higher PM<sub>2.5</sub> magnitude and concentration. Greater unfavorable meteorological conditions produced longer duration PM<sub>2.5</sub> pollution episodes. There was only one high diel PM<sub>2.5</sub> peak around midnight (23:00 pm–2:00 am) for most of the monitoring sites during episodes. Air parcel transport pathways during PM<sub>2.5</sub> episodes indicated that the air trajectories having the highest polluted average PM<sub>2.5</sub> values varied based on the episode duration. The trajectories from intermediate-distance transmission arriving in Tehran during PM<sub>2.5</sub> pollution episodes showed the highest average PM<sub>2.5</sub> values for all durations and total duration.</p> Conclusions <p>These findings provide insights into the potential for accurate approaches for forecasting episodes and development of effective emergency mitigation strategies for the anthropogenic emissions during meteorological conditions that drive episode formation.</p> Graphical Abstract <p></p>

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Characterization and Transport Pathways of High PM2.5 Pollution Episodes During 2015–2021 in Tehran, Iran

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月5日

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  • Mohammad Saleh Ali-Taleshi,
  • Alireza Riyahi Bakhtiari,
  • Nairui Liu,
  • Philip K. Hopke

摘要

Purpose

High PM2.5 pollution episodes can affect entire regions around the world and have substantial impacts on climate, visibility, and human health. Understanding the main characteristics, origin, and transport pathways of PM2.5 episodes is crucial for determining the episodes causes, alleviating episodic pollution, and regional joint emission control strategies. We used daily average PM2.5 data as well as related meteorological data.

Methods

The STL (Seasonal-Trend decomposition based on Loess) method was utilized for the identification of PM2.5 episodes during January to December (2015-2021) in Tehran, Iran. The trends in the duration, frequency, and number of PM2.5 episodes were assessed and the PM2.5 baseline trends compared with these trends. Additionally, the characteristics of episodes were investigated using three categories.

Results

The results showed an all-site annual severity of PM2.5 pollution episodes durations as being more than 50% higher than the seasonal trend. The PM2.5 episode frequency trends indicated a reverse relationship between the episode frequency and their duration. The PM2.5 episodes with longer duration showed higher PM2.5 magnitude and concentration. Greater unfavorable meteorological conditions produced longer duration PM2.5 pollution episodes. There was only one high diel PM2.5 peak around midnight (23:00 pm–2:00 am) for most of the monitoring sites during episodes. Air parcel transport pathways during PM2.5 episodes indicated that the air trajectories having the highest polluted average PM2.5 values varied based on the episode duration. The trajectories from intermediate-distance transmission arriving in Tehran during PM2.5 pollution episodes showed the highest average PM2.5 values for all durations and total duration.

Conclusions

These findings provide insights into the potential for accurate approaches for forecasting episodes and development of effective emergency mitigation strategies for the anthropogenic emissions during meteorological conditions that drive episode formation.

Graphical Abstract