Unveiling Atmospheric Layers: Vertical Pollution Patterns and Prospects for High-Resolution Aerosol Retrievals Using the Eastern Mediterranean as a Case Study

Irina Rogozovsky, Albert Ansmann, Julian Hofer, Alexandra Chudnovsky

Research output: Contribution to journalArticlepeer-review

Abstract

The vertical distribution of aerosols plays a fundamental role in shaping air quality, influencing energy balance through radiative forcing, and impacting atmospheric dynamics. In the Eastern Mediterranean, we identify 10 distinct layering conditions characterized by specific vertical layering structures and aerosol mixing states. These configurations range from purely anthropogenic layers to complex multilayered mixtures, where marine aerosols, anthropogenic pollution, and dust occupy different altitudes, sometimes interacting or being further modified by rain. We conducted air mass back-trajectory clustering at 700 and 1700 m above ground level, linking pollution types to their transport origins. Satellite-derived aerosol optical depth biases were also systematically evaluated under various pollution scenarios, showing a strong satellite-ground correlations during dust events but poor accuracy under nondust conditions with marine-anthropogenic mixtures (35% of cases). Random Forest analyses demonstrated the potential to predict pollution layering types. Additionally, anthropogenic pollution content is increasing with altitude across all layering types, with evidence suggesting a growing prominence of anthropogenic pollution. These trends align with projections of a strengthening Persian Trough, the dominant summer synoptic system. This detailed categorization provides valuable insights into the complexity of pollution sources and atmospheric interactions in the region. The integration of vertical layering data holds significant potential, enhancing climate predictions, and pollution mitigation strategies on both local and global scales.

Original languageEnglish
Pages (from-to)12181-12195
Number of pages15
JournalEnvironmental Science and Technology
Volume59
Issue number24
DOIs
StatePublished - 24 Jun 2025

Keywords

  • AERONET
  • HYSPLIT
  • MAIAC AOD
  • PollyXT lidar
  • aerosol layering
  • pollution sources
  • random forest
  • retrieval bias

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • Environmental Chemistry

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