Distant source contributions to PM10 profile evaluated by SOM based cluster analysis of air mass trajectory sets

Ferhat Karaca, Fatih Camci

Research output: Contribution to journalArticle

51 Citations (Scopus)

Abstract

This paper evaluates the effects of long-range transport patterns of air masses to the regional PM profile in a megacity, Istanbul, Turkey. Five-day hourly backward trajectories were obtained by the HYSPLIT model for selected episodic events in 2008. Self Organizing Maps (SOM), a very powerful classification tool, was used to cluster these trajectories. In total, eight cluster groups were obtained. All of the clusters were evaluated with respect to inhalable particulate matter (PM10) concentrations observed in Istanbul for the arrival times of the trajectories. Istanbul is generally under the effect of trajectories in three clusters (1, 2 and 4) (52% of all pre-selected episodic events), which have higher mean concentration values than the mean value of all the samples. These clusters typically make significant PM contributions to Istanbul's air quality. PM loadings of the trajectories in these clusters were attributed to massive anthropogenic activity over all of Europe and southwestern air flow most likely carrying PM10 atmospheric particles originating from the Saharan Desert and other global dust generation regions located in the northern part of Africa.

Original languageEnglish
Pages (from-to)892-899
Number of pages8
JournalAtmospheric Environment
Volume44
Issue number7
DOIs
Publication statusPublished - Mar 1 2010
Externally publishedYes

Keywords

  • Air pollution
  • Artificial neural networks (ANN)
  • Cluster analysis
  • HYSPLIT model
  • Long-range transport

ASJC Scopus subject areas

  • Environmental Science(all)
  • Atmospheric Science

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