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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/amtd-6-4941-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amtd-6-4941-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Submitted as: research article 04 Jun 2013

Submitted as: research article | 04 Jun 2013

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This preprint was under review for the journal AMT but the revision was not accepted.

Applying receptor models Unmix and PMF on real data set of elements in PM for sources evaluation of the sea coastal side region (Southeast Adriatic Sea)

D. Đorđević1, S. Petrović2, D. Relić3, and A. Mihajlidi-Zelić3 D. Đorđević et al.
  • 1ICTM – Centre of Chemistry, University of Belgrade, Studentski trg 12–16, 11000 Belgrade, Serbia
  • 2ICTM – Centre of Catalysis, University of Belgrade, Studentski trg 12–16, 11000 Belgrade, Serbia
  • 3Faculty of Chemistry, University of Belgrade, Studentski trg 12–16, 11000 Belgrade, Serbia

Abstract. Two receptor modeling techniques were applied to a common data set of daily measurements of 11 elements in particulate matter (PM). Samples of PM were collected in the 5 yr period at an urban site located at the sea coast. In the vicinity of the sampling site traffic is a permanent but not significant anthropogenic source. In this study we used both the Unmix and PMF receptor models for evaluation of the sources contribution. Unmix found thirteen solutions for several combinations of species, but four solutions satisfy the criteria Min R2 > 0.8 and Min S/N > 2. Unmix identified three and four sources in satisfactory solutions. The PMF model has given 3 possible solutions and by further analysis the best solution of four sources was selected. F peak refinement enabled finding a more realistic solution that includes re-suspension and traffic as dominant source contributions. The results given in this study are in accordance with the results of Enrichment Factors analysis presented in our previous work.

D. Đorđević et al.

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D. Đorđević et al.

D. Đorđević et al.

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