Source apportionment of PM10 and PM2.5 in major urban Greek agglomerations using a hybrid source-receptor modeling process

G Argyropoulos; C Samara; E Diapouli; K Eleftheriadis; K Papaoikonomou; A Kungolos

doi:10.1016/j.scitotenv.2017.05.088

Source apportionment of PM₁₀ and PM_2.5 in major urban Greek agglomerations using a hybrid source-receptor modeling process

Sci Total Environ. 2017 Dec 1:601-602:906-917. doi: 10.1016/j.scitotenv.2017.05.088. Epub 2017 Jun 3.

Authors

G Argyropoulos¹, C Samara², E Diapouli³, K Eleftheriadis³, K Papaoikonomou⁴, A Kungolos⁴

Affiliations

¹ Environmental Pollution Control Laboratory, Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece. Electronic address: geoarg@chem.auth.gr.
² Environmental Pollution Control Laboratory, Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
³ National Centre of Scientific Research "Demokritos", Institute of Nuclear Technology and Radiation Protection, Environmental Research Laboratory, 15310 Ag. Paraskevi, Attiki, Greece.
⁴ Department of Planning and Regional Development, University of Thessaly, 38334 Volos, Greece.

PMID: 28582736
DOI: 10.1016/j.scitotenv.2017.05.088

Abstract

A hybrid source-receptor modeling process was assembled, to apportion and infer source locations of PM₁₀ and PM_2.5 in three heavily-impacted urban areas of Greece, during the warm period of 2011, and the cold period of 2012. The assembled process involved application of an advanced computational procedure, the so-called Robotic Chemical Mass Balance (RCMB) model. Source locations were inferred using two well-established probability functions: (a) the Conditional Probability Function (CPF), to correlate the output of RCMB with local wind directional data, and (b) the Potential Source Contribution Function (PSCF), to correlate the output of RCMB with 72h air-mass back-trajectories, arriving at the receptor sites, during sampling. Regarding CPF, a higher-level conditional probability function was defined as well, from the common locus of CPF sectors derived for neighboring receptor sites. With respect to PSCF, a non-parametric bootstrapping method was applied to discriminate the statistically significant values. RCMB modeling showed that resuspended dust is actually one of the main barriers for attaining the European Union (EU) limit values in Mediterranean urban agglomerations, where the drier climate favors build-up. The shift in the energy mix of Greece (caused by the economic recession) was also evidenced, since biomass burning was found to contribute more significantly to the sampling sites belonging to the coldest climatic zone, particularly during the cold period. The CPF analysis showed that short-range transport of anthropogenic emissions from urban traffic to urban background sites was very likely to have occurred, within all the examined urban agglomerations. The PSCF analysis confirmed that long-range transport of primary and/or secondary aerosols may indeed be possible, even from distances over 1000km away from study areas.

Keywords: Conditional Probability Field (CPF); Non-parametric bootstrapping; Particulate Matter; Potential Source Contribution Function (PSCF); Robotic Chemical Mass Balance (RCMB); Southeastern Europe.