Journal
ATMOSPHERIC ENVIRONMENT
Volume 94, Issue -, Pages 274-286Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2014.05.039
Keywords
PM2.5; Source apportionment; Receptor models; Chemical transport models
Funding
- European Program MED through the APICE grant
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Receptor and Chemical Transport Models are commonly used tools in source apportionment studies, even if different expertise is required. We describe an experiment using both approaches to apportion the PM2.5 (i.e., particulate matter with aerodynamic diameters below 2.5 mu m) sources in the city of Genoa (Italy). A sampling campaign was carried out to collect PM2.5 samples daily for approximately six month during 2011 in three sites. The subsequent compositional analyses included the speciation of elements, major ions and both organic and elemental carbon; these data produced a large database for receptor modelling through Positive Matrix Factorisation (PMF). In the same period, a meteorological and air quality modelling system was implemented based on the mesoscale numerical weather prediction model WRF and the chemical transport model CAMx to obtain meteorological and pollutant concentrations up to a resolution of 1.1 km. The source apportionment was evaluated by CAMx over the same period that was used for the monitoring campaign using the Particulate Source Apportionment Technology tool. Even if the source categorisations were changed (i.e., groups of time-correlated compounds in PMF vs. activity categories in CAMx), the PM2.5 source apportionment by PMF and CAMx produced comparable results. The different information provided by the two approaches (e.g., real-world factor profile by PMF and apportionment of a secondary aerosol by CAMx) was used jointly to elucidate the composition and origin of PM2.5 and to develop a more general methodology. When studying the primary and secondary components of PM, the main anthropogenic sources in the area were road transportation, energy production/industry and maritime emissions, accounting for 40%-50%, 20%-30% and 10%-15%, of PM2.5, respectively. (C) 2014 Elsevier Ltd. All rights reserved.
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