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The Dependence of PM Size Distribution from Meteorology and Local-Regional Contributions, in Valencia (Spain) – A CWT Model Approach

Category: Air Pollution Modeling

Volume: 15 | Issue: 5 | Pages: 1979-1989
DOI: 10.4209/aaqr.2015.03.0162
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Konstantinos Dimitriou

  • Laboratory of Meteorology, Department of Physics, University of Ioannina, (null), Greece


Atmospheric stagnation conditions triggered the accumulation of PM2.5 and PM1.
Wind blown dust enhanced PMCOARSE concentrations mainly during warm seasons.
Vehicular PM emissions were emerged.
Extreme PM events of all size fractions matched with South-South West airflows.
Saharan dust PMCOARSE intrusions were clearly indicated.


This paper combines an analysis of hourly air pollution measurements and daily meteorological data with backward air mass trajectories, in order to elucidate local/regional sources and processes (e.g., atmospheric dispersion/stagnation, dust resuspension, etc.) defining PM levels and size distribution in Valencia (Spain). Four size fractions of PM (PM10, PMCOARSE = PM10–PM2.5, PM2.5 and PM1) were independently studied. No chemical/physical interactions among the four different size categories were assumed. Wind dispersion of PM2.5 and PM1 was indicated, whereas atmospheric stagnation conditions triggered the accumulation of fine particles, mainly produced from local combustion. Wind blown dust enhanced PMCOARSE concentrations, particularly throughout warm periods when dry land facilitates dust resuspension. Hourly air mass trajectory points were analyzed by Concentration Weighted Trajectory (CWT) model and Potential Source Contribution Function (PSCF) on a 0.5° × 0.5° resolution grid. The outcome of CWT model and PSCF identified Iberian Peninsula, France, North-West Africa and the Mediterranean as potential exogenous PM source areas. Extreme events of all PM fractions were primarily associated with the prevalence of South-South West airflows, whereas Saharan dust PMCOARSE intrusions also emerged. The availability of hourly meteorological data and the analysis of the chemical species included in PM mass could further clarify the findings of this paper and remove uncertainties.


PM10 PM2.5 PM1 Potential source contribution function Concentration weighted trajectory model

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