Receptor modelling techniques are widely used in order to identify the main natural and anthropogenic processes driving aerosol levels at a receptor. In this work, Positive Matrix Factorization (PMF) was used to apportion PM2.5 levels at a traffic site (Msida) located in a coastal town. 180 filters collected throughout a yearly sampling campaign conducted in 2016, were chemically characterized by light absorbance analysis, x-ray fluorescence and ion chromatography in order to determine the concentrations of black carbon, 17 elements and 5 ions, respectively. The resulting chemical data base was used in conjunction with PMF in order to identify the 7 components affecting the PM2.5 levels at the receptor site. Six of these sources are considered to be typical of the atmospheric composition of coastal traffic sites: traffic (27.3%), ammonium sulfate (23.6%), Saharan dust (15%), aged sea salt (12.7%), shipping (5%) and fresh sea salt (4.6%). This is the first time that such a study was carried out in Malta and helps in understanding the aerosol pollution climate of the Central Mediterranean, which is still relatively understudied when compared to the Eastern and Western Mediterranean. Furthermore, we have isolated a factor exclusive to Malta: the fireworks component, which is responsible for 2.9% of the PM2.5 and which has health implications due to its chemical composition. The results of this work should also serve to guide the policy makers in achieving the necessary emission reductions in order to achieve the WHO guideline for PM2.5 by 2020.
Keywords: Anthropogenic aerosol sources; Central mediterranean; Natural aerosol sources; PM(2.5); Positive matrix factorization; Source apportionment.
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