Abstract. The present study aims at identifying and apportioning fine aerosols to their major sources in Paris (France) – the second most populated "larger urban zone" in Europe – and determining their geographical origins. It is based on the daily chemical composition of PM2.5 examined over 1 year at an urban background site of Paris (Bressi et al., 2013). Positive matrix factorization (EPA PMF3.0) was used to identify and apportion fine aerosols to their sources; bootstrapping was performed to determine the adequate number of PMF factors, and statistics (root mean square error, coefficient of determination, etc.) were examined to better model PM2.5 mass and chemical components. Potential source contribution function (PSCF) and conditional probability function (CPF) allowed the geographical origins of the sources to be assessed; special attention was paid to implement suitable weighting functions. Seven factors, namely ammonium sulfate (A.S.)-rich factor, ammonium nitrate (A.N.)-rich factor, heavy oil combustion, road traffic, biomass burning, marine aerosols and metal industry, were identified; a detailed discussion of their chemical characteristics is reported. They contribute 27, 24, 17, 14, 12, 6 and 1% of PM2.5 mass (14.7 μg m−3) respectively on the annual average; their seasonal variability is discussed. The A.S.- and A.N.-rich factors have undergone mid- or long-range transport from continental Europe; heavy oil combustion mainly stems from northern France and the English Channel, whereas road traffic and biomass burning are primarily locally emitted. Therefore, on average more than half of PM2.5 mass measured in the city of Paris is due to mid- or long-range transport of secondary aerosols stemming from continental Europe, whereas local sources only contribute a quarter of the annual averaged mass. These results imply that fine-aerosol abatement policies conducted at the local scale may not be sufficient to notably reduce PM2.5 levels at urban background sites in Paris, suggesting instead more coordinated strategies amongst neighbouring countries. Similar conclusions might be drawn in other continental urban background sites given the transboundary nature of PM2.5 pollution.

No abstract

The present study was aimed at the identification, differentiation and characterization of red and white Cretan wines, which are described with Protected Geographical Indication (PGI), using ultraviolet–visible absorption spectroscopy. Specifically, the grape variety, the wine aging process and the role of barrel/container type were investigated. The combination of spectroscopic results with machine learning-based modelling demonstrated the use of absorption spectroscopy as a facile and low-cost technique in wine analysis. In this study, a clear discrimination among grape varieties was revealed. Moreover, a grouping of samples according to aging period and container type of maturation was accomplished, for the first time.