Elemental Composition and Light Absorbance of Ambient Fine Particles at 21 European Locations

We sampled fine particles (PM2.5) over a 1-year period at 21 central urban monitoring sites in 20 cities of the European Community Respiratory Health Survey (ECRHS). Particle filters were then analysed for elemental composition using energy dispersive X-ray fluorescence spectrometry and reflectance...

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Bibliographic Details
Main Authors: Gotschi T., Hazenkamp Von Arx M. E., Heinrich J., Burney P., Forsberg B., Jarvis D., Maldonado J., Norbck D., Stern W. B., Sunyer J., Torn K., Verlato G., Villani S., Kunzli N., BONO, Roberto
Other Authors: Hazenkamp-Von Arx M.E., Bono R., Stern W.B.
Format: Article in Journal/Newspaper
Language:English
Published: 2005
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Online Access:http://hdl.handle.net/2318/2430
Description
Summary:We sampled fine particles (PM2.5) over a 1-year period at 21 central urban monitoring sites in 20 cities of the European Community Respiratory Health Survey (ECRHS). Particle filters were then analysed for elemental composition using energy dispersive X-ray fluorescence spectrometry and reflectance (light absorption). Elemental analyses yielded valid results for 15 elements (Al, As, Br, Ca, Cl, Cu, Fe, K, Mn, Pb, S, Si, Ti, V, Zn). Annual and seasonal means of PM2.5, reflectance, and elements show a wide range across Europe with the lowest levels found in Iceland and up to 80 times higher concentrations in Northern Italy. This pattern holds for most of the air pollution indicators. The mass concentration of S did constitute the largest fraction of the analysed elements of PM2.5 in all locations. The crustal component varies from less than 10% up to 25% across these cities. Temporal correlations of daily values vary considerably from city to city, depending on the indicators compared. Nevertheless, correlations between estimates of long-term exposure, such as annual means, are generally high among indicators of PM2.5 from anthropogenic sources, such as S, metals, and reflectance. This highlights the difficulty to disentangle effects of specific sources or PM constituents in future health effect analyses using annual averages.