Spatial variation of PM elemental composition between and within 20 European study areas - Results of the ESCAPE project

Publié le 1 Septembre 2015
Mis à jour le 5 juillet 2019

An increasing number of epidemiological studies suggest that adverse health effects of air pollution may be related to particulate matter (PM) composition, particularly trace metals. However, we lack comprehensive data on the spatial distribution of these elements. We measured PM2.5 and PM10 in twenty study areas across Europe in three seasonal two-week periods over a year using Harvard impactors and standardized protocols. In each area, we selected street (ST), urban (UB) and regional background (RB) sites (totaling 20) to characterize local spatial variability. Elemental composition was determined by energy-dispersive X-ray fluorescence analysis of all PM2.5 and PM10 filters. We selected a priori eight (Cu, Fe, K, Ni, S, Si, V, Zn) well-detected elements of health interest, which also roughly represented different sources including traffic, industry, ports, and wood burning. PM elemental composition varied greatly across Europe, indicating different regional influences. Average street to urban background ratios ranged from 0.90 (V) to 1.60 (Cu) for PM2.5 and from 0.93 (V) to 2.28 (Cu) for PM10. Our selected PM elements were variably correlated with the main pollutants (PM2.5, PM10, PM2.5 absorbance, NO2 and NOx) across Europe: in general, Cu and Fe in all size fractions were highly correlated (Pearson correlations above 0.75); Si and Zn in the coarse fractions were modestly correlated (between 0.5 and 0.75); and the remaining elements in the various size fractions had lower correlations (around 0.5 or below). This variability in correlation demonstrated the distinctly different spatial distributions of most of the elements. Variability of PM10_Cu and Fe was mostly due to within-study area differences (67% and 64% of overall variance, respectively) versus between-study area and exceeded that of most other traffic-related pollutants, including NO2 and soot, signaling the importance of non-tailpipe (e.g., brake wear) emissions in PM.

Auteur : Tsai MY, Hoek G, Eeftens M, de Hoogh K, Beelen R, Beregszaszi T, Cesaroni G, Cirach M, Cyrys J, de Nazelle A, de Vocht F, Ducret Stich R, Eriksen K, Galassi C, Grazuleviciene R, Grazulevicius T, Grivas G, Gryparis A, Heinrich J, Hoffmann B, Iakovides M, Keuken M, Kramer U, Kunzli N, Lanki T, Madsen C, Meliefste K, Merritt AS, Molter A, Mosler G, Nieuwenhuijsen MJ, Pershagen G, Phuleria H, Quass U, Ranzi A, Schaffner E, Sokhi R, Stempfelet M, Stephanou E, Sugiri D, Taimisto P, Tewis M, Udvardy O, Wang M, Brunekreef B
Environment international, 2015, vol. 84, p. 181-92