Investigation of the geographical origins of PM10 based on long, medium and short-range air mass back-trajectories impacting Northern France during the period 2009-2013

Trajectory-based statistical models (TMs) are widely used to locate source areas responsible for atmospheric pollution at receptor sites. In order to study the influence of long, medium and short-range back-trajectories (BTs) on geographical sources location, an original approach was applied to daily PM10 concentrations measured for 5 years (2009-2013) at 12 receptor sites in the Hauts-de-France (HdF) region bounded on the south by the Paris megacity and on the north by the Benelux countries. The methodology used was based on two complementary TMs, Concentration Field (CF) and Potential Source Contribution Function (PSCF), and included several meaningful constraints in order to improve the spatial representativeness and the statistical significance of the potential source maps. The selection of BTs depending on the occurrence of scavenging precipitations (>1 mm h−1) during the transport of air masses and altitude limitations with respect to the planetary boundary layer height led to more realistic maps. The variability of the density of BT endpoints was accounted for by a weighting function which highlighted medium-distant yet recurring (e.g. Benelux and West of Germany) potential sources of PM10. Investigating the effect of short-range BTs (75% of endpoints within a radius of 500 km from the receptor sites) pointed out at nearby large conurbations (Lille and Paris areas). Comparing our potential source maps with European PM10 emission inventory maps as well as PM10 measurements at European background monitoring stations for similar periods confirmed our results for Central Europe, the Benelux and the East of Germany. This study showed how the combination of several receptor sites enables the determination of potential source areas impacting a whole region. It pointed out also that the fine-tuned parametrization of the CF and PSCF TMs may considerably help improving the knowledge on geographical location of sources related to long, medium and short-range BTs and could be easily implemented for other regions of interest.