Evaluation of aerosol sources at European high altitude background sites with trajectory statistical methods
Introduction
The temporal variability of atmospheric particulate matter (PM) concentrations at a monitoring site is highly related to the history of the air mass arriving at that site. Therefore numerous studies of atmospheric PM levels have applied trajectory statistical methods (TSM), which allow simultaneous computational treatment of air mass back-trajectories and of PM concentrations at one or several receptor points.
The analysis of a large number of back-trajectories of air masses arriving at receptor sites is a valuable tool for investigating the sources and origins of particulate matter at those sites. Subsequently, cluster analysis can be used to group trajectories into homogeneous groups, depending on direction and speed of transport (Dorling et al., 1992, Brankov et al., 1998, Salvador et al., 2008). Furthermore, the synoptic meteorological scenarios associated to each cluster can be extracted from the analysis and used to highlight the fluctuations of the aerosol load and composition at sites.
TSM also permit to identify geographical areas associated with very low and high concentrations of PM components. Thus, they can be interpreted as potential sink and source regions, or also as preferred air mass transport pathways (Stohl, 1998). Although they do not consider effects such as atmospheric dispersion, chemical conversion, or dry and wet deposition, TSM are easy to apply and powerful, identifying the relevant source regions and the air flow regimes which are associated with regional and large-scale air pollution transport. As discussed by Viana et al. (2008), receptor modelling techniques using back-trajectory analysis (alone and in combination with other receptor modelling) have been applied only by a relatively low number of research teams in Europe (Viana et al., 2008 and references therein). Because TSM holds great potential for identifying potential source regions of PM, these authors encouraged their use in PM source apportionment studies. The use of TSM deploying large trajectory ensembles can significantly reduce the trajectory uncertainty (random errors) generated by interpolation and truncation processes, low temporal or spatial resolution of wind data, or an inappropriate selection of the starting heights, and permits important improvements in the predictability of TSM (Stohl, 1998, Lupu and Maenhaut, 2002).
Cluster Analysis (CA) can be used to classify the air mass origins that arrive at a site, but CA does not provide any information on the geographical location of potential source regions. This information can be obtained by applying the Redistributed Concentration Field method (RCF) (Stohl, 1996). This technique has already been applied to locate potential source regions for PM components (Stohl, 1996, Salvador et al., 2007), acidic species in precipitation (Charron et al., 1998) or heavy metals (Han et al., 2004). Wotawa and Kröger (1999) successfully tested the ability of the RCF method to reproduce emission inventories of air pollutants.
On the basis of a 2-year aerosol data set obtained within the CARBOSOL European project (Present and Retrospective State of Organic Aerosol over Europe), many important issues related to sources of PM10 and PM2.5 (particles with aerodynamic size lower than 10 and 2.5 μm, respectively) have been discussed and evaluated (Legrand and Puxbaum, 2007). An important outcome of CARBOSOL was to provide a comprehensive data set on inorganic and carbonaceous aerosol constituents at rural and background sites in Europe (Pio et al., 2007). These data were discussed versus environmental conditions at sites (marine versus continental, rural versus forested, boundary layer versus free troposphere, and winter versus summer) for elemental and organic carbon (EC and OC), major inorganic ions (Pio et al., 2007) and some specific organic species such as C2-C5 dicarboxylic acids (Legrand et al., 2007) or levoglucosan (Puxbaum et al., 2007). A seasonal source apportionment of PM2.5 organic aerosol was also performed (Gelencsér et al., 2007). Current EMEP models have been used to simulate sulfate and OC (Simpson et al., 2007) and EC (Tsyro et al., 2007) concentrations over Europe and data were compared with observations made during CARBOSOL.
Up to now CARBOSOL data have not been examined in terms of source regions and transport pathways for the different aerosol fractions. Only Fagerli et al. (2007) performed source–receptor calculations with the EMEP model to allocate sulfate and ammonium sources at the top of the Alps with the aim to discuss their ice core records. TSM would nicely complement the dispersion modelling approach previously applied to the CARBOSOL data set.
In this work we have first applied a cluster analysis to classify the air mass origins that arrive at three continental background sites where the climatology of aerosol was established during CARBOSOL. Then, the meteorological scenarios associated to each cluster were extracted and their impact on particle concentrations and composition at sites evaluated. Finally, the redistributed concentration field method was also applied.
Section snippets
CARBOSOL sampling sites and data
In the framework of the CARBOSOL European project, atmospheric aerosol was continuously sampled for 2 years at 6 monitoring sites in Europe (Pio et al., 2007). Three of these sites are located in the centre of Europe (Fig. 1) and can be classified as natural continental background: Schauinsland-SIL in Germany (47°55′N, 07°54′E, 1205 m asl), Puy de Dôme-PDD in France (45°46′N, 02°57′E, 1450 m asl) and Sonnblick-SBO in Austria (47°03′N, 12°57′E, 3106 m asl). PDD and SIL are medium-elevation
Characterisation and seasonal evolution of the clusters
As seen in Fig. 2 the final cluster centers after the last iteration in the clustering procedure at SBO, PDD and SIL were quite similar, despite some minor cluster differences from one site to another. Zonal flows accounted for most of data at the 3 sites (46% at PDD, 50% at SIL and SBO). They correspond to fast westerly flows from the mid Atlantic Ocean (cluster 1), moderately fast southwesterly (cluster 2) and fast north-westerly flows (clusters 3). The fastest flows (cluster 1) more
Conclusions
In this work different trajectory statistical methods have been applied to describe the main air mass flow patterns over central Europe and interpret the levels of the aerosol chemical components recorded at three remote background sites in this area. Their main potential source areas have also been geographically identified. A clear seasonal pattern has been observed at the three sites. During summer the highest EC, OC, SO42−, K+ and 210Pb concentrations were associated with slow and moderate
Acknowledgements
This work was financed by the Spanish Ministry of Science and Innovation through the Acción Integrada HP2006-0034. The data from Schauinsland, Puy de Dôme and Sonnblick used in this study were obtained as part of project CARBOSOL (EVK2-2001-113), which was supported by the European Commission. ECMWF and NILU are acknowledged for providing the data sets and the FLEXTRA trajectories computed from Schauinsland and Puy de Dôme (www.nilu.no/trajectories/). The developers of the FLEXTRA model
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