I DENTIFICATION OF LONG - RANGE TRANSPORT OF AEROSOLS OVER A USTRIA USING EARLINET LIDAR MEASUREMENTS

The aims of the study is to identify the paths of the long-range transported aerosols over Austria and their potential origin, and to estimate their properties, using lidar measurements from EARLINET stations closest to Austria from Germany and Romania and aerosol transport models. As of now, there is no lidar station in Austria. The study is part of a project to estimate the usefulness of a lidar station located in Vienna, Austria.


INTRODUCTION
Aerosols are produced locally, with given properties; they are then transported over short-to long-distances, usually in turbulent movements. Transport and dispersion of aerosols depend on aerosols' properties, on meteorological conditions, and on surface properties. During transport, aerosols can also mix with other atmospheric, so more sources contribute to the aerosol budget in a given place.
Lidar systems are useful tools to determine the properties of long-range transported aerosols and their vertical distribution [1][2][3]. EARLINET [4], a network of lidar systems with stations distributed over Europe, provides comprehensive groundbased lidar data for aerosol vertical distribution as well as aerosols' optical and microphysics properties, allowing a detailed study of long-range transported aerosols in Europe.
To identify the source regions of aerosols, a statistical analysis of back-trajectories can be performed. The back-trajectories analysis relates the aerosol mass loading changes at a receptor location to spatially-fixed sources, identifying the sources by a source -receptor matrix calculation [5].
Due to its geographical position in Central Europe, Austria is affected mainly by local and long-range transport of aerosols from variable sources. Marine aerosols with sea-salt particles content are rarely observed above Austria, as the nearest sea, Adriatic Sea, is located at a distance of few hundred kilometers, so aerosols measured in Austria are predominantly continental aerosol.
The purpose of this analysis is to study the longrange transport of aerosols over Austria, assuming a receptor site at Vienna. The study is based on cluster analysis, using measurements from EARLINET lidar stations closest to Austria, MACC reanalysis data [6] and the FLEXPART aerosol dispersion model [7].

METHODOLOGY
The analysis has been performed for Vienna (48.21°N, 16.36°E) as receptor site, using data from the period March -May 2014. This period has been reported of Austria as "seventh warmest spring (March -May) in its 247-year period of record, at 1.5°C higher than the 1981-2010 average" [8] The vertical distributions of aerosols over Vienna were obtained from MACC reanalysis data related to dust aerosol and smoke. Here, smoke was considered a mixture of organic mater, sulphate and black carbon.
The contribution of the different aerosol sources was evaluated comparing the spatial distribution of the layers as determined from the lidar measurements with the FLEXPART forward and backward simulations for each observed aerosol layers. From the lidar measurements, the aerosol layers were calculated using a wavelet analyses applied on the derivative of back-scattering coefficients. The transport of aerosols (dust or smoke) and the source-receptor sensitivity were calculated with the FLEXPART model using 6hourly GFS meteorological data interleaved with operational forecasts every 3 hours. The model was run for 7 days using a backward simulation with a tracer released within a volume estimated from lidar measurements and MACC observations, where no lidar measurements were available (at receptor site). The tracer release period ranges were taken of the order of two hours when estimated from lidar measurements, and from one to three days when estimated from MACC observations.
The types of the aerosols in Vienna were estimated from the analysis of the aerosol layer optical properties obtained from lidar measurements, correlating the layers at the lidar stations with the FLEXPART transport layers in the cluster analysis.
The regions of the potential aerosol sources were taken from NASA Fire Information for Resource Management System (FIRMS) maps [9] for fire investigation, and Barcelona Supercomputer Center regional dust forecast model -BSC-DREAM8b [10], for dust investigation over Europe.

RESULTS
For all cases, the cluster analysis was performed for two levels: 850 hPa (aprox. 1200 m) and 750 hPa (aprox. 3000 m)  The dates selected and the altitudes for Vienna and the considered lidar stations measurements for this case are shown in Table 1. For the lidar stations, the first altitude is obtained from FLEXPART at the station coordinates, while the second altitude is obtained from the lidar measurements.    For this case, a single cluster was identified for each of the two levels, 850 hPa and 700 hPa passing over Leipzig station. Table 3 shows the results obtained for this case. From the optical properties obtained from the lidar measurements, it results that the Case 1 is a mixture between dust and smoke particles. This mixture could be possible due to the same transport pathway for both sources, from North America over West Sahara. The threedimensional structure of the aerosol distribution revealed by the lidar systems, combined with MACC observations and the three-dimensional structure of the aerosol plume from FLEXPART aerosol transport model (see Figs. 8 and 9) confirm the presence of the two different components, smoke and dust coming from the two aerosol sources : smoke from North America (see Fig 10) and dust from Sahara (see Fig. 11). Case 2 and case 3 are Saharan dust intrusions over Europe.

CONCLUSIONS
This study of aerosols over Austria, based on a cluster analysis of aerosol layers determined from lidar measurements correlated with layers from the FLEXPART model revealed an influence of long-range transport (combined or alternated) of Saharan dust and aerosols emissions of wildfires from North America. Two cases of dust and one case of mixture of dust from Sahara and smoke from biomass burning from American wildfire were identified for the period analyzed, Spring 2014.