Title: Source identification by a statistical analysis of backward trajectories based on peak pollution events
Authors: Rita Cesari; Paolo Paradisi; Paolo Allegrini
ISAC-CNR Sede di Lecce, Str. Prov. Lecce-Monteroni km 1200, 73100 Lecce, Italy
ISTI-CNR, via G. Moruzzi 1, 56124 Pisa, Italy
IFC-CNR, Via Moruzzi 1, 56124 Pisa, Italy; Centro EXTREME, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà 7, 56127 Pisa, Italy
Abstract: Back-trajectory techniques are extensively used to identify the most probable source locations, starting from the known pollutants concentration data at some receptor sites. In this paper, we review the trajectory statistical methods (TSMs) that are most used in literature for source identification, which are essentially based on the concept of residence time (RT), and we introduce a novel statistical method. To validate this method, artificial receptor data at two receptor sites are derived from numerical simulations with a given aerial source, using the Lagrangian dispersion model (LSM) FLEXPART in forward mode. Then the RTs are computed using again the model FLEXPART, but in backward mode. Then, the new statistical methodology, which is based on the use of peak concentration events, is applied to reconstruct the spatial distribution of emission sources. Our approach requires simulation times shorter than those required in other methods and could overcome the problem of ghost sources.
Keywords: trajectory statistical methods; backward trajectories; Lagrangian dispersion models; LSMs; environmental pollution; source identification; peak events; residence time analysis; air pollution; air quality; atmospheric dispersion modelling; numerical simulation.
Int. J. of Environment and Pollution, 2014 Vol.55, No.1/2/3/4, pp.94 - 103
Available online: 29 Nov 2014