Source identification by a statistical analysis of backward trajectories based on peak pollution events

Cesari R, Paradisi P, Allegrini P

Waste Management and Disposal  Trajectory-based statistical methods  Environmental pollution  G.3 PROBABILITY AND STATISTICS  Management  I.6.4 SIMULATION AND MODELING. Model Validation and Analysis  Policy and Law  Pollution  Source identification  Backward trajectories  J.2 PHYSICAL SCIENCES AND ENGINEERING  Lagrangian dispersion models  Monitoring 

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.

Source: INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION, vol. 55 (issue 1-4), pp. 94-103

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