A trajectory statistical method for the identification of sources associated with concentration peak events (Contributo in atti di convegno)

Type

• Prodotto della ricerca (Classe)
• Contributo in atti di convegno (Classe)

Label

• A trajectory statistical method for the identification of sources associated with concentration peak events (Contributo in atti di convegno) (literal)

Anno

• 2013-01-01T00:00:00+01:00 (literal)

Alternative label

• Cesari R., Paradisi P., Allegrini P. (2013)
  A trajectory statistical method for the identification of sources associated with concentration peak events
  in HARMO 15 - 15th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, Madrid, Spain, 6-9 May 2013
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Cesari R., Paradisi P., Allegrini P. (literal)

Note

• PuMa (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• CNR-ISAC, Lecce, Italy; CNR-ISTI, Pisa, Italy; CNR-IFC, Pisa, Italy (literal)

Titolo

• A trajectory statistical method for the identification of sources associated with concentration peak events (literal)

Abstract

• We briefly review the Trajectory Statistical Methods (TSMs) most used in literature for source identification, essentially based on the concept of Residence Time. Then, we introduce a statistical methodology that, starting from the Concentration Field method, takes into account only the peak values in the concentration time series measured at multiple receptor sites. We use virtual simulations to evaluate the performance of our approach. In order to derive concentration time series at multiple receptors, the Lagrangian Dispersion Model (LSM) FLEXPART is used, in the time forward mode, to simulate dispersion from a known emission source. Then, virtual concentration data are available in the receptor sites. As in many TSMs, Residence Times need to be computed and, to this goal, we use FLEXPART, but in the backward mode, that is, FLEXPART is applied to compute the backward trajectories from the receptor sites. Then, our proposed statistical method is applied to the computed Residence Times and to the concentration data to reconstruct the spatial distribution of emission sources. The numerical results show that our approach could overcome the problem of ghost sources. Further, the proposed method requires simulation times shorter that those required in other methods, since it makes use of a relatively small set of trajectories. This could be of some interest in the characterization of impact studies and local climatic scenarios. (literal)

Prodotto di

• Institute of atmospheric sciences and climate (ISAC) (Istituto)
• Elaborazione di segnali e immagini per impieghi diagnostici e interpretazione di immagini multisorgente (ICT.P10.012.001) (Modulo)
• Istituto di fisiologia clinica (IFC) (Istituto)
• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)

Autore CNR

• RITA CESARI (Persona)
• PAOLO ALLEGRINI (Unità di personale esterno)
• PAOLO PARADISI (Persona)

Insieme di parole chiave

• Parole chiave di "A trajectory statistical method for the identification of sources associated with concentration peak events" (Insieme di parole chiave)

Incoming links:

Prodotto

• Institute of atmospheric sciences and climate (ISAC) (Istituto)
• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)
• Istituto di fisiologia clinica (IFC) (Istituto)
• Elaborazione di segnali e immagini per impieghi diagnostici e interpretazione di immagini multisorgente (ICT.P10.012.001) (Modulo)

Autore CNR di

• PAOLO PARADISI (Persona)
• RITA CESARI (Persona)
• PAOLO ALLEGRINI (Unità di personale esterno)

Insieme di parole chiave di

• Parole chiave di "A trajectory statistical method for the identification of sources associated with concentration peak events" (Insieme di parole chiave)