1. Inverting time dependent concentration signals to estimate pollutant emissions in case of accidental or deliberate release
- Author
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Lionel Soulhac, Patrick Armand, Pietro Salizzoni, Nabil Ben Salem, Laboratoire de Mecanique des Fluides et d'Acoustique (LMFA), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), DAM Île-de-France (DAM/DIF), Direction des Applications Militaires (DAM), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)
- Subjects
Pollutant ,010504 meteorology & atmospheric sciences ,Meteorology ,Pollutant emissions ,Inverse ,Inversion (meteorology) ,Deliberate release ,Mechanics ,010501 environmental sciences ,Management, Monitoring, Policy and Law ,Atmospheric dispersion modeling ,01 natural sciences ,Pollution ,[SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph] ,Boundary layer ,13. Climate action ,Environmental science ,Waste Management and Disposal ,ComputingMilieux_MISCELLANEOUS ,0105 earth and related environmental sciences ,Wind tunnel - Abstract
We test the reliability of an inverse model to estimate the amount of mass released instantaneously by a source of pollutant in a turbulent boundary layer. To that purpose we use wind tunnel experiments simulating the dispersion of puffs due to the impulsive release of pollutant. For each of these emissions we recorded time dependent signals at fixed receptors. These single signals have been used as input data for an inverse dispersion model in order to evaluate its error in estimating the real emission of pollutant. The inversion has been also performed using the ensemble average of the 100 signals as input data. The comparison of both approaches allows us to discuss the reliability of an atmospheric dispersion inverse model in real situations.
- Published
- 2014
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