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Discussion papers | Copyright
https://doi.org/10.5194/amt-2018-260
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 20 Aug 2018

Research article | 20 Aug 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

Optical thickness matching algorithm applied to the case study of an accidental fire smoke plume over the Paris area with N2-Raman lidar

Xiaoxia Shang1,a, Patrick Chazette1, and Julien Totems1 Xiaoxia Shang et al.
  • 1Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Institut Pierre Simon Laplace (IPSL), CEA-CNRSUVSQ, UMR 8212, Gif-sur-Yvette, France
  • anow at: Finnish Meteorological Institute, P.O. Box 1627, 70211, Kuopio, Finland

Abstract. A smoke plume, coming from an accidental fire in a textile warehouse in the north of Paris, covered a significant part of the Paris area on 17 April 2015 and seriously impacted the visibility over the megalopolis. This exceptional event was sampled with an automatic N2-Raman lidar, which operated 15km south of Paris. The industrial pollution episode was concomitant with a long-range transport of dust aerosols raised from Sahara, and with the presence of an extended stratus cloud cover. The analysis of the ground-based lidar profiles therefore required the development of an original inversion algorithm, using a top-down aerosol optical thickness matching (TDAM) approach. This study is, to the best of our knowledge, the first lidar measurement of an accidental fire smoke plume. Vertical profiles of the aerosol extinction coefficient, depolarization and lidar ratio are derived to optically characterize the aerosols that form the plume. We found a lidar ratio close to 50±10sr for this fire smoke aerosol layer. The particle depolarization ratio is low, ~1±0.1%, suggesting the presence of spherical particles and therefore highly hydrated aerosols in that layer. A Monte Carlo algorithm was used to assess the uncertainties on the optical parameters, and to evaluate the TDAM algorithm.

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Latest update: 18 Sep 2018
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Short summary
For the first time, a ground based N2-Raman lidar sampled smoke plumes originating from a large accidental warehouse fire in the Paris area. We developed a new algorithm, dubbed top-down aerosol optical thickness matching, to characterize the optical properties of the smoke aerosols, without a pre-determined reference zone and in presence of clouds. The industrial pollution episode was concomitant with a long-range transport of dust aerosols, and with the presence of an extended stratus cloud.
For the first time, a ground based N2-Raman lidar sampled smoke plumes originating from a large...
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