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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2018-6
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2018-6
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model description paper 09 Mar 2018

Model description paper | 09 Mar 2018

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This discussion paper is a preprint. A revision of the manuscript is under review for the journal Geoscientific Model Development (GMD).

Optimization of an Urban Monitoring Network for Retrieving an Unknown Point Source Emission

Hamza Kouichi1, Pierre Ngae1, Pramod Kumar1, Amir-Ali Feiz1, and Nadir Bekka1,2 Hamza Kouichi et al.
  • 1LMEE, Université d'Evry Val-d'Essonne, 40 Rue du Pelvoux 91020 Courcouronnes, France
  • 2LSA, Université Saad Dahlab-Blida, 09130 Blida, Algérie

Abstract. This study presents a methodology for the optimization of a monitoring network of sensors measuring the polluting substances in an urban environment with a view to estimate an unknown emission source. The methodology was presented by coupling the Simulated Annealing algorithm with the renormalization inversion technique and the Computational Fluid Dynamics (CFD) modeling approach. Performance of a network was analyzed by reconstructing the unknown continuous point emissions using the concentration measurements from the sensors in that optimized network. This approach was successfully applied and validated with 20 trials of the Mock Urban Setting Test (MUST) tracer field experiment in an urban-like environment. The optimal networks in the MUST urban region enabled to reduce the size of original network (40-sensors) to ~1/3rd (13-sensors) and to 1/4th (10-sensors). The 10 and 13 sensors optimal networks have estimated the averaged location errors of 19.20m and 17.42m, respectively, which are comparable to 14.62m from the original 40-sensors network. In 80% trials, emission rates with the 10 and 13 sensors networks were estimated within a factor of two which are also comparable to 75% from the original network. This study presents the first application of the renormalization data-assimilation approach for the optimal network design to estimate a continuous point source emission in an urban-like environment.

Hamza Kouichi et al.
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Hamza Kouichi et al.
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Latest update: 10 Dec 2018
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Short summary
Retrieval of an hazardous source (leak, terrorist attack, etc.) is an important operational issue for local authorities, health professionals, security and defense responsible, etc. As the issue is crucial, estimation of the source parameters must be precise. To ensure that, an established monitoring network must be optimal. This study presents a methodology for the optimization of a monitoring network of the sensors in an urban like environment with a view to estimate an unknown emission source.
Retrieval of an hazardous source (leak, terrorist attack, etc.) is an important operational...
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