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Pollution source identification using a coupled diffusion model with a genetic algorithm

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  • Khlaifi, Anis
  • Ionescu, Anda
  • Candau, Yves

Abstract

A new approach for the source quantification has been developed on the basis of real air pollutant hourly concentrations of SO2, measured by three monitoring stations, during 9h, around a group of three industrial sources. This inverse problem has been solved by coupling a direct model of diffusion (Pasquill’s Gaussian model) with a genetic algorithm, to search solutions leading to a minimum error between model outputs and measurements. The inversion performance depends on the relationship between the wind field and the configuration sources–receptors: good results are obtained when the monitoring stations are downwind from the sources, and in these cases, the order of magnitude of emissions is retrieved, sometimes with less than 10% error for at least two sources; there are some configurations (wind direction versus source and receptor locations) which do not permit to restore emissions. The latter situations reveal the need to conceive a specific network of sensors, taking into account the source locations and the most frequent weather patterns.

Suggested Citation

  • Khlaifi, Anis & Ionescu, Anda & Candau, Yves, 2009. "Pollution source identification using a coupled diffusion model with a genetic algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(12), pages 3500-3510.
    • Handle: RePEc:eee:matcom:v:79:y:2009:i:12:p:3500-3510
    DOI: 10.1016/j.matcom.2009.04.020
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    Cited by:

    1. Qin, Rui & Liu, Yan-Kui, 2010. "Modeling data envelopment analysis by chance method in hybrid uncertain environments," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(5), pages 922-950.
    2. Maciel, Leandro & Gomide, Fernando & Ballini, Rosangela, 2016. "A differential evolution algorithm for yield curve estimation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 129(C), pages 10-30.
    3. Yu Li & Jinggang Chu & Guozhen Wei & Sifan Jin & Tiantian Yang & Bo Li, 2021. "Robust Placement of Water Quality Sensor for Long-Distance Water Transfer Projects Based on Multi-Objective Optimization and Uncertainty Analysis," Sustainability, MDPI, vol. 13(4), pages 1-15, February.

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