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Unmanned Aerial Air Quality measurements: the potential for industrial fire plumes characterization with onboard low-cost sensor measurements

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Abstract

During an industrial fire, potentially hazardous substances may be released outside the site by atmospheric transfer. In order to characterize their potential impact, it is essential to gather data as quickly and reliably as possible on the consequences of the event on the environment and on the population. However, recent events related to the Lubrizol 2019 factory fire in Rouen have highlighted the difficulty in certain circumstances of listing the composition of fumes and knowing the mechanisms that contributed to their emission. These shortcomings taint the numerical models used to prioritize the fallout zones and thus distort the assessment of the impact of the fire on the environment and the health of the populations. The DESIHR project (Drones en Essaims pour la Surveillance de Sites Industriels à Hauts Risques), winner of an French National Research Agency grant, aims to develop innovative tools and methods based on the use of a fleet of autonomous drones to characterize in real-life situations the substances present in a fire plume as well as their emission and propagation conditions. The definition of the control laws governing the behaviour of each drone must in this context be based on real-time air quality information from sensors onboard each mobile vector. In order to limit the mass and the energy cost, low-cost sensors are among others considered in the DESIHR project. The objective of the work presented here is to address the potential for industrial fire plumes characterization with onboard low-cost sensor measurements in complex environments. On the basis of experiments carried out before the start of the project, it will address issues ranging from the selection of pollutants monitored and subsequent sensors to the use of data by drones, through the definition of innovative protocols for qualifying measurement performance based on real air matrices.
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Dates and versions

ineris-03892320 , version 1 (09-12-2022)

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  • HAL Id : ineris-03892320 , version 1

Cite

Brice Berthelot. Unmanned Aerial Air Quality measurements: the potential for industrial fire plumes characterization with onboard low-cost sensor measurements. Air Sensors International Conference (ASIC), UC Davis Air Quality Research Center, May 2022, Pasadena, United States. ⟨ineris-03892320⟩

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