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Caractérisation des émissions de méthane à l'échelle locale à l'aide d'une méthode d'inversion statistique basée sur un modèle gaussien paramétré avec les données d'un gaz traceur

Abstract : The increase of atmospheric methane concentrations since the beginning of the industrial era is directly linked to anthropogenic activities. This increase is partly responsible for the enhancement of the greenhouse effect leading to a rise of Earth's surface temperatures and a degradation of air quality. There are still considerable uncertainties regarding methane emissions estimates from many sources at local scale. A better characterization of these sources would help the implementation of effective adaptation and mitigation policies to reduce these emissions.To do so, we have developed a new method to quantify methane emissions from local sites based on the combination of mobile atmospheric measurements, a Gaussian model and a statistical inversion. These atmospheric measurements are carried out within the framework of the tracer method, which consists in emitting a gas co-located with the methane source at a known flow. An estimate of methane emissions can be given by measuring the tracer and methane concentrations through the emission plume coming from the site. This method presents some limitations especially when several sources and/or extended sources can be found on the studied site. In these conditions, the colocation of the tracer and methane sources is difficult. The Gaussian model enables to take into account this bad collocation. It also gives a separate estimate of each source of a site when the classical tracer release method only gives an estimate of its total emissions. The statistical inversion enables to take into account the uncertainties associated with the model and the measurements.The method is based on the use of the measured tracer gas concentrations to choose the stability class of the Gaussian model that best represents the atmospheric conditions during the measurements. These tracer data are also used to parameterize the error associated with the measurements and the model in the statistical inversion. We first tested this new method with controlled emissions of tracer and methane. The tracer and methane sources were positioned in different configurations in order to better understand the contributions of this method compared to the traditional tracer method. These tests have demonstrated that the statistical inversion parameterized by the tracer gas data gives better estimates of methane emissions when the tracer and methane sources are not perfectly collocated or when there are several sources of methane.In a second time, I applied this method to two sites known for their methane emissions, namely a farm and a gas distribution facility. These measurements enabled us to test the applicability and robustness of the method under more complex methane source distribution conditions and gave us better estimates of the total methane emissions of these sites that take into account the location of the tracer regarding methane sources. Separate estimates of every source within the site are highly dependent on the meteorological conditions during the measurements. The analysis of the correlations on the posterior uncertainties between the different sources gives a diagnostic of the separability of the sources.Finally I focused on methane emissions associated with the waste sector. To do so, I carried out several measurement campaigns in landfills and wastewater treatment plants and I also used data collected on this type of sites during other projects. I selected the most suitable method to estimate methane emissions of each site and the obtained estimates for each one of these sites show the variability of methane emissions in the waste sector.
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Submitted on : Thursday, October 26, 2017 - 10:06:10 AM
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  • HAL Id : tel-01624241, version 1


Sébastien Ars. Caractérisation des émissions de méthane à l'échelle locale à l'aide d'une méthode d'inversion statistique basée sur un modèle gaussien paramétré avec les données d'un gaz traceur. Météorologie. Université Paris Saclay (COmUE), 2017. Français. ⟨NNT : 2017SACLV030⟩. ⟨tel-01624241⟩



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