Showing papers by "Mines ParisTech published in 2023"

Monitoring of atmospheric ammonia (NH3) in Auvergne-Rhône-Alpes region (France): comparison between satellite, ground-based observations, and simulations from a chemistry-transport model

Abstract: Atmospheric ammonia (NH3) is a gaseous precursor of secondary inorganic aerosols, which represent a significant part of concentrations of fine particulate matter PM2.5 measured in the French region Auvergne-Rhône-Alpes (AuRA). Although French State gives an objective for reducing territorial NH3 emissions, ammonia concentrations in ambient air are not regulated. Very few continuous measurement stations exist in France and cover a time range of a few years at most. Ammonia can also be monitored by satellite remote sensing, which offers a better spatial coverage over more than a decade.  Atmo Auvergne-Rhône-Alpes (Atmo AuRA) is a regional observatory of air quality approved by the French State. Atmo AuRA extends its activities to the use of satellite remote sensing data as an external source of information to test the consistency of its emission cadastres, air quality forecasts and hindcasts and potentially improve them.  Since 2015, Amo AuRA maintains a station in Lyon with an analyzer measuring continuously NH3 mixing ratios. The association also builds regional emission inventories of air pollutants, including NH3, and runs routinely CHIMERE chemistry-transport model to evaluate and forecast regional air quality. The chemistry-transport modeling can be used to simulate NH3 atmospheric content for given emissions from inventories and be compared with actual measurements.  In this study, we compare different datasets describing NH3 atmospheric content in AuRA region. Morning in situ measurements in Lyon are compared with NH3 level 2 data of total columns retrieved from the Infrared Atmospheric Sounding Interferometer (IASI), to evaluate their covariations on the period 2016-2021. The temporal consistency between ground measurements and simulations from CHIMERE is also investigated over the same period. Finally, a comparative analysis on CHIMERE and IASI data is done both in terms of spatial distribution and temporal evolution. 

Retrieval of surface solar irradiance from satellite using machine learning: pitfalls and perspectives

Abstract: Abstract. Knowledge of the solar surface irradiance (SSI) spatial and temporal characteristics is critical in many domains, the first of which is likely solar energy. While meteorological ground stations can provide accurate measurements of SSI locally, they are sparsely distributed worldwide. SSI estimations derived from satellite imagery are thus crucial to gain a finer understanding of the solar resource. To infer SSI from satellite images is, however, not straightforward and it has been the focus of many researchers in the past thirty to forty years. For long, the emphasis has been on empirical models (simple parameterization linking the reflectance to the clear-sky index) and on physical models. Recently, new satellite SSI retrieval methods are emerging, which directly infer the SSI from the satellite images using machine learning. Although only a few such works have been published, their practical efficiency has already been questioned. The objective of this paper is to better understand the potential and the pitfalls of this new coming family of methods. To do so, simple multi-layer-perceptron (MLP) models are constructed with different training datasets of satellite-based radiance measurements from Meteosat Second Generation (MSG) with collocated SSI ground measurements from Meteo-France. The performance of the models is evaluated on a test dataset independent from the training set both in space and time. We found that the data-driven model’s performance is very dependent on the training set. On the one hand, even a simple MLP can significantly outperform a state-of-the-art physical retrieval method, provided the training set is sufficiently large and similar enough to the test set. On the other hand, in certain configurations, the data-driven model can dramatically underperform even in stations located close to the training set.

Determination of upward/downward soil water fluxes using soil thermal profile series : two field case studies

Abstract: Water transfer through the unsaturated zone, in terms of upward or downward water fluxes, is a critical term for estimation of the water budget. As fluid flow modifies diffusive heat transfer through advective processes, since the early 90s several studies have attempted to deduce vertical water flow from soil temperature series. Likewise, if information on the water content profiles is known, bulk thermal properties can be inferred from thermal time series at different depths.In this study we compare two field sites in the Paris Basin Area, with two different types of soil and vegetation. We present our preliminary results from two approaches aiming at retrieving inferring soil bulk thermal parameters, namely heat capacity and conductivity, as well as vertical water flow.On the one hand, thermal measurements until a depth of 1.8 m have been carried out in a managed crop field. Using frequency decomposition of the thermal series, the upward and downward flows are determined. The water fluxes are compared with high-frequency EM time-lapse maps in an attempt to spatialize the variations.On the other hand, the thermal properties of a wetland area are inferred from soil thermal time series inversion using the thermo-hydrodynamic code suite Ginette, and are compared with spatial distribution of vegetation derived from remote sensing imagery.The two approaches are compared and discussed with their respective caveats and abilities.

Modelling the source of glacial earthquakes: numerical modelling of the response of a tide-water glacier to the capsize of an instable iceberg

Abstract: One current concern in Climate Sciences is the estimation of the annual amount of ice lost by glaciers and the corresponding rate of sea level rise. Greenland ice sheet contribution is significant with about 30% to the global ice mass losses. The processes that control ablation at tidewater glacier termini, glacier retreat and calving are complex, setting the limits to the estimation of dynamic mass loss and the relation to glacier dynamics. It involves interactions between bedrock – glacier – icebergs – ice-mélange – water – atmosphere. Moreover, the capsize of cubic kilometer scale icebergs close to a glacier front can destabilize the glacier, generate tsunami waves, and induce mixing of the water column which can impact both the local fauna and flora. We aim to improve the physical understanding of the response of glacier front to the force of a capsizing iceberg against the terminus. For this, we use a mechanical model of iceberg capsize against the mobile glacier interacting with the solid earth through a frictional contact and we constrain it with measured surface displacements and seismic waves that are recorded at teleseismic distances. Our strategy is to construct a solid dynamics model, using a finite element solver, involving a deformable glacier, basal contact and friction, and simplified iceberg-water interactions. We simulate the response of a visco-elastic near-grounded glacier to the capsize of an iceberg close to the terminus. The influence of the glacier geometry, the type of capsize, the ice properties and the basal friction on the glacier dynamic and the observed surface displacements are assessed. The surface displacements simulated with our model are then compared with measured displacements for well documented events. We show the surface and basal displacements of the glacier are significantly different in the case of to a top-out and a bottom-out (the two possible rotations) iceberg capsize.  This suggests different basal forces in both types of capsize, and thus probably a different signature in the seismic waves generated at the basal surface during capsize. To reproduce the vertical displacements of the glacier, our results suggest a higher hydrodynamic force on the glacier tongue than suggested in previous studies.

Thermal-Mechanical Fatigue (Including Thermal Shock)

Abstract: Components operating at high temperature are subjected to heating and cooling transients during start up and shut down operations or during regime changes. Repetition of these transients induced thermal fatigue (TF) due to constrained thermal strains. Primary stresses may superimpose on TF, which results in thermal-mechanical fatigue (TMF). This is usually a non-isothermal low-cycle fatigue process, which often involves inelastic strains in critical areas of components, and therefore, needs plastic or visco-plastic constitutive modeling. This article first describes the laboratory tests used to characterize the behavior and lifetime under TMF or TF loading: TMF tests on specimens without temperature gradient to check the predictions of constitutive models and lifetime models independently; thermal shock (TS) tests on simple structures to check the whole prediction chain. Experimental results and damage mechanisms are then reported for metallic alloys and coated systems (including thermal barrier coatings (TBC)). Oxidation and surface effects are then described, which can significantly influence TMF/TF damage mechanisms. Constitutive models are briefly described and compared with TMF test results. As components are mostly designed to crack initiation, crack initiation models are then presented, and some examples of application to the assessment of lifetime in components are shown. Crack growth modeling is briefly described. An overview of life prediction models against TMF is finally given.