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Yelva Roustan

Researcher at École des ponts ParisTech

Publications -  58
Citations -  1356

Yelva Roustan is an academic researcher from École des ponts ParisTech. The author has contributed to research in topics: Air quality index & Deposition (aerosol physics). The author has an hindex of 19, co-authored 50 publications receiving 1146 citations. Previous affiliations of Yelva Roustan include University of Paris & ParisTech.

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Identification of sensitive parameters in the modeling of SVOC reemission processes from soil to atmosphere.

TL;DR: A sensitivity analysis targeted on the 'reemission' output variable was conducted, including soil properties, partition coefficients and meteorological conditions, to identify the key parameters in reemission modeling and their effect on global modeling uncertainty.
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Modelling of the atmospheric dispersion of mercury emitted from the power sector in Poland

TL;DR: In this article, a chemical scheme devoted to mercury transformations in the atmosphere was implemented into the Polyphemus air quality system, which was then used to perform simulations for 2008 in two domains, namely over Europe and over Poland.
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Multimedia Modelling of the Exposure to Cadmium and Lead Released in the Atmosphere―Application to Industrial Releases in a Mediterranean Region and Uncertainty/Sensitivity Analysis

TL;DR: In this article, two advanced models that respectively simulate the transport of heavy metals in the atmosphere at continental and regional scale, as well as the transfer of contaminants in the air-soil-plant system, were used to study the potential accumulation of lead and cadmium in vegetables in a French region submitted to global and local industrial releases.
Posted ContentDOI

Quantification of the modelling uncertainties in atmospheric releasesource assessment and application to the reconstruction of theautumn 2017 Ruthenium 106 source

TL;DR: A posteriori distributions meant to identify the origin of the release, to assess the source term, to quantify the uncertainties associated to the observations and the model, as well as densities of the weights of the perturbed ensemble, are presented.
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Aerosol Plume Characterization From Multitemporal Hyperspectral Analysis

TL;DR: A multitemporal methodology to retrieve aerosol type, to map the aerosol concentration, and to quantify mass flow rate from airborne hyperspectral data is described in this paper, which is in a good agreement with in situ stack measurements and modeling.