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PhD Defense

Delphy Rodriguez (LATMOS)

Title : Characterization of urban pollution in Parisian region by a synergy of surface measurements and high-resolution modelling

Date and time : The 24-06-2019 at 14h00

Type : thèse

Université qui délivre le diplôme : Sorbonne Université (spécialité Physique de l'Atmosphère)

Location : Sorbonne Universtié - Campus Jussieu - 4 place Jussieu - Paris - Salle de conférences IMPMC - Pièce 401 tour 23 4ème étage - couloir 22/23
Members of jury :

- François Ravetta (LATMOS, président)
- Bérengère Lebental (IFSTTAR, rapporteur)
- Cathy Liousse (Laboratoire d'Aérologie, rapporteur)
- Augustin Colette (INERIS, examinateur)
- Valérie Gros (LSCE, examinateur)
- Olivier Sanchez (Airparif, examinateur)
- Sébastien Payan (LATMOS, directeur)
- Myrto Valari (LMD, co-directeur)
- Laurence Eymard (LATMOS, invitée)
- Eric Parent (AgroParisTech, invité

Summary :

The harmful effects of air pollution need high-resolution concentration estimates. Ambient pollutant concentrations are routinely measured by surface monitoring sites of local agencies (Airparif in Paris, France). Such networks are not dense enough to represent the strong horizontal gradients of pollutant concentrations over urban areas. And, high-resolution models that simulate 3D pollutant concentration fields have a large spatial coverage but suffer from uncertainties. Those both information sources exploited independently are not able to estimate accurately human exposure. We suggest two approaches to solve this problem:

(1) direct pollution measurement by using low cost mobile sensors and reference instruments. A high variability across pollution levels is shown between microenvironments and also in the same room. Mobile
sensors should be deployed on a large scale due to their technical constraints. Reference instruments are very expensive, cumbersome, and can only be used occasionally.

(2) by combining local ground stations measurements with concentration fields of the Parallel Micro Swift Spray (PMSS) model at a horizontal resolution of 3 meters. We determined “representativeness areas” of stations - perimeter where concentrations are very close to the one of the station location – only from PMSS simulations.

Next, we developed a Bayesian model to extend the measured concentration of the monitoring sites within representativeness areas. Then, concentrations estimate at the Airparif monitors location and within
these areas is improved.

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