With about 12 years of experience in academic research, I am a research scientist in atmospheric physics and chemistry who focuses on air pollution. Along my career, I have worked in three well-recognized research institutions in France (LISA and LAREO) and Spain (BSC) on this topic through complementary points of view, using a large variety of data and methods. This has allowed me to acquire a broad and refined knowledge of the processes involved along with a good understanding of the most important challenges to be addressed.

With a PhD (2010-2014) in atmospheric chemistry and environmental physics conducted at the Laboratoire Inter-universitaire des Systèmes Atmosphériques (LISA; Créteil, France) under the supervision of Dr. Matthias Beekmann, I started my research career investigating multiple aspects of urban air pollution at the megacity scale by first focusing on Paris. My doctoral research was undertaken in collaboration with AIRPARIF, the local agency in charge of monitoring and forecasting air pollution in the Paris region. The main objectives were (1) to unravel the sources of fine particulate matter (PM_2.5) in Paris using a variety of in-situ observations collected along three complementary research campaigns (MEGAPOLI, PARTICULES, FRANCIPOL), and (2) to evaluate how well they are represented in the CHIMERE regional chemistry-transport model. In this frame, I investigated the chemical speciation, emissions, formation regime and regional transport of PM_2.5 in Paris.

Following my interest in understanding air pollution at larger scales with alternative observational datasets, I joined the French branch of the In-service Aircraft for a Global Observing System (IAGOS; formerly known as MOZAIC) European Research Infrastructure at Laboratoire d’Aérologie – Observatoire Midi-Pyrénées (LAERO-OMP; Toulouse, France) as a postdoctoral fellow (2014-2018) under the supervision of Dr. Valérie Thouret. IAGOS operates worldwide routine in-situ measurements of ozone (O₃) and carbon monoxide (CO) on-board a fleet of commercial aircraft since 1994. My postdoctoral research focused on analysing the O₃ and CO tropospheric vertical profiles obtained during take-off and landing phases above more than 300 worldwide metropolitan areas. From 2014 to 2018, I was involved in the first Tropospheric Ozone Assessment Report (TOAR-I) IGAC initiative that gathered about 240 international ozone experts, especially in the group in charge of providing an up-to-date scientific assessment of tropospheric O₃’s global distribution and trends.

In parallel to my work at LAERO-OMP, I progressively developed an interest in learning about new avenues and methods to better explore the growing amount of data available from models and observations. In this sense, I followed several intensive training courses on machine learning (ML) and artificial intelligence. This allowed me to obtain in 2018 a MSCA COFUND postdoctoral grant (STARS programme) at the BSC where I started a new research line in which I am exploring the use of statistical and machine learning approaches to improve our scientific knowledge and predictive capabilities in air quality. 

Interested in Earth Observation, I progressively start to work with satellite-based air quality products, first and foremost the high-resolution TROPOMI observations. Over the most recent years, a substantial part of my research is focusing on the tropospheric ozone and its NOx and VOC precursors over the Iberian Peninsula, combining the use of TROPOMI and in-situ surface observations with air quality modeling with our in-house MONARCH model. Since 2021, we are working in close colaboration with the Spanish ministry of environment (MITECO), within a consortium of several Spanish research institutions, on the design of the Spanish national ozone mitigation plan, in which we are responsible for the modeling part with MONARCH. In parallel, I am leading the MITIGATE RETOS Spanish national project focused on unraveling the ozone chemical regime over Spain using TROPOMI NO2 and HCHO observations. 

In 2022, I was granted the Ramon y Cajal (period 2023-2027) in the frame of which I am consolidating the aforementioned research line at BSC. 

• 11/2010 – 02/2014: Ph.D. in Atmospheric Physics and Chemistry, University of Paris Diderot (Paris, France), Laboratoire Inter-universitaire des Systèmes Atmosphériques (LISA, Créteil, France). Ph.D. dissertation title: Fine aerosol in a European megacity – Simulation of the sources (supervised by Dr. Matthias Beekmann).
• 09/2009 – 06/2010: M.Sc. in Atmospheric Physics and Chemistry, University of Paris Est Creteil (Créteil, France) and University of Paris Diderot (Paris, France)
• 09/2008 – 06/2009: M.Sc. in Mechanics and Fluid Dynamics, University of Science and Technology Lille 1 (Villeneuve d’Ascq, France)
• 09/2005 – 08/2008: Engineer diploma from Ecole Centrale de Lille, Junior and senior years of engineering studies at one of France’s top 15 Grandes Ecoles in Engineering at master’s level. Advanced Mechanics option, with specialization in Fluid Mechanics
• 09/2003 – 06/2005: Ecole Préparatoire aux Grandes Ecoles, Lycée Faidherbe (Lille, France). Advanced intensive two-year undergraduate studies preparing for the competitive entrance exam to the French Grandes Ecoles’s in engineering 

Most relevant on-going activities :

• MOSAQ (Model Output Statistics for Air Quality; Marie Sklodowska-Curie Actions Postdoctoral grant; 10/2018-09/2020) : Nowadays, air quality forecast are typically based on the use of chemistry-transport models. Given the persistent uncertainty sources affecting these models and their input data, the use of statistical methods for correcting the raw air quality forecasts taking benefit from the in-situ surface observations available can considerably improve our foreacsting capabilities. In this context, I am investigating a variety of statistical approaches for improving the air quality forecasts, including some innovative machine-learning techniques. Opened in the frame of a MSCA grant that ended in 2020, I keep coordinating this research line in the group.
• AQ-WATCH (Air Quality: Worldwide Analysis and forecasTing of Atmospheric Composition for Health; H2020 project; 01/2020-12/2023; https://www.aq-watch.eu/): The AQ-WATCH aims at designing Earth Observation downstream application in the field of air quality. In the frame of this project, I am developing an innovative machine-learning-based approach for estimating surface nitrogen dioxide (NO₂) concentrations based on satellite NO₂ observations from the last-generation TROPOMI sensor, and in-situ NO₂ surface observations, combined with a variety of ancillary data, including ERA5 meterological reanalysis from ECMWF, CAMSRA global air quality reanalysis from the Copernicus Atmospheric Monitoring Service (CAMS) and land-use data from the Copernicus Land Monitoring Service (CLMS). This product prototype is being currently tested in several regions, including Santiago de Chile region (Chile), Po valley (Italy), Mexico City (Mexico) and Catalonia (Spain). The long-term objective of this preliminary work is to develop our capabilities for continuous monitoring of surface air quality based on space-based observations.
• EARLY-ADAPT (ERC Consolidator Grant; 02/2021-01/2026) : Led by Joan Ballester from ISGlobal, the EARLY-ADAPT project aims to jointly analyse the environmental, socioeconomic and demographic drivers of recent trends in human health. In the frame of this project, we are collaborating with ISGlobal to investigate how to bias-correct the long-term CAMSRA reanalysis of the atmospheric composition over Europe, using the extensive network of air quality monitoring stations available. Based of a very detailed health database, this will allow Joan Ballester's team to investigate the associated health impacts of air pollution.
• MITIGATE (MonIToring and dIagnosinG ozone formATion from spacE; RETOS Spanish national project; 09/2021-08/2024): The chemical formation of tropospheric O₃ intrinsically depends on the availability of its nitrogen oxides (NOx) and volatile organic carbon (VOCs) precursors. While NOx surface observations are available at a number of monitoring stations, VOCs observations remain extremely scarce, which limits our ability to understand the formation of O₃. The MITIGATE project aims at taking advantage of the NO₂ and formaldehyde (HCHO) TROPOMI observations to investigate the formation of O₃ over Spain. We will make use of both NMMB-MONARCH simulations and machine-learning algorithms to better relate the information available through TROPOMI to the NOx-VOC sensitivity regimes prevailing at the surface. The long-term objective here is to strenghten our capacity of design observation-based effective emission control strategies over the country, which could bring large benefits for both human health and ecosystems.

Main research lines :

• Air Quality

Publications :