[Live radio] Recherche académique : indépendance TotalE

22/03/2023 19:00

Climat : la fin des saisons ?

15/03/2023 19:00

34e Journées Scientifiques de l’Environnement (JSE)

14/03/2023 19:00

Climate Change Isn’t Everything: Liberating Climate Politics from Alarmism

20/11/2024 14:00

Cycle de séminaires sur l’éthique et la responsabilité de l’engagement public des scientifiques.

Near-field pollutant dispersion in the urban environment

19/11/2024 15:00

Dr. Chao Lin is an Assistant Professor at the Institute of Industrial Science, The University of Tokyo. His primary focus is pollutant dispersion modeling in urban settings, utilizing computational fluid dynamics (CFD) tools and wind tunnel experiments to study complex pollutant behaviors around buildings.

Modelling sea ice dynamics and their interactions with the ocean

19/11/2024 11:00

Séminaire du LOCEAN.

Modélisation du potentiel oxydant des aérosols : un indicateur du risque sanitaire

21/05/2024 14:00

Le potentiel oxydant (PO) des aérosols est devenu un indicateur prometteur des effets néfastes des particules sur la santé, en complément de la masse des aérosols. En particulier, le PO est un indicateur du stress oxydant chez les organismes vivants et les êtres humains par la formation d’espèces réactives de l’oxygène.

Afin de fournir une cartographie de la variabilité spatiale et temporelle du PO en France, nous avons mis en place une stratégie pour simuler le potentiel oxydant volumique (POv) des particules dans le modèle de qualité de l’air de pointe CHIMERE sur l’ensemble du territoire français pour les années 2013 et 2014. Pour ce faire, un PO intrinsèque (POi) dérivé des mesures et spécifique à la source, déterminé par l’approche de modélisation des récepteurs par factorisation matricielle positive (PMF), est combiné aux sources de particules dans le modèle CHIMERE déterminées par une technique de taggage à l’émissions (PSAT).

Les résultats montrent un comportement satisfaisant des simulations CHIMERE par rapport aux observations d’aérosols (PM10) du réseau de qualité de l’air en France, ainsi qu’aux mesures de composition chimique effectuées sur plus de 10 sites de typologies différentes pendant deux années. En outre, une correspondance généralement satisfaisante entre la PMF et les combinaisons de sources de PM10 dérivées de la PSAT a pu être obtenue, comme l’indiquent les profils chimiques spécifiques de ces sources. Les valeurs de POv simulées par rapport aux valeurs observées ont montré des corrélations médianes allant de 0,35 à 0,60 et des biais fractionnels moyens allant de -0,3 à zéro, en fonction du test PO considéré (acide ascorbique AA, ou dithiothréitol DTT) et des sources de PM10 prises en compte (un ensemble réduit basé sur les métaux de transition et les espèces organiques contre un ensemble étendu prenant également en compte l’aérosol inorganique secondaire, la poussière et le sel de mer).

Pour l’ensemble étendu, la corrélation s’avère meilleure d’environ 0.1 à 0.15 pour les deux tests AA et DTT. Les champs de POv moyens sur deux ans obtenus montrent des zones d’intérêt majeur dans lesquelles le potentiel oxydant volumique est important, en particulier au niveau des grandes agglomérations urbaines, et également le long des autoroutes, et plus prononcés que les distributions de PM10 correspondantes. Ceci est dû à un POi élevé, en particulier pour les sources primaires telles que le trafic et la combustion de la biomasse. Ces effets sont plus marqués pour les essais AA que pour les essais DTT, ainsi que pour la méthode de l’ensemble réduit que celle de l’ensemble étendu.

Dans l’ensemble, grâce à la répartition des POv, ces résultats plaident en faveur d’une réduction accrue des émissions du transport routier et de la combustion de biomasse utilisée pour le chauffage dans les politiques de réduction de la pollution.

Relationship and feedback between LULC changes and hydroclimatic variability in Amazonia

06/05/2024 14:00

The Amazon rainforest plays a vital role by functioning as a regulator of the climate system, providing essential ecosystem services and acting as the main terrestrial carbon sink. It drives hydroclimatic processes and mitigates the effects of droughts through the strong coupling exerted between the soil, vegetation and the atmosphere. Indeed, forests operate as hydraulic pumps, absorbing and linking water stored in the soil with the atmosphere. Therefore, they have the potential to impact rainfall patterns through biophysical processes like water recycling. However, these capacities have been reduced during the last decades due to disturbances in the climate-vegetation system. The hydrological cycle has intensified, and extensive forest areas have been degraded. All this has accentuated a process of biophysical transition from a predominantly forested ecosystem to a Savanna. Therefore, given these complexities, understanding the direction of changes, the impacts and their interrelationships is of vital importance.

Using multiple datasets and a Land Surface Model coupled with a General Circulation Model, this thesis delves into the study of the interactions between Amazon hydroclimatology and vegetation. In addition, it seeks to expand our understanding of modifications in the vegetation-atmosphere system and its links with climate and Land Use and Land Cover (LULC) changes. Likewise, taking into account the increasing rates of deforestation, it investigates the effects and feedback resulting from a large-scale forest loss scenario on hydrological processes and water stress.
The results show that, over the southwestern Amazon, a little-explored region, forests undergo a transition from being influenced by energy availability to depending on water availability throughout the year. During the peak of the rainy season, vegetation growth is primarily influenced by energy availability rather than water availability. Nevertheless, outside of this period and for most of the year, forests respond positively to precipitation and terrestrial water storage, suggesting that vegetation is primarily dependent on water supply. However, a spatial analysis reveals that recent deforestation modifies these transitions and destabilizes the natural balance in the climate-vegetation system.

The nature of these imbalances in the Amazon is not entirely clarified. Through an approach based on the relationships of water fluxes, energy and vegetation conditions over the last four decades, it is explored whether these changes are intrinsic to climate variability or are driven by anthropogenic processes. 67% of the southwestern Amazon has experienced a transition towards a predominantly dry state due to climatic factors (external forcing), while 21% has transitioned towards a state dominated by deforestation (internal forcing). However, external and internal forcings are not independent processes, as both mechanisms drive changes simultaneously. By weighing the magnitudes of these forcings, we show that the synergies have led 74% of the southwestern Amazon toward a state of greater water stress. Nevertheless, during recent years, although combined external-internal processes continue to exert significant control over changes, 30% of these are strictly dominated by internal forcing. This suggests that internal processes are playing an increasingly relevant role in the transition towards a state characterized by high forest water stress, especially in areas where deforestation and anthropogenic pressure are increasing.

Using the land surface component (ORCHIDEE) coupled to the atmospheric component (LMDZ) of the IPSL Earth System Model, the effects of projected deforestation by 2050 on the terrestrial hydrological cycle and dryness of the Amazon region are examined. Deforestation decreases precipitation, reduces evapotranspiration and increases runoff. In addition, it drives an increase in the runoff coefficient and a significant decrease in moisture recycling, which results in a water deficit throughout the Amazon ecosystem. In fact, deforestation accentuates water stress especially in the southwestern Amazon (positive feedback). Water demands in the atmosphere, on the land surface and even in the soil root zone intensify during the dry season. During the wet season, the deficit of specific atmospheric humidity becomes even more acute towards the tropical Andes over the Altiplano region. These findings provide a more thorough understanding of the possible effects of massive forest removal on the water availability and resilience of the Amazon in a context where changes are occurring at an accelerated rate.

Sea-level rise and coastal risks: marine flooding and coastal erosion

23/05/2024 14:00

Coastal hazards such as flooding, erosion and salinization are a major concern for coastal zones management. In fact, projections suggest that by the middle of the 21st century, approximately 1 billion persons will be exposed to these hazards globally due to ongoing sea-level rise and coastal development. Confronted with this challenge, coastal managers and researchers are asking the same questions: (1) are we already able to attribute specific coastal impacts to sea-level rise? (2) how, where and when should climate change and sea-level rise impacts materialize? Responding to these two questions is generally difficult due to the limited accuracy of coastal hazard and risk models. This leads to a third question: how can we evaluate and manage uncertainties in sea-level rise and coastal impact projections?

Within my research, together with many colleagues, I adapted, developed and applied methods to address these three questions. This includes approaches to detect and eventually attribute impacts of sea-level rise as well as probabilistic methods to propagate uncertainties from coastal forcing (such as sea levels, waves and surges) to coastal impacts such as flooding and erosion. Yet, probabilistic approaches have a limited ability to capture future coastal risks because the probability of an early ice-sheet collapse during the late 21^st century or early 22^nd century is unknown. To model this deep uncertainty, we proposed to go beyond the use of single probabilistic distributions and use extraprobabilitic approaches to represent future sea-level changes and propagate them across coastal impacts models and eventually support some coastal adaptation decisions.

Over the coming years, it is clear that present-day and future coastal risk assessments will become more precise, or at least that the assumptions of these models will be clearly set out. For example, the CoCliCo project, which I am coordinating, aims at developing such broad-scale projections of coastal flooding in Europe. However, by limiting ourselves to delivering information on future risks without assessing critically adaptation options, we may be missing the most important aspect of adaptation. Indeed, the challenge in coastal zones is not limited to protecting against coastal hazards and sea-level rise. It rather consists in achieving what the IPCC calls climate resilient development, that is, mitigating climate change, adapting to committed impacts of climate change, reducing biodiversity losses and achieving the 17 sustainable development goals adopted by United Nation members in 2015. As part of my future research projects, I propose to contribute exploring pathways toward coastal resilient development.