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On a high-order shallow-water wave model with canonical non-local Hamiltonian structure
No full textInternational audienceWe derive and study a new family of non-local partial differential equations (PDEs) that model free-surface long gravity waves over a flat bottom. To derive the model equations we approximate the velocity potential as a series of vertical polynomials derived from the shallow-water expansion of the Dirichlet-to-Neumann problem in the Hamiltonian formulation of free-surface potential flow and invoke Luke's variational principle. The resulting evolution equations exhibit a non-local Hamiltonian structure being coupled with a system of linear elliptic spatial PDEs on the horizontal plane. A key advantage of this approach is that it directly yields canonical Hamiltonian equations, which are well-suited for numerical solutions using standard methods. This class of model equations offers high-order shallow-water approximations of the water-wave problem. It contains terms whose spatial derivatives are at most of order two, distinguishing it from asymptotic methods involving higher-order mixed spatio-temporal derivatives. We explore the first non-trivial member of this family, highlighting its connections to other mathematical models and emphasizing its practical utility. We then analyze and discuss its linear dispersive properties and demonstrate that it does not exhibit a specific type of instability known as wave-trough instability. Additionally, we demonstrate its effectiveness in simulating the long-distance steady propagation of strongly non-linear solitary waves and the head-on collision of two counter-propagating solitary waves. In the latter case, comparisons with experimental data confirm the model's ability to capture complex wave dynamics, including wave transformation in the presence of strong non-linearity and dispersion. The extension of this approach to accommodate variable bottom topography is briefly discussed
Subgroups of a free group with every growth rate
No full textFor every α ∈ [1, 2r -1], we show there exists a subgroup H < F_r whose growth rate is
Universal social welfare orderings and risk
No full textInternational audienceHow can social prospects be evaluated and compared when there may be a risk on i) the actual allocations that people will receive, ii) the existence of these future people, and iii) their preferences? This paper investigates this question, which can arise when considering policies, such as climate policy, that affect people who do not yet exist. We start from the observation that there is no social ordering that meets minimal requirements of fairness, social rationality, and respect for people's ex ante preferences. We explore three ways around this impossibility. First, if we drop the ex ante Pareto requirement, we can obtain fair ex post criteria that take an (arbitrary) expected utility of an equally-distributed equivalent level of well-being. Second, if the social ordering is not an expected utility, we can obtain fair ex ante criteria that evaluate uncertain individual prospects with a certaintyequivalent measure of well-being. Third, if we accept that interpersonal comparisons rely on VNM utility functions even in absence of risk, we can construct expected utility social orderings that satisfy of a version of Pareto ex ante
Livrable : Transports en commun, marche, vélo et micro-mobilité. Dix volets pour aménager des quartiers de gare du « quart d’heure » de la région Hauts-de-France, à l’échelle piétonnière et cyclable
No full textThe renewed interest in cycling and the rise of micromobility reflect a profound transformation in daily mobility practices, driven by a growing demand for intermodality. The research conducted highlights the key role of these diverse modal combinations with public transport networks, which emerge as an effective solution to the challenges of the first and last miles. Our estimates reveal a significant potential for modal shift from car use toward these intermodal practices. The challenge is twofold: to enhance the attractiveness of public transport while promoting more sustainable local travel. To this end, these ten pillars help to link urban planning and mobility by fostering a synergy between the development of a true ’cycling system’ and the planning transit-oriented areas. This deliverable aims to provide decision-makers, planners, and transport operators with tools to fully integrate cycling into station districts. This policy brief thus sets out ten strategic recommendations to create favorable conditions for intermodal practices and to encourage urban development that is both oriented toward public transport and supported by walking and cycling
Resources for a Safe and Resilient Europe: The Case for Minimum Taxation of Ultra-High-Net-Worth Individuals in the EU
No full textPublication parue dans la note EUTAX observatory mars 2025This policy note provides a revenue estimate of how much European Member States could raise with a minimum tax of 2% or 3% on the wealth of people owning more than €100 million or €1 billion in wealth – the scenarios considered in the report commissioned by the G20 presidency
Incertitudes et modélisation de la propagation des coûts indirect du changement climatique via les chaînes d'approvisionnement
No full textThis thesis examines the evaluation of indirect economic impacts from natural disasters, focusing on the uncertainties in modeling these impacts. Accurate assessment of indirect costs is crucial for effective risk management policies. However, the complexities of economic systems and reliance on diverse modeling assumptions necessitate a deeper understanding of the uncertainties involved. The thesis conducts an in-depth analysis of the Adaptive Regional Input-Output (ARIO) model, a hybrid approach combining Input-Output (10) and Agent-Based Modelling techniques. This research provides insights into key mechanisms driving indirect economic impacts and explores the ARIO model's reliability across various applications. Chapter 1 introduces the increasing risks associated with weather and climate-related disasters, emphasizing the importance of systemic risk evaluation that considers both direct and indirect economic impacts. Chapter 2 reviews methodologies for evaluating indirect costs, including econometric methods, 10 models, Computable General Equilibrium (CGE) models, and hybrid/Agent-Based Models (ABM), and discusses current challenges. Chapter 3 describes the ARIO model, central to this thesis, detailing its structure, behavior, hypotheses, and limitations, and introduces BoARIO, an open-source Python implementation developed during the thesis. Chapter 4 evaluates the ARIO model's robustness using a case study of the 2021 flooding in Germany, analyzing its sensitivity to various parameters and the influence of reconstruction demand on outcomes. lt highlights the importance of testing multiple configurations of economic data to ensure robustness. Chapter 5 assesses the ARIO model's reliability in evaluating indirect costs of river floods globally, using a dataset of modelled flood events for historical and future periods, and compares different recovery scenarios. lt emphasizes the need to explore various scenarios and parameters and examine sectoral and regional variations. Chapter 6 explores the cascading effects of multiple disasters, revealing that sequential events can amplify or mitigate impacts depending on economic conditions and model assumptions. Overall, the thesis highlights the ARIO model's sensitivity to parameter choices, reconstruction dynamics, and economic data, underscoring the need to evaluate multiple scenarios, parameters, and data sources for reliable conclusions. The ARIO model's ability to bridge simplicity and complexity makes it well-suited for exploratory studies, emphasizing the critical role of transparent and flexible modeling approaches in understanding indirect economic impacts and supporting robust disaster risk management strategies.Cette thèse examine l'évaluation des impacts économiques indirects des catastrophes naturelles, en mettant l'accent sur les incertitudes liées à la modélisation. L'évaluation des coûts indirects est essentielle pour concevoir des politiques efficaces de gestion des risques. Cependant, les complexités des systèmes économiques et la dépendance aux hypothèses de modélisation nécessitent d'évaluer les incertitudes associées. La thèse propose une analyse détaillée du modèle Adaptive Regional Input-Output (ARIO), explorant les mécanismes clés des impacts économiques indirects et évaluant la fiabilité du modèle dans divers contextes. Le Chapitre 1 introduit les risques croissants liés aux catastrophes météorologiques et climatiques, soulignant l'importance d'une évaluation systémique des risques. Le Chapitre 2 passe en revue les méthodologies d'évaluation des coûts indirects, incluant les méthodes économétriques, les modèles Input-Output, les modèles d'équilibre général et les modèles agents basés. Le Chapitre 3 décrit le modèle ARIO, détaillant sa structure, son fonctionnement, ses hypothèses et ses limites, et présente BoARIO, une implémentation open-source en Python. Le Chapitre 4 évalue la robustesse du modèle ARIO à travers une étude de cas sur les inondations de 2021 en Allemagne, analysant la sensibilité du modèle à différents paramètres et l'influence de la reconstruction. Le Chapitre 5 évalue le modèle ARIO pour estimer les coûts indirects à l'échelle mondiale, en comparant différents scénarios de reconstruction. Le Chapitre 6 explore les effets en cascade de catastrophes multiples, révélant que des événements successifs peuvent amplifier ou atténuer les impacts indirects selon les conditions économiques et les hypothèses de modélisation. En conclusion, la thèse met en évidence la sensibilité du modèle ARIO aux choix de modélisation et souligne la nécessité d'évaluer plusieurs scénarios, paramètres et sources de données pour tirer des conclusions robustes. Ce travail met en lumière le rôle crucial des approches de modélisation transparentes et flexibles dans l'amélioration de la compréhension des impacts économiques indirects et la mise en place de stratégies robustes de gestion des risques liés aux catastrophes naturelles
L'influence de différents supports cartographiques sur le traitement cognitif de l'espace-temps géographique : une étude empirique
No full textInternational audienceGeographers employ various techniques to represent the multiple dimensions of geographical time-space through maps. For example, precise cartographic transformations can be applied to distort spatial extents, enhancing the visualization of temporal distances. Some innovative cartographic representations, such as shrivelled maps, are specifically designed to depict time-space within transport networks where different speeds apply. Representing time-space in maps is a complex challenge, but it also raises questions about how such representations are interpreted and utilized by non-experts. In this study, we examined the impact of different geographic map formats on cognitive tasks requiring judgments of spatial distance or temporal duration in naïve participants. The behavioral results supported the hypothesis that different map formats exert distinct influences on the cognitive processes involved in these tasks. Additionally, the data suggested that shrivelled maps have the potential to facilitate the selection of optimal routes based on travel time, particularly in complex scenarios, given adequate training.Les géographes emploient diverses techniques pour représenter les multiples dimensions de l'espace-temps géographique sur des cartes. Par exemple, des transformations cartographiques précises peuvent être appliquées pour déformer les étendues spatiales, améliorant ainsi la visualisation des distances temporelles. Certaines représentations cartographiques innovantes, telles que les cartes ratatinées, sont spécifiquement conçues pour représenter l'espace-temps au sein des réseaux de transport où des vitesses différentes s'appliquent. La représentation de l'espace-temps sur les cartes est un défi complexe, mais elle soulève également des questions sur la manière dont ces représentations sont interprétées et utilisées par des non-spécialistes. Dans cette étude, nous avons examiné l'impact de différents formats de cartes géographiques sur des tâches cognitives nécessitant des jugements de distance spatiale ou de durée temporelle chez des participants naïfs. Les résultats comportementaux soutiennent l'hypothèse que les différents formats de cartes exercent des influences distinctes sur les processus cognitifs impliqués dans ces tâches. En outre, les données suggèrent que les cartes ratatinées ont le potentiel de faciliter la sélection d'itinéraires optimaux basés sur le temps de trajet, en particulier dans des scénarios complexes, sous réserve d'un entraînement au format adéquat
Building without income mixing: Public housing quotas in France
No full textWe study the effects of the SRU law introduced in France in December 2000 to support scattered development of public housing in cities and favor social mixity. This law imposes 20% of public dwellings to all medium and large municipalities of large-enough cities, with fees for those not abiding by the law. Using exhaustive fiscal data, we evaluate the effects of the law over the 1996-2008 period using a difference-in-differences approach at the municipality and neighborhood levels. We find that the law stimulated public housing construction in treated municipalities, but only slightly increased the presence of low-income households. Indeed, new public dwellings enter categories to which medium-income are eligible and most additional occupants are not poor. Within municipalities, the policy decreased public housing segregation but it barely decreased low-income segregation. This comes from local authorities increasing over time the presence of public dwellings in neighborhoods away from existing public housing but in places concentrating low-income households
Flooded with potential: urban drainage science as seen by early-career researchers
No full textInternational audienceThis opinion paper reflects on the current challenges facing urban drainage systems (UDS) research, along with solutions for fostering sustainable development. Over the course of a year-long project involving 92 participants aged 24–38, including PhD candidates, post-doctoral researchers, and early-career academics, we identified critical challenges and opportunities for the sustainable development of UDS. Our exploration highlights four key challenges: limited public visibility leading to resource constraints, insufficient collaboration across subfields, issues with data scarcity and data sharing, and geographical specificities. We emphasise the importance of raising public and political awareness regarding UDS's vital role in climate adaptation and urban resilience, advocating for blue-green infrastructure and open data practices. Additionally, we address systemic academic barriers that hinder innovative research. We call for a shift away from metrics that prioritise quantity over quality. We recommend establishing stable career pathways that empower early-career researchers. This paper aims to catalyse a broader community dialogue about the future of UDS research, uniting voices from various career stages. By presenting actionable recommendations, we aim to inspire fundamental changes in research conduct, evaluation, and sustainability, ensuring the field of UDS is prepared to meet pressing urban water management challenges worldwide
Population exposure to outdoor NO2, black carbon, and ultrafine and fine particles over Paris with multi-scale modelling down to the street scale
No full textInternational audienceThis study focuses on mapping the concentrations of pollutants of interest to health (NO2, black carbon (BC), PM2.5, and particle number concentration (PNC)) down to the street scale to represent the population exposure to outdoor concentrations at residences. Simulations are performed over the area of Greater Paris with the WRF-CHIMERE/MUNICH/SSH-aerosol chain, using either the top-down inventory EMEP or the bottom-up inventory Airparif, with correction of the traffic flow. The concentrations of the pollutants are higher in streets than in the regional-scale urban background, due to the strong influence of road traffic emissions locally. Model-to-observation comparisons were performed at urban background and traffic stations and evaluated using two performance criteria from the literature. For BC, harmonized equivalent BC (eBC) concentrations were estimated from concomitant measurements of eBC and elemental carbon. Using the bottom-up inventory with corrected road traffic flow, the strictest criteria are met for NO2, eBC, PM2.5, and PNC. Using the EMEP top-down inventory, the strictest criteria are also met for NO2, eBC, and PM2.5, but errors tend to be larger than with the bottom-up inventory for NO2, eBC, and PNC. Using the top-down inventory, the concentrations tend to be lower along the streets than those simulated using the bottom-up inventory, especially for NO2 concentrations, resulting in fewer urban heterogeneities. The impact of the size distribution of non-exhaust emissions was analysed at both regional and local scales, and it is higher in heavy-traffic streets. To assess exposure, a French database detailing the number of inhabitants in each building was used. The population-weighted concentration (PWC) was calculated by weighting populations by the outdoor concentrations to which they are exposed at the precise location of their home. An exposure scaling factor (ESF) was determined for each pollutant to estimate the ratio needed to correct urban background concentrations in order to assess exposure. The average ESF in Paris and the Paris ring road is higher than 1 for NO2, eBC, PM2.5, and PNC because the concentrations simulated at the local scale in streets are higher than those modelled at the regional scale. It indicates that the Parisian population exposure is underestimated using regional-scale concentrations. Although this underestimation is low for PM2.5, with an ESF of 1.04, it is very high for NO2 (1.26), eBC (between 1.22 and 1.24), and PNC (1.12). This shows that urban heterogeneities are important to be considered in order to represent the population exposure to NO2, eBC, and PNC but less so for PM2.5