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• The 80 km/h speed limit is associated with a significant reduction in fatalities. • Estimated benefits are between 300 and 350 lives saved. • Estimated effects vary between counties, illustrating the potential impact depending on the local context. • The dynamics of the measure evolve over time. Introduction : Speeding is considered to be a major contributor to road fatalities and injuries worldwide. Inappropriate speeding behavior is associated with a high casualty burden. It could be responsible for at least 30% of road accidents. Method : In 2018, the French authorities decided to introduce a new speed limit. They lowered the speed limit to 80 km/h on the unseparated interurban network. The aim was to reduce the number of fatalities and injuries and to implement some measures in line with international commitments. This paper uses different econometric models applied to time series for different groups of counties. Results : The results show a significant positive contribution of the new speed limit. The estimated number of lives saved is between 300 and 350. The overall reduction in the number of fatalities is 10%. The results also show a differentiated impact according to the local context and the different dynamics at play. Conclusions and Practical Applications : The results of this paper are in line with the scientific literature on speed limit reductions. They represent a validation of a debated public decision, while at the same time consolidating the body of knowledge on the subject, helping the decision-maker to adopt an appropriate measure to improve road safety performance. [ABSTRACT FROM AUTHOR]

A common task in today's transport simulation research is the assessment of on-demand mobility services on a large scale. A framework that is widely used for such tasks is MATSim, which has been applied frequently to study highly dynamic on-demand mobility services. To date, its efficient fleet management implementation does not yet support on-demand requests that are pre-booked in advance. This type of service, however, is seeing increased interest in the context of long-distance, rural, and inclusive mobility. Therefore, the present paper explores how prebooking can be integrated into MATSim and a use case for the city of Melun in France is presented. [ABSTRACT FROM AUTHOR]

In a context of massive renovation of residential buildings, stakeholders need decision-support models based on knowledge of the current building stock and accurate simulation of energy demand. This paper presents a new strategy for reducing energy consumption in the building sector, a key factor in combating climate change and promoting sustainability. We introduce an approach to (1) plan retrofits at community level, with a building resolution, for different years of an optimization period and (2) assist local authorities in selecting effective measures to improve the environmental performance of their building stock. The focus is on creating trajectory retrofit plans creation for a building stock with three main retrofit options: improving insulation, heating systems and hot water systems. We adapt a complex but linear approach, a type of problem-solving structure known as a multidimensional multiple-choice knapsack problem, which manages to handle a large number of possible retrofit combinations without becoming unwieldy. The planning process is streamlined as a single-objective optimization task that aims to reduce the total cost of retrofits by reducing their net present value. The efficiency of the model is demonstrated by simulating retrofit scenarios for 4,000 buildings in a French region to prove its ability to tackle large problems. France's targets for decarbonizing the residential sector are taken into account, with a target of reducing GHG emissions by a factor of 10 and a building stock consuming 80kWhEP/m2/year. The results show that these plans are feasible, but that they will require 50% of all buildings to undergo major renovation with abatement costs of around €200/tGES. Our practical application to an actual community demonstrates the model's ability to identify appropriate retrofitting measures and compile building data. • Development of an energy optimization framework integrating a linear simulation model. • Multi-stage optimization generalizing the knapsack problem for building renovation dynamics. • Bridging the gap in energy retrofit strategies by comparing decision-maker and model proposals. [ABSTRACT FROM AUTHOR]

There is a pressing need for a fast and efficient satellite remote sensing tool to estimate coastal bathymetry for any coastline in the world. To date, satellite methods for deriving bathymetry have mainly focused on linking the radiometric response to a known water depth, as with SPOT, Landsat and Sentinel. Here, wave properties (static and dynamic) are approximated using the small time delay between the different color bands of Sentinel-2 to then calculate a depth using wave linear dispersion theory. In this paper, we present a spatial correlation method within the S2Shores (Satellites to Shores) Python toolbox: a processing chain/toolbox of coastal observations using methods applied to optical satellites. The resulting individual bathymetries are finally qualified according to the standards of the International Hydrographic Organization, anticipating their operational use. • S2Shores spatial-correlation method for optical satellite coastal observations. • Bathymetry qualified with the International Hydrographic Organization standards. • Wave characteristics from the time delay between spectral bands of Sentinel-2. [ABSTRACT FROM AUTHOR]

This study focuses on assessing the effect of short- and long-term nonlinear deformation (plasticity and creep) on the thermo-hydro-mechanical (THM) responses of Callovo-Oxfordian (COx) claystone, considered as the host formation for the geological radioactive waste disposal in France, if it is licensed. The temperature increase due to heat emitted from the waste package induces a pore pressure rise in low permeability porous rocks such as the COx claystone, due to the difference in the thermal expansion coefficients between water and the argillaceous skeleton. This phenomenon has been evidenced by laboratory and in situ heating experiments. Recently, the key THM phenomena taking place around the high-level radioactive waste (HLW) repository based on the French concept, have been investigated using a thermoporoelasticity approach. In this paper, certain nonlinearities observed in the mechanical behaviour of the COx claystone have been considered in the evaluation of these THM processes. Three numerical simulations (thermoporoelastic, thermoporoelastoplastic and thermoporoelastoviscoplastic) are performed using Comsol Multiphysics code, in which the time-dependent behaviour of the COx is described by a power law whereas the elastoplastic behaviour is modelled by a strain hardening with a Hoek-Brown criterion and a non-associative flow rule. The role of elastoplastic and viscoplastic parts of deformations on the temperature, pore pressure and stresses time evolution in the far-field, is highlighted. • THM processes around a repository for HLW (high-level activity) radioactive waste based on the French concept. • Role of mechanical nonlinearities on the thermal pressurisation and their impacts on pore pressure and stress changes in the far field. • Competition between the thermal pressurisation and the creep mechanism on the variations of the pore pressure and the host rock integrity is highlighted. [ABSTRACT FROM AUTHOR]

• Half of parental transfer crowded out by the means-tested scholarship. • IV estimate using nonlinear schedule slightly higher (0.5) than OLS (0.4). • Larger estimated crowding-out effect under IV is driven by non-intact families. • Predictions of the altruistic model (full eviction) not validated. • Means-testing necessary to prevent a windfall effect for wealthy parents. This paper investigates the extent to which means-tested scholarships received by higher education students crowd out parental financial support at the intensive margin. We estimate a private transfer function using survey data collected in France in 2014 on a sample of students aged 18–24 who receive public scholarships. Introducing the amount of public transfer as an exogenous covariate, we find that one additional euro of scholarship is associated with a decrease in parental transfers of 0.40 euro. Using an instrumental variable strategy that exploits the non-linear schedule of the scholarship amount, we find a larger effect with a decrease of about 0.50. Our results suggest that a substantial part of the scholarship benefits low-income parents by reducing the amount of money they give to their student children. [Display omitted] [ABSTRACT FROM AUTHOR]

Proponents of short food supply chains (SFSC) have lauded their environmental benefits. Nevertheless, most studies on SFSCs have focused on their climate impact, while the synthetic pesticide use by farmers participating in SFSCs has received little research attention. In this study, we investigate the effect of farmers' involvement in different SFSC channels on synthetic pesticide use and crop yields. This study relies on data obtained from the 2020 French agricultural census and a 2018 French national survey on the phytosanitary practices of representative market gardeners. This paper uses a multinomial endogenous treatment effect model in order to account for endogeneity. We demonstrate that the effect of SFSC participation on farmers' synthetic pesticide use varies depending on the type of SFSC channel employed. Farmers who sell part of their vegetable crops through direct-to-consumer (DTC) channels use significantly fewer synthetic pesticides than those who only sell their crops through long food supply chains (LFSC). However, there is no evidence that farmers involved in direct-to-retailer (DTR) channels use significantly fewer synthetic pesticides. In addition, we have not found any evidence that SFSC participation decreases crop yields. [ABSTRACT FROM AUTHOR]

By implementing Principal Component Analysis (PCA) of multitemporal satellite data, this paper presents modeling solutions for air pollutant variation in three scenarios related to COVID-19 lockdown: pre, during, and after lockdown. Tropospheric NO 2 satellite data from Sentinel-5P was used. Two novel PCA-models were developed: Weighted Principal Component Analysis (WPCA) and Rescaled Principal Component Analysis (RPCA). Model results were tested for goodness-of-fit to empirical NO 2 data. The models were used to predict actual near-surface NO 2 concentrations. Model-predicted NO 2 concentrations were validated with NO 2 data acquired at ground monitoring stations. Besides, meteorological bias affecting NO 2 was assessed. It was found that the weather component had substantial impact on NO 2 built-ups, propitiating air pollutant decrease during lockdown and increase after. WPCA and RPCA models well fitted to observed NO 2. Both models accurately estimated near-surface NO 2 concentrations. Modeled NO 2 variation results evidenced the prolongated effect of the total lockdown (up to half a year). Model-predicted NO 2 concentrations were found to highly correlate with monitoring station NO 2 data collected on the ground. It is concluded that PCA is reliable in identifying and predicting air pollution variation patterns. The implementation of PCA is recommended when analyzing other pollutant gases. [Display omitted] • PCA is reliable for identifying and predicting air pollution variation. • WPCA and RPCA models well fitted observed NO 2. • Both models accurately estimated near-surface NO 2 concentrations. • Total lockdown had prolongated effect on NO 2 concentrations. • Weather conditions propitiated air pollutant decrease during lockdown and increase after. [ABSTRACT FROM AUTHOR]