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The Environmental Displacement Dataset (EnDis) quantifies human movement in response to sudden-onset natural hazards, including floods, storms, wildfires, landslides, earthquakes, and volcanic activity.

Le Meillour & Sinet-Mathiot et al. 2024 Increasing sustainability in palaeoproteomics by optimizing digestion times for large-scale archaeological bone analyses DOI: 10.1016/j.isci.2024.109432 MALDI-ToF MS data (raw data: mzML files, merged spectra: msd files) used for the ZooMS analysis of the bone material from Baishiya Karst Cave (China) and La Draga (Spain), along with the R codes for merging triplicates into one msd file. 

Originally developed and validated at the Cabauw (Netherlands) topographically flat onshore location, the alpha-I wind resource extrapolating method was tested at the FINO3 offshore site in the North Sea (Germany). The aim was to prove its validity also when applied over a substantially different environment in terms of surface characteristics and stability conditions. Data from local mast at 30, 80, and 100 m were used, with extrapolations to 80-m and 100-m turbine hub heights accomplished based on 30-m turbulence intensity observations. Trained over a 2-year period (2011-2012), the method was validated on year 2013. Similarly to the onshore application, the method was reliable in extrapolating wind speed to both 80 m and 100 m, with bias within 5%, NRMSE = 0.20 and r = 0.94. Conversely, scores were largely better than at the onshore site in predicting the annual energy yield, biased by 0.41-1.02% at 80 m, and 1.12-1.36% at 100 m. The method proved to be highly sensitive to the stability classification, as not considering this option increased its biases to 4.51-5.93% at 80 m, and 7.46-8.23% at 100 m. Method's reliability might suitably help reduce the number of masts installed throughout a large offshore area.

The present paper exhibits a real time assessment of a robust Energy Management Strategy (EMS) for battery-super capacitor (SC) Hybrid Energy Storage System (HESS). The proposed algorithm, dedicated to an electric vehicular application, is based on a self-gain scheduled controller, which guarantees the H∞ performance for a class of linear parameter varying (LPV) systems. Assuming that the duty cycle of the involved DC-DC converters are considered as the variable parameters, that can be captured in real time, and forwarded to the controller to ensure both; the performance and robustness of the closed-loop system. The subsequent controller is therefore time-varying and it is automatically scheduled according to each parameter variation. This algorithm has been validated through experimental results provided by a tailor-made test bench including both the HESS and the vehicle traction emulation system. The experimental results demonstrate the overall stability of the system, where the proposed LPV supervisor successfully accomplishes a power frequency splitting in an adequate way, respecting the dynamic of the sources. The proposed solution provides significant performances for different speed levels.

The most widely used process for hydrogen production is steam methane reforming. It can be carried out using a membrane reactor in which simultaneous hydrogen production and purification occur. Mathematical modeling of these reactors plays a key role in the selection of the design and operating parameters that yield high performance for the reactor. This review study discusses, synthesizes, and compares different mathematical modeling studies on the packed bed membrane reactors for hydrogen production from methane found in the literature. Different approaches used in these modeling studies for the hydrogen permeation steps, reaction kinetic expressions, phases involved (pseudo-homogeneous and heterogeneous), and spatial dimensions (one, two, and three dimensional) are given.

Abstract This work assesses the impacts of aggressive driving behavior on pollutants emissions and energy consumption at a city level. Furthermore, it performs an economic analysis considering the potential avoided emissions and fuel savings and discusses potential policy measures to address this topic. The results showed that aggressive driving significantly impacts energy consumption and emissions, with energy consumption increasing by more than ∼200% and emissions by 330% for aggressive driving compared to non-aggressive driving (in MJ/km and in g/km, respectively). This increment was found to be even higher for diesel vehicles than for gasoline vehicles. On the contrary, gasoline vehicles showed higher percentages of increase for most emissions (CO, NOx and NO). Results also revealed that aggressive driving impacts are higher for local streets when examining the city level. Moreover, the economic analysis showed that significant cost reductions may be achieved by avoiding aggressive driving, reaching up to 52.5 k€ on a daily basis. In conclusion, this study is of particular relevance to policy makers and urban planners, enabling to obtain a comprehensive overview of the impacts of aggressive driving behaviors at a city level and providing new insights to perform further developments and to assess the feasibility of the implementation of policy measures.

In this study, air concentrations of BaP in two different seasons (winter 2015 and summer 2016) and BaP levels in ground vegetation from Tarragona County were used as control simulations performed with the WRF-CHIMERE air quality modelling system, in order to reproduce the incidence of that hazardous chemical in air and soils. The CTM was validated for the present climatology, showing a good ability to represent air and soil concentrations of BaP over the target domain (petrochemical, chemical, urban and background sites), particularly in the winter. Then, the variation of the BaP concentrations in air and soils were simulated for the time series 1996-2015 and for the climate change scenario RCP8.5 (2031-2050). While an increase is projected for the levels in air, particularly in chemical and remote sites where the variation can go up to 10%, in terms of soil deposition the findings are the opposite, with an evident decrease in soil BaP concentrations, particularly for background sites. Finally, a potential health effect of BaP for the local population (lung cancer) was assessed. Although according to the projections the EU threshold for BaP atmospheric incidence (1 ng m-3) will not be reached by 2050, there will be an increase in the life-time risk of lung cancer, particularly in the most populated areas within the simulation domain.

Alternative fuels and energy vectors are becoming increasingly important in terms of technical, geopolitical, economic, and environmental aspects. In particular, gaseous fuels and vectors, such as fossil or synthetic natural gas (NG) blended with hydrogen, commonly help provide optimal strategies to reduce global and toxic emissions of internal combustion engines, owing to their adaptability, anti-knock capacity, lower toxicity of pollutants, reduced CO2 emissions, and costeffectiveness. However, diesel engines still represent the reference category among internal combustion engines in terms of maximum thermodynamic efficiency. The possibility offered by dual-fuel (DF) systems to combine the efficiency and performance of diesel engines with the environmental advantages of gaseous fuels has been the subject of extensive investigations. However, the simple replacement of diesel fuel with gaseous fuel does not allow for optimising the engine performance, owing to the high percentage of unburned gaseous fuel, which compromises the potential reduction of CO2; therefore, more complex combustion strategies should be realised. In this study, with the aim of improving the DF combustion process, an experimental investigation was performed to analyse low-temperature combustion (LTC), using NG and two enriched hydrogen-compressed NG blends as primary fuels. The LTC mode was activated by means of a very early advanced pilot injection and carried out in two close steps. The double pilot injection was used to control the energy release rate in the first combustion stage, thereby minimizing the increase of the rate of pressure and allowing the extension of the operation range under LTC. The experimental activity was also focused on analysing the particle emissions, as it is well known that these emissions, together with those of nitrogen oxide, constitute the main pollutants resulting from diesel fuel combustion. The results demonstrated the potential to reduce the unburned fuel, NOx, and particle emissions simultaneously, while maintaining equivalent CO2 emissions to a diesel-only engine. Both the timing and pressure of the pilot injection proved to be critical parameters for optimising the emissions and performance