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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.

Abstract In this article, we investigate the intergenerational transmission of sustainable consumption practices. Whereas previous studies have used self-reported attitudes and behaviour, this study uses data on actual energy consumption for space-heating and hot water combined with extensive panel data from Danish administrative registers. The paper shows significant intergenerational correlations between the energy consumption patterns of adults and their mothers, also when controlling for the energy consumption of the mother-in-law, where possible. Furthermore, it shows that the intergenerational correlation is slightly stronger for adults with lower income levels. These results suggest that energy consumption practices are shared and reproduced within the family. Following theories of practice, the intergenerational similarities in energy consumption practices refer to bodily learned practices that are indirectly transmitted and negotiated through family relations. In this way, these findings also contribute to a better understanding of how practical understanding regarding how to perform practices is transmitted within more ordinary aspects of consumption that play a less obvious role in distinction. To ensure more sustainable consumption practices in the future, this paper points to the importance of the role of family relations and the transmission of embodied practices.

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. 

This chapter traces situations in which economic and material practices that can be connected to a globalised economy intersect with elements connected to climate change. We present three stories from the High Arctic, each showing moments where such intersections happen in different ways, generating specific concerns and lines of effects. The stories are situated in Qaanaaq, the northernmost town in Greenland, located at 77° N. Here, although human livelihoods and ecosystems are affected by globalised economies – capitalist modes of production and lines of consumption – people live with limited access to free flows of money and commodities. The chapter describes and situates particular concerns and effects related to climate change, and analyses how climate change effects tangle with and impinge upon the complexity of local livelihoods and national aspirations in Greenland. It questions how public and political discourses tend to engage with climatic and environmental change as one phenomenon that takes place globally, and poses a puzzle to be solved by a global community. Rather than seeing climate change as providing humanity with one broad puzzle to be solved, we propose these ethnographic stories as pieces of a puzzle, or puzzling pieces, each providing viewpoints and specifically situated challenges and concerns to learn from in order to deal with climatic changes and changes in livelihood opportunities, theoretically as well as practically and politically.

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.

Energy companies trading in derivatives which have a value based on an energy product ( “Energy Trading”) are subjected to a fragmented regulatory framework. They are supervised by a multitude of authorities on a national and European level. These authorities cooperate horizontally (between EU agencies or between national regulatory authorities) or vertically – between EU agencies and NRA’s) and in a formal and informal way. They share information on Energy Trading to detect market abuse. This article aims to provide insight in the effectiveness of supervisory activities within the Energy Trading landscape. In doing so, the obligation for energy companies to report fundamental data on the derivatives they trade in, is used for illustrative purposes and explained in light of the European Market Infrastructure Regulation (‘EMIR’), the Markets in Financial Instruments Directive and Regulation (‘MiFID II and MiFIR’) and the regulation on wholesale energy market integrity and transparency (‘REMIT’). The article finishes with a conclusion which advocates the necessity of information sharing and professional secrecy in the current regulatory landscape and intends to contribute to a discussion on the effectiveness of information sharing within an international context.

Green tea catechins mixed with caffeine have been proposed as adjuvants for maintaining or enhancing energy expenditure and for increasing fat oxidation, in the context of prevention and treatment of obesity. These catechins-caffeine mixtures seem to counteract the decrease in metabolic rate that occurs during weight loss. Their effects are of particular importance during weight maintenance after weight loss. Other metabolic targets may be fat absorption and the gut microbiota composition, but these effects still need further investigation in combination with weight loss. Limitations for the effects of green tea catechins are moderating factors such as genetic predisposition related to COMT-activity, habitual caffeine intake, and ingestion combined with dietary protein. In conclusion, a mixture of green tea catechins and caffeine has a beneficial effect on body-weight management, especially by sustained energy expenditure, fat oxidation, and preservation of fat free body-mass, after energy restriction induced body-weight loss, when taking the limitations into account.

Climate change forces society to adapt. Adaptation strategies are preferably based on the best available climate information. Climate projections, however, often inform adaptation strategies after being interpreted once or several times. This process affects the original message put forward by climate scientists when presenting the basic climate projections, in particular regarding uncertainties. The nature of this effect and its implications for decision-making are as yet poorly understood. This chapter explores the nature and consequences of (a) the communication tools used by scientists and experts and (b) changes in the communicated information as it travels through the decision-making process. It does so by analyzing observatories; the interpretative steps taken in a sample of 25 documents, pertaining to the field of public policies for climate change impact assessment and adaptation strategies. Five phases in the provisioning of climate information are distinguished: pre-existing knowledge (i.e., climate models and data), climate change projection, impact assessment, adaptation strategy, and adaptation plan. Between the phases, climate information is summarized and synthesized in order to be passed on. The results show that in the sample, information on uncertainty is underrepresented: e.g., studies focus on only one scenario and/or disregard probability distributions. In addition, visualization tools are often used ineffectively, leading to confusion and unintended interpretations. Several recommendations are presented. While climatologists need better training in communication issues, decision-makers also need training in climatology to adopt more cautious and robust adaptation strategies that account for the uncertainty inherent in climate projections.

Due to the increasing awareness of climate change, depletion of natural resources, and increasing world population, companies in the agri-food sector need to redesign their existing supply chains and take into account both the economic and environmental impact of their operations. In practice not all the required information is available in advance due to various sources of uncertainty in agri-food supply chains. In this research a multi-objective two-stage stochastic programming model is proposed to analyse and evaluate the economic and environmental impacts to account for uncertainty in agri-food supply chains. A mushroom supply chain in the Netherlands is presented as an illustrative case study. Optimal production planning decisions calculated with a two-stage stochastic programming model are compared with the results of an equivalent deterministic model. The results of the optimizations show that accounting for stochasticity in important model parameters can reduce the difference between expected and realized economic performance by approximately 4% on average. Moreover, this paper demonstrates that including stochastic model parameters can reduce the environmental impact without compromising the current economic performance. Given the assumptions in the setup of the case study and the available information, it is concluded that applying a 2-stage stochastic programming approach for production planning decisions can lead to improved economic and environmental performance in an agri-food supply chain. New findings in real-life case studies are needed to get profound insights and understanding on the impact of uncertainty on production planning decisions in sustainable agri-food supply chains.