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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.

In this paper, the performances of two iron-based syngas-fueled chemical looping (SCL) systems for hydrogen (H2) and electricity production, with carbon dioxide (CO2) capture, using different reactor configurations were evaluated and compared. The first investigated system was based on a moving bed reactor configuration (SCL-MB) while the second used a fluidized bed reactor configuration (SCL-FB). Two modes of operation of the SCL systems were considered, namely, the H2 production mode, when H2 was the desired product from the system, and the combustion mode, when only electricity was produced. The SCL systems were modeled and simulated using Aspen Plus software. The results showed that the SCL system based on a moving bed reactor configuration is more efficient than the looping system with a fluidized bed reactor configuration. The H2 production efficiency of the SCL-MB system was 11 % points higher than that achieved in the SCL-FB system (55.1 % compared to 44.0 %). When configured to produce only electricity, the net electrical efficiency of the SCL-MB system was 1.4 % points higher than that of the SCL-FB system (39.9 % compared to 38.5 %). Further, the results showed that the two chemical looping systems could achieve >99 % carbon capture efficiency and emit ~2 kg CO2/MWh, which is significantly lower than the emission rate of conventional coal gasification-based plants for H2 and/or electricity generation with CO2 capture.

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.

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.

Sustainability is commonly assessed along environmental, societal, economic and technological dimensions. A crucial aspect of sustainability is that inter-generational equality must be ensured. This requires that sustainability is attained in the here and now as well as into the future. Therefore, what is perceived as 'sustainable' changes as a function of societal opinion and technological and scientific progress. A concept that describes the ability of systems to change is adaptive capacity. Literature suggests that the ability of systems to adapt is an integral part of sustainable development. This paper demonstrates that indicators measuring adaptive capacity are underrepresented in current urban water sustainability studies. Furthermore, it is discussed under which sustainability dimensions adaptive capacity indicators are lacking and why. Of the >90 indicators analysed, only nine are adaptive capacity indicators, of which six are socio-cultural, two technological, one economical and none environmental. This infrequent use of adaptive capacity indicators in sustainability assessments led to the conclusion that the challenge of dynamic and uncertain urban water systems is, with the exception of the socio-cultural dimension, not yet sufficiently reflected in the application of urban water sustainability indicators. This raises concerns about the progress towards urban water systems that can transform as a response variation and change. Therefore, research should focus on developing methods and indicators that can define, evaluate and quantify adaptive capacity under the economic, environmental and technical dimension of sustainability. Furthermore, it should be evaluated whether sustainability frameworks that focus on the control processes of urban water systems are more suitable for measuring adaptive capacity, than the assessments along environmental, economic, socio-cultural and technological dimensions.

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.