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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.

Globalization has changed the way global society addresses common and global problems.

This paper presents results of an online stated choice experiment on preferences of Dutch private car owners for alternative fuel vehicles (AFVs) and their characteristics. Results show that negative preferences for alternative fuel vehicles are large, especially for the electric and fuel cell car, mostly as a result of their limited driving range and considerable refueling times. Preference for AFVs increases considerably with improvements on driving range, refueling time and fuel availability. Negative AFV preferences remain, however, also with substantial improvements in AFV characteristics; the remaining willingness to accept is on average € 10,000-€ 20,000 per AFV. Results from a mixed logit model show that consumer preferences for AFVs and AFV characteristics are heterogeneous to a large extent, in particular for the electric car, additional detour time and fuel time for the electric and fuel cell car. An interaction model reveals that annual mileage is by far the most important factor that determines heterogeneity in preferences for the electric and fuel cell car. When annual mileage increases, the preference for electric and fuel cell cars decreases substantially, whilst the willingness to pay for driving range increases substantially. Other variables such as using the car for holidays abroad and the daily commute also appear to be relevant for car choice. © 2014 Elsevier Ltd.

Climaps.eu is an online atlas providing data, visualizations and commentaries about climate adaptation debate. It contains 33 issue-maps and 5 issue-stories. Each of the maps focuses on one issue in the adaptation debate and provides.The atlas is addressed to climate experts (negotiators, NGOs and companies concerned by global warming, journalists…) and to citizens willing to engage with the issues of climate adaptation.It employs advanced digital methods to deploy the complexity of the issues related to climate adaptation and information design to make this complexity legible.

In ecological risk assessment, exposure is generally modelled assuming static conditions, herewith neglecting the potential role of emission, environmental and biomass dynamics in affecting bioavailable concentrations. In order to investigate the influence of such dynamics on predicted bioavailable concentrations, the spatially-resolved dynamic model "ChimERA fate" was developed, incorporating macrophyte and particulate/dissolved organic carbon (POC/DOC) dynamics into a water-sediment system. An evaluation against three case studies revealed a satisfying model performance. Illustrative simulations then highlighted the potential spatio-temporal variability of bioavailable concentrations after a pulsed emission of four chemicals in a system composed of a pond connected to its inflow and outflow streams. Changes in macrophyte biomass and POC/DOC levels caused exposure variations which were up to a factor of 4.5 in time and even more significant (several orders of magnitude) in space, especially for highly hydrophobic chemicals. ChimERA fate thus revealed to be a useful tool to investigate such variations and to identify those environmental and ecological conditions in which risk is expected to be highest.

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.

The search for affordable high performance electrode materials in photoelectrochemical hydrogen production by solar water splitting is an ongoing quest. Hematite is a photoanode material with an electronic band gap suitable for efficient absorption of visible light in a photoelectrochemical cell (PEC). Although its poor electronic structure makes hematite a controversial candidate for PEC, it remains promising because it is an earth abundant, chemically stable and low cost material – necessary prerequisites for PEC to become a competitive cost-efficient solar fuel economy. In addition to reviewing some recent PEC research on hematite and its relevant physical and chemical characteristics, we show how hematite obtained by a low cost synthesis can be refined by hydrothermal treatment and further functionalized by coating with phycocyanin, a light harvesting protein known for photosynthesis in blue-green algae.

This work analyzes the synergy between two complementary unit operations - adsorbent dehumidification and drying - and presents a mixed integer nonlinear programming approach to optimize energy performance in a two-stage system. Combined with active constraint analysis, the adsorbent properties that promote energy performance are derived. Microporous adsorbents with higher sorption capacities at low vapor pressures and requiring higher regeneration temperatures are preferred for ambient air dehumidification in the first stage. For exhaust air dehumidification, mesoporous adsorbents with lower regeneration temperatures are preferred such that the exhaust air from the first regeneration stage can sufficiently regenerate them. For drying below 50 C, energy consumption reductions of about 70% are achieved compared to conventional dryers without adsorbent dehumidification depending on adsorbent properties. The results demonstrate the usefulness of superstructure optimization in matching the drying process with the capabilities of the adsorbents to enhance process synergy for improved energy efficiency. © 2013 American Chemical Society.