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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.

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.

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.

This paper aims at reviewing the life cycle assessment (LCA) literature on second generation bioethanol based on lignocellulosic biomass and at identifying issues to be resolved for good LCA practice. Reviews are carried out on respective LCA studies published over the last six years. We use the classification of lignocellulosic biomass to define system boundaries, so that the comparison among LCA results can be thoroughly assessed based on identified system components. A basis for attributing environmental burden for different biomass feedstocks is also suggested. Despite the non-homogeneous systems, we conclude that second generation bioethanol performs better than fossil fuel at least for the two most studied impact categories, net energy output and global warming. For the latter category, carbon sequestration at the biomass generation stage can even consistently offset the GHG emissions from all parts of the life cycle chains at high ethanol percentage (≥85%). The aspect of biogenic carbon and agrochemical input for energy crops and biomass residues, and the effect of removal of the latter from soil have not been treated consistently. In contrast, the exclusion of upstream chain of biomass waste feedstocks is observed in practice. The bioethanol conversion process is mostly based on simultaneous saccharification and co-fermentation, characterized by high yield and low energy input. In this regard, the LCA results tend to under estimate the real impacts of the current technology. The choice of allocation methods strongly influences the final results, particularly when economic value is used as a reference. Substitution of avoided burden seems to be the most popular allocation method in practice, followed by partition based on mass, energy, and economic values.

In this study we show that a chemical ferricyanide cathode can be replaced by a biological oxygen reducing cathode in a plant microbial fuel cell (PMFC) with a new record power output. A biocathode was successfully integrated in a PMFC and operated for 151 days. Plants growth continued and the power density increased reaching a maximum power output of 679 mW/m2 plant growth area (PGA) in a 10 min polarization. The two week record average power densities was 240 mW/m2 PGA. The new records were reached due to the high redox potential of oxygen reduction which was effectively catalyzed by microorganisms in the cathode. This resulted in a 127 mV higher cathode potential of the PMFC with a biocathode than a PMFC with a ferricyanide cathode. We also found that substrate availability in the anode likely limits the current generation. This work is crucial for PMFC application as it shows that PMFC can be a completely sustainable biotechnology with an improved power output.

Governments around the world try to stimulate the development and use of renewable energy technologies, like wind energy. While wind turbines are increasingly being implemented, however. it lack of social acceptance tit the local level remains an important challenge for developers of wind power plant.,;. This article aims to explore the relative importance of social and institutional conditions and their interdependencies in the operational process of planning wind power schemes. The article not only focuses on how negative local social conditions can frustrate public policy (cf. NIMBY syndrome), but also on how positive local social conditions can compensate for a negative public policy framework. We analyzed the cases of implementing wind power of two actors (the regional energy distributor and small private investors) in the municipality of Zeewolde, the Netherlands. Both cases illustrate that the formal institutional framework (formal rules, procedures and instruments) is neutral in a certain sense. Social conditions - management styles, interests and informal contacts - put meaning in this framework. The way stakeholders deal with the prevailing institutional structure clarifies social acceptance and therewith implementation.

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.