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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.

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 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 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 paper some preliminary experimental results on a Zebra battery based propulsion system for urban bus applications are presented. The tests were carried out using a laboratory 1:1 scale test bench, composed by a 65 kW electric drive, specifically designed for urban bus applications, supplied by two 20 kWh Zebra batteries connected in parallel. The electric power train was tested on a laboratory bench, connected through a fixed ratio gear box to a 100 kW regenerative electric brake provided with speed and torque controls, in order to evaluate the propulsion system performance in steady state operative conditions. The obtained preliminary experimental results were utilized to implement a Matlab-Simulink model of urban bus, which might be powered by the same electric propulsion system studied. Thanks to this model it was possible to evaluate the dynamic behavior of the urban bus, working on standard driving cycles, taking into account the resistant forces represented by proper vehicle/road/aerodynamic parameters. An evaluation of the expected real vehicle driving range was also estimated in different road conditions.

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.

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.