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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.

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.

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.

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.

Abstract This work assesses the impacts of aggressive driving behavior on pollutants emissions and energy consumption at a city level. Furthermore, it performs an economic analysis considering the potential avoided emissions and fuel savings and discusses potential policy measures to address this topic. The results showed that aggressive driving significantly impacts energy consumption and emissions, with energy consumption increasing by more than ∼200% and emissions by 330% for aggressive driving compared to non-aggressive driving (in MJ/km and in g/km, respectively). This increment was found to be even higher for diesel vehicles than for gasoline vehicles. On the contrary, gasoline vehicles showed higher percentages of increase for most emissions (CO, NOx and NO). Results also revealed that aggressive driving impacts are higher for local streets when examining the city level. Moreover, the economic analysis showed that significant cost reductions may be achieved by avoiding aggressive driving, reaching up to 52.5 k€ on a daily basis. In conclusion, this study is of particular relevance to policy makers and urban planners, enabling to obtain a comprehensive overview of the impacts of aggressive driving behaviors at a city level and providing new insights to perform further developments and to assess the feasibility of the implementation of policy measures.

Decentralized detection in a network of wireless sensor nodes involves the fusion of information about a phenomenon of interest (PoI) from geographically dispersed nodes. In this paper, we investigate the problem of binary decentralized detection in a dense and randomly deployed wireless sensor network (WSN), whereby the communication channels between the nodes and the fusion center are bandwidth-constrained. We consider a scenario in which sensor observations, conditioned on the alternate hypothesis, are independent but not identically distributed across the sensor nodes.We compare two different fusion architectures, namely, the parallel fusion architecture (PFA) and the cooperative fusion architecture (CFA), for such bandwidthconstrained WSNs, where each sensor node is restricted to send a 1-bit information to the fusion center. For each architecture, we derive expression for the probability of decision error at the fusion center. We propose a consensus flooding protocol for CFA and analyze its average energy consumption. We analyze the effects of PoI intensity, realistic link models, consensus flooding protocol, and network connectivity on the system reliability and average energy consumption for both fusion architectures. We demonstrate that a trade-off exists among spatial diversity gain, average energy consumption, delivery ratio of the consensus flooding protocol, network connectivity, node density, and PoI intensity in CFA. We then provide insight into the design of cooperative WSNs.