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The European Commission (EC) has set ambitious CO2 emission reduction objectives for the transport sector by 2050. In this context, most decarbonisation scenarios for transport foresee large market penetration of electric vehicles in 2030 and 2050. The emergence of electrified car mobility is, however, uncertain due to various barriers such as battery costs, range anxiety and dependence on battery recharging networks. Those barriers need to be addressed in the 2020–2030 decade, as this is key to achieving electrification at a large scale in the longer term. The paper explores the uncertainties prevailing in the first decade and the mix of policies to overcome the barriers by quantifying a series of sensitivity analysis scenarios of the evolution of the car markets in the EU Member States and the impacts of each barrier individually. The model used is PRIMES-TREMOVE, which has been developed by E3MLab and constitutes a detailed energy-economic model for the transport sector. Based on model results, the paper assesses the market, energy, emission and cost impacts of various CO2 car standards, infrastructure development plans with different geographic coverage and a range of battery cost reductions driven by learning and mass industrial production. The assessment draws on the comparison of 29 sensitivity scenarios for the EU, which show that removing the barriers in the decade 2020–2030 is important for electrification emergence. The results show that difficult policy dilemmas exist between adopting stringent standards and infrastructure of wide coverage to push technology and market development and adverse effects on costs, in case the high cost of batteries persists. However, if the pace of battery cost reductions is fast, a weak policy for standards and infrastructure is not cost-effective and sub-optimal. These policies are shown to have impacts on the competition between pure electric and plug-in hybrid vehicles. Drivers that facilitate electrification also favour the uptake of the former technology, the latter being a reasonable choice only in case the barriers persist and obstruct electrification.

A “Well-to-Propeller” Life Cycle Assessment of maritime transport was performed with a European geographical focus. Four typical types of vessels with specific operational profiles were assessed: a container vessel and a tanker (both with 2-stroke engines), a passenger roll-on/roll-off (Ro-Pax) and a cruise vessel (both with 4-stroke engines). All main engines were dual fuel operated with Heavy Fuel Oil (HFO) or Liquefied Natural Gas (LNG). Alternative onshore and offshore fuel supply chains were considered. Primary energy use and greenhouse gas emissions were assessed. Raw material extraction was found to be the most impactful life cycle stage (~90% of total energy use). Regarding greenhouse gases, liquefaction was the key issue. When transitioning from HFO to LNG, the systems were mainly influenced by a reduction in cargo capacity due to bunkering requirements and methane slip, which depends on the fuel supply chain (onshore has 64% more slip than offshore) and the engine type (4-stroke engines have 20% more slip than 2-stroke engines). The combination of alternative fuel supply chains and specific operational profiles allowed for a complete system assessment. The results demonstrated that multiple opposing drivers affect the environmental performance of maritime transport, a useful insight towards establishing emission abatement strategies.

The diffusion of electric vehicles (EVs) can be sustained by the presence of integrated solutions offering parking and clean power supply. The recourse to DC systems allows better integration of EV bidirectional energy exchange, photovoltaic panels, and energy storage. In this paper, a methodology for optimal techno-economic sizing of a DC-microgrid for covering EV mobility needs is carried out. It is based on the definition of different scenarios of operation, according to typical EV usage outlooks and environmental conditions. In each scenario, optimal operation is carried out by means of a specific approach for EV commitment on different stations. The sizing procedure is able to handle the modular structure of microgrid devices. The proposed approach is applied to a case study of an envisaged EV service fleet for the Bari port authority.

This Round Robin Test program aims to establish the influence of the combined wave and current effect on the power capture and performance of a generic tidal turbine prototype. Three facilities offering similar range of experimental conditions have been selected on the basis that their dimensions along with the rotor diameter of the turbine translate into low blockage ratio conditions. The performance of the turbine shows differences between the facilities up to 25% in terms of average power coefficient, depending on the wave and current cases. To prevent the flow velocity increasing these differences, the turbine performance coefficients have been systematically normalized using a time-average disc-integrated velocity, accounting for vertical gradients over the turbine swept area. Differences linked to blockage effects and turbulence characteristics between facilities are both responsible for 5 to 10% of the power coefficient gaps. The intrinsic differences between the tanks play a significant role as well. A first attempt is given to show how the wave-current interaction effects can be responsible for differences in the turbine performance. In these tanks, the simultaneous generation of wave and current is a key part often producing disruptions in both of these flow characteristics.

This paper evaluates how policy shaped the emergence of electric mobility in three countries, Norway, the Netherlands and Denmark, between 2010 and 2015. Whereas previous studies have looked at the effects of separate policy instruments, this paper gives insights in the interaction effects of instruments on the diffusion of battery electric cars between five policy areas. Based on analysis of synergetic, contradictory and pre-conditional effects, we find that an effective policy mix includes: fiscal incentives that mirror the actual carbon footprint of the respective vehicles; non-fiscal demand-side incentives; centrally financed and/or coordinated charging infrastructure; clarity regarding the choice of technology that will be supported. Moreover, development of a domestic, e-mobility-related industry and a high share of renewable energy strengthens the legitimization of e-mobility support. The findings help designing policy mixes in the transition to electric mobility.

According to the Paris Agreement, the European energy system transition is essential to achieve GHG emission reduction targets set by the EU and limit the growth of global temperatures. Investigating the role of emerging mitigation technologies and their uncertainties together with the different GHG reduction targets is crucial to realize this transition. This study analyzes the uncertainties of electric vehicles' learning paths and biomass availability for biofuels, considering policy uncertainties. Since these technologies are considered possible alternatives to conventional fuels to reduce CO2 emissions in transport, it is critical to understand their future role and the possible impact of their uncertainties during the European energy system design in case of different climate ambitions. Stochastic modeling is applied to analyze associated uncertainties as an additional approach to a traditional sensitivity analysis. Our results show that decarbonization of car transport is prioritized, and electric cars appear as no-regret options in the sector's design during the energy transition. Therefore, early deployments of EVs are essential to hedge the given uncertainties independent of the hedging period's length. Longer resolution time reduces the deployment of electric vehicles in the recourse strategies compared to having a shorter one due to a delay in the cost reductions. This decline becomes more evident with the stochastic analysis. The policy uncertainty of decarbonization targets has the highest impact on the studied uncertainties on the development of the transport sector. The transport sector can show faster adjustments considering the technology portfolio's shorter lifetime. Thanks to this adjustment, the sector depicts higher decarbonization in the hedging as well as in the recourse strategies.

The mooring system of floating wave energy converters (WECs) has a crucial impact on power generation efficiency, cost of delivered energy, proper operation, reliability and survivability. An effective design, addressing such competing objectives, requires appropriate mathematical models to predict mooring loads and dynamic response. However, conversely to traditional offshore engineering applications, experience in modelling mooring systems for WECs is limited, due to their unique requirement of maximising the motion while minimising loads and costs. Even though modelling approaches and software are available for this application, guidelines and critical comparison are still scarce. This paper proposes a discussion and validation of three mooring-line models: one quasi-static approach (developed in-house) and two dynamic lumped-mass approaches (the open source MoorDyn and the commercial OrcaFlex). The case study is a 1:32-scale prototype of a floating oscillating water column WEC tested in a wave tank, with three mooring lines, each one comprising of a riser and a clump weight. Validation, performed by imposing fairlead displacements and comparing resulting tensions, shows good agreement. The small scale may induce numerical instabilities and uncertainties in the parameter estimation. Finally, likely due to internal resonance of this particular mooring system, high-frequency content in the mooring tension is found, albeit absent in the kinematics of the floater.