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Extensive surfaces of land are currently under-utilized, marginal and/or contaminated (MUC) in many EU and neighbouring countries. In the past few years, scientific research has demonstrated that bioenergy crops can potentially render this land profitable, generating income for the local populations and, at the same time, reaching the goals of the new Renewable Energy Directive (REDII) without interfering with food production. The main purpose of this paper is to measure net economic returns by computing benefits and costs of low indirect Land Use Change (iLUC) biofuel production on MUC land from the perspective of both the private investors and social welfare. A standard cost-benefit technique was applied to analyse and compare net returns of different advanced bioenergy value-chains in monetary terms. Productivity, economic feasibility and green-house gas (GHG) emissions impact were assessed and considered for the economic analysis. The considered pathways were cellulosic or second generation (2G) ethanol from Giant reed (Arundo donax) in Italy, electricity from miscanthus, biochemicals from spontaneous grass and cultivated Lucerne (Alpha-alfae) with sorghum for biomethane in Germany, and 2G ethanol from Willow (Salix viminalis) in Ukraine. For the risk assessment, Monte Carlo simulation was applied. The results indicated that in Italy and Ukraine, although the production of 2G ethanol would allow positive net yearly margins, the investments will not be profitable compared to the baseline scenarios. In Germany, the work showed good profitability for combined heat and power (CHP) and biochemicals. On the other hand, investments in biomethane showed negative results compared with the baseline scenarios. Finally, the Monte Carlo simulation enabled us to identify the range of possible economic results that could be attained once volatility is factored in. While for Italy the likelihood of yielding positive results remains lower than 20 percent, case studies in Ukraine and Germany showed higher certainty levels, ranging from 49 to 91 percent. [ABSTRACT FROM AUTHOR]

A Monte Carlo simulation methodology is suggested in order to assess the impact of ambient wind on a vehicle's performance and emissions. A large number of random wind profiles is generated by implementing the Weibull and uniform statistical distributions for wind speed and direction, respectively. Wind speed data are drawn from eight cities across Europe. The vehicle considered is a diesel-powered, turbocharged, light-commercial vehicle and the baseline trip is the worldwide harmonized light-duty vehicles WLTC cycle. A detailed engine-mapping approach is used as the basis for the results, complemented with experimentally derived correction coefficients to account for engine transients. The properties of interest are (engine-out) NO and soot emissions, as well as fuel and energy consumption and CO2 emissions. Results from this study show that there is an aggregate increase in all properties, vis-à-vis the reference case (i.e., zero wind), if ambient wind is to be accounted for in road load calculation. Mean wind speeds for the different sites examined range from 14.6 km/h to 24.2 km/h. The average increase in the properties studied, across all sites, ranges from 0.22% up to 2.52% depending on the trip and the property (CO2, soot, NO, energy consumption) examined. Based on individual trip assessment, it was found that especially at high vehicle speeds where wind drag becomes the major road load force, CO2 emissions may increase by 28%, NO emissions by 22%, and soot emissions by 13% in the presence of strong headwinds. Moreover, it is demonstrated that the adverse effect of headwinds far exceeds the positive effect of tailwinds, thus explaining the overall increase in fuel/energy consumption as well as emissions, while also highlighting the shortcomings of the current certification procedure, which neglects ambient wind effects. [ABSTRACT FROM AUTHOR]