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The variability in viscosity and combustion quality has been identified from the literature as a barrier to the use of biodiesel fuels in motorsport. These parameters can affect performance, emissions and fuel consumption. Diesel engines have had recent success in endurance and touring car racing; biodiesel is an opportunity to increase the sustainability of this emerging area of motorsport.\ud \ud Methyl esters from rapeseed, soybean and sunflower oils were tested alongside EN 590 diesel fuel. Variations in fuel consumption, output torque and power were observed between the fuels. Further tests were carried out on an automotive diesel engine to evaluate the in-cylinder pressures for soybean B100, beef tallow B50 and EN 590 to gain understanding of the reasons behind the performance differences noted in the initial tests.\ud \ud Retarding the start of injection for B50 and B100 biodiesel improved the peak torque by up to 5% enabling the production of equal torque at the same engine speed when compared to EN 590 but with lower peak in-cylinder pressure and a shorter ignition delay. The application of this to motorsport is the potential to achieve higher peak power outputs; the shorter ignition delay and more rapid combustion has the potential to be used to raise the maximum engine speed and therefore the peak power output of diesel engines for motorsport.

Sustainability assessments require the management of a wide variety of information types, parameters and uncertainties. Multi criteriadecision analysis(MCDA) has been regarded as a suitable set of methods to perform sustainability evaluations as a result of its flexibility and the possibility of facilitating the dialogue between stakeholders, analysts and scientists. However, it has been reported that researchers do not usually properly define the reasons for choosing a certain MCDA method instead of another. Familiarity and affinity with a certain approach seem to be the drivers for the choice of a certain procedure. This reviewpaperpresents the performance of five MCDA methods (i.e. MAUT, AHP, PROMETHEE, ELECTRE and DRSA) in respect to ten crucial criteria that sustainability assessments tools should satisfy, among which are a life cycle perspective, thresholds and uncertainty management, software support and ease of use. The review shows that MAUT and AHP are fairly simple to understand and have good software support, but they are cognitively demanding for the decision makers, and can only embrace a weak sustainability perspective as trade-offs are the norm. Mixed information and uncertainty can be managed by all the methods, while robust results can only be obtained with MAUT. ELECTRE, PROMETHEE and DRSA are non-compensatory approaches which consent to use a strong sustainability concept, accept a variety of thresholds, but suffer from rank reversal. DRSA is less demanding in terms of preference elicitation, is very easy to understand and provides a straightforward set of decision rules expressed in the form of elementary “if … then …” conditions. Dedicated software is available for all the approaches with a medium to wide range of results capability representation. DRSA emerges as the easiest method, followed by AHP, PROMETHEE and MAUT, while ELECTRE is regarded as fairly difficult. Overall, the analysis has shown that most of the requirements are satisfied by the MCDA methods (although to different extents) with the exclusion of management of mixed data types and adoption of life cycle perspective which are covered by all the considered approaches.