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The fuel cell vehicle (FCV) has the potential to revolutionize the world's transportation systems. As choices are made on sources of fuel for FCVs it is important to consider the life-cycle implications of each option or system. This paper summarizes the methodology and results of a joint initiative to evaluate the life-cycle performance of 72 vehicle and fuel scenarios in 3 Canadian cities, comparing Proton Exchange Membrane (PEM) fuel cell vehicles and fuelling infrastructure with conventional and alternative fuel vehicles. The analysis is based on actual performance data of commercial and near-commercial technologies. The specific fuels investigated were gasoline, diesel, natural gas, methanol, hydrogen and electricity. The Pembina Institute's Life-Cycle Value Assessment (LCVA) methodology was used to compare the environmental, economic and social performance of each system.

Life Cycle Assessment (LCA) is commonly used to measure the environmental and economic impacts of engineering projects and/or products. However, there is some uncertainty associated with any LCA study. The LCA inventory analysis generally relies on imperfect data in addition to further uncertainties created by the assessment process itself. It is necessary to measure the effects that data and process uncertainty have on the LCA result and to communicate the level of uncertainty to those making decisions based on the LCA. To accomplish this, a systematic and rigorous means to assess the overall uncertainty in LCA results is required. This paper demonstrates the use of Monte Carlo Analysis to track and measure the propagation of uncertainty in LCA studies. The Monte Carlo technique basically consists of running repeated assessments using random input values chosen from a specified probable range.