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Life Cycle Assessment of Fuel Cell Vehicles - Dealing with Uncertainties

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  • Contadini, Jose F.

Abstract

Subjectivity and uncertainty surround life cycle assessment (LCA) in transportation terms, particularly when new technologies are evaluated amid future scenarios. The Fuel Upstream Energy and Emission Model (FUEEM) was developed to incorporate and propagate uncertainty within an LCA analysis. The model uses probabilistic curves generated by experts as inputs and then employs Monte Carlo simulation techniques to propagate these uncertainties throughout the full chain of fuel production and use. The FUEEM process also explicitly involves interested parties in the entire analysis process, not only in the final review phase. The FUEEM process is demonstrated within an analysis for the use of three different fuel cell vehicle technologies—direct hydrogen, indirect methanol, and indirect hydrocarbon—in 2010 within the South Coast Air Basin of California.

Suggested Citation

  • Contadini, Jose F., 2002. "Life Cycle Assessment of Fuel Cell Vehicles - Dealing with Uncertainties," Institute of Transportation Studies, Working Paper Series qt9gz1s67d, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt9gz1s67d
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    References listed on IDEAS

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    1. Stewart, Thomas R., 1999. "Commentary on "The Delphi technique as a forecasting tool: Issues and analysis" by Rowe and Wright," International Journal of Forecasting, Elsevier, vol. 15(4), pages 380-381, October.
    2. Beckmann, Günter & Klopries, Burkhard, 1991. "CO2 increase: Questions beyond climatic change," Energy, Elsevier, vol. 16(11), pages 1317-1330.
    3. Hauer , Karl-Heinz, 2001. "Analysis Tool for Fuel Cell Vehicle Hardware and Software (Controls) with an Application to Fuel Economy Comparisons of Alternative System Designs," Institute of Transportation Studies, Working Paper Series qt52g0c03n, Institute of Transportation Studies, UC Davis.
    4. Ayton, Peter & Ferrell, William R. & Stewart, Thomas R., 1999. "Commentaries on "The Delphi technique as a forecasting tool: issues and analysis" by Rowe and Wright," International Journal of Forecasting, Elsevier, vol. 15(4), pages 377-379, October.
    5. Rowe, Gene & Wright, George, 1999. "The Delphi technique as a forecasting tool: issues and analysis," International Journal of Forecasting, Elsevier, vol. 15(4), pages 353-375, October.
    6. Sperling, Daniel, 1989. "Transportation Energy Futures," University of California Transportation Center, Working Papers qt6tm50979, University of California Transportation Center.
    7. Norman Dalkey & Olaf Helmer, 1963. "An Experimental Application of the DELPHI Method to the Use of Experts," Management Science, INFORMS, vol. 9(3), pages 458-467, April.
    8. Welch, Eric & Bretschneider, Stuart & Rohrbaugh, John, 1998. "Accuracy of judgmental extrapolation of time series data: Characteristics, causes, and remediation strategies for forecasting," International Journal of Forecasting, Elsevier, vol. 14(1), pages 95-110, March.
    9. Timothy M. Barry, 1996. "Recommendations on the Testing and Use of Pseudo‐Random Number Generators Used in Monte Carlo Analysis for Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 16(1), pages 93-105, February.
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    Cited by:

    1. McCarthy, Ryan, 2004. "A Methodology to Assess the Reliability of Hydrogen-based Transportation Energy Systems," Institute of Transportation Studies, Working Paper Series qt0jb3w61z, Institute of Transportation Studies, UC Davis.
    2. Menten, Fabio & Tchung-Ming, Stéphane & Lorne, Daphné & Bouvart, Frédérique, 2015. "Lessons from the use of a long-term energy model for consequential life cycle assessment: The BTL case," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 942-960.
    3. McCarthy, Ryan, 2004. "A Methodology to Assess the Reliability of Hydrogen-based Transportation Energy Systems," Institute of Transportation Studies, Working Paper Series qt3tt704km, Institute of Transportation Studies, UC Davis.
    4. McCarthy, Ryan, 2004. "A Methodology to Assess the Reliability of Hydrogen-based Transportation Energy Systems," Institute of Transportation Studies, Working Paper Series qt14g1g7t7, Institute of Transportation Studies, UC Davis.
    5. Lipman, Timothy E., 2004. "What Will Power the Hydrogen Economy? Present and Future Sources of Hydrogen Energy," Institute of Transportation Studies, Working Paper Series qt5w82s62b, Institute of Transportation Studies, UC Davis.

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