General Information
    • ISSN: 2010-0264
    • Frequency: Bimonthly (2010-2014); Monthly (Since 2015)
    • DOI: 10.18178/IJESD
    • Editor-in-Chief: Prof. Richard Haynes
    • Executive Editor: Ms. Nancy Y. Liu
    • Abstracting/ Indexing: Chemical Abstracts Services (CAS), CABI, DOAJ, Ulrich Periodicals Directory, Engineering & Technology Digital Library, Electronic Journals Library, Crossref, ProQuest.
    • E-mail: ijesd@ejournal.net
  • Feb 21, 2017 News! Vol. 8, No. 3 has been indexed by Crossref.
  • Feb 20, 2017 News! Vol.8, No.3 has been published with online version. 15 peer reviewed articles are published in this issue.
Editor-in-chief
The University of Queensland, Australia
It is my honor to be the editor-in-chief of IJESD. The journal publishes good papers in the field of environmental science and development.
IJESD 2013 Vol.4(6): 652-657 ISSN: 2010-0264
DOI: 10.7763/IJESD.2013.V4.432

The Propagation of Probabilistic and Possibilistic Uncertainty in a Life Cycle Assessment: A Case Study of a Naphtha Cracking Plant in Taiwan

Kevin Fong-Rey Liu, Si-Yu Chiu, Ming-Jui Hung, and Jong-Yih Kuo
Abstract—The use of a life cycle assessments (LCA) is dramatically increasing, partially due to the ease of use of the commercial software. However, there is a critical doubt about the credibility of the assessment results, particularly in endpoint assessments. Each phase of a LCA involves some simplifications, assumptions and choices. More research is required to improve the credibility of assessments, such as studies of time and space effects and studies of dose-response effects. Another method of improving the credibility of assessments is to characterize, propagate and analyze uncertainty in a LCA. In this study, a probabilistic method (Monte Carlo simulation) and a possibilistic method (fuzzy set theory) are used to model uncertainty in the inventory (input data) of a naphtha cracking plant in Taiwan. The results of the probabilistic and possibilistic approaches are compared and discussed. The results show that although probability and possibility distributions have approximately the same bottom width, their highest peaks have almost the same value. The primary difference between probabilistic and possibilistic methods is in the number of calculations. In this study, at least 10,000-time simulations are used for a Monte Carlo simulation, in order to obtain a smoother curve and the vertex method for the possibilistic approach only uses 11 α-cuts (intervals), to produce a smooth triangle.

Index Terms—Life cycle assessment, Monte Carlo simulation, fuzzy set theory, possibility theory.

K. F. R. Liu, S. Y. Chiu, and M. J. Hung are with the Department of Safety, Health and Environmental Engineering, Ming Chi University of Technology, New Taipei City, Taiwan (e-mail: kevinliu@mail.mcut.edu.tw; mingjui@mail.mcut.edu.tw).
J. Y. Kuo is with the Department of Science and Information Engineering, National Taipei University of Technology, Taipei, Taiwan (e-mail: jykuo@ntut.edu.tw).

[PDF]

Cite:Kevin Fong-Rey Liu, Si-Yu Chiu, Ming-Jui Hung, and Jong-Yih Kuo, "The Propagation of Probabilistic and Possibilistic Uncertainty in a Life Cycle Assessment: A Case Study of a Naphtha Cracking Plant in Taiwan," International Journal of Environmental Science and Development vol. 4, no. 6, pp. 652-657, 2013.

Copyright © 2008-2016. International Journal of Environmental Science and Development. All rights reserved.
E-mail: ijesd@ejournal.net