Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
권호 표지

A Methodology on Treating Uncertainty of LCI Data using Monte Carlo Simulation

몬테카를로 시뮬레이션을 이용한 LCI data 불활실성 처리 방법론

  • 박지형 (한국과학기술연구원 CAD/CAM 연구센터) ;
  • 서광규 (상명대학교 산업정보시스템공학과)
  • Published : 2004.12.01
Download PDF
⟨ Previous Next ⟩

Abstract

Life cycle assessment (LCA) usually involves some uncertainty. These uncertainties are generally divided in two categories such lack of data and data inaccuracy in life cycle inventory (LCI). This paper explo.es a methodology on dealing with uncertainty due to lack of data in LCI. In order to treat uncertainty of LCI data, a model for data uncertainty is proposed. The model works with probabilistic curves as inputs and with Monte Carlo Simulation techniques to propagate uncertainty. The probabilistic curves were derived from the results of survey in expert network and Monte Carlo Simulation was performed using the derived probabilistic curves. The results of Monte Carlo Simulation were verified by statistical test. The proposed approach should serve as a guide to improve data quality and deal with uncertainty of LCI data in LCA projects.

Keywords

References

  1. Park, J.-H. and Seo, K.-K., 'Approximate Life Cycle Assessment of Classified Products Using Artificial Neural Network and Statistical Analysis in Conceptual Product Design,' Journal of the KSPE, Vol. 20, No. 3, pp. 207-213, 2003
  2. Curran, M. A., Environmental Life-Cycle Assessment, McGraw-hill, New York, 1996
  3. Huijbregts, M. A., Norris, G. A., Bretz, R., Ciroth, A., Maurice, B., Bahr, B., Weidema, B. P., Beaufort, A., 'Framework for Modelling Data Uncertainty in Life Cycle Inventories,' International Journal of Life Cycle Assessment, Vol. 6, No. 3, pp. 127-132, 2001
  4. Bjorklund, A. E., 'Survey of Approaches to Improve Reliability in LCA,' International Journal of Life Cycle Assessment, Vol. 7, No. 2, pp. 64-72, 2002 https://doi.org/10.1007/BF02978849
  5. Contadini, J. F., Moore, R. M. and Mokhtarian, P. L., 'Life Cycle Assessment of Fuel Cell Vehicles: A Methodology Example of Input Data Treatment for Future Technologies,' International Journal of Life Cycle Assessment, Vol. 7, No. 2, pp. 73-84, 2002 https://doi.org/10.1007/BF02978850
  6. Weidema, B. P. and Wemes, M. S., 'Data Quality Management for LCIs: an Example of using Data Quality indicators,' Journal of Cleaner Production, Vol. 4, No. 3-4, pp. 167-174, 1996 https://doi.org/10.1016/S0959-6526(96)00043-1
  7. Hoffmann, L., Weidema, B. P., Kristiansen, K., Kruger, A. S. and Ersboll, A. K., Statistical Analysis and Uncertainties in relation to LCA, Special Report No.1, Nordic Council of Ministers, Copenhagen, Denmark, 1995
  8. Chevalier, J. L. and Le Teno, J. F., 'Life Cycle Analysis with ill-defined Data and its Application to Building Products,' International Journal of Life Cycle Assessment, Vol. 1, No. 2, pp. 90-96, 1996 https://doi.org/10.1007/BF02978652
  9. Beccali, G., Beccali, M. and Cellura, M., 'Fuzzy Set Application in LCI of building material,' Proceedings of the Second International Conference on Building and Material, Vol. 1, 1997
  10. Petersen, E. H., 'LCA of Building Components. Handling Uncertainties in LCAs,' Proceedings of the Second International Conference on Building and Material, Vol. 1, 1997
  11. Kennedy, D. J., Montgomery, D.C. and Quay, B.H., 'Data Quality - Stochastic Environmental LCA Modeling,' International Journal of Life Cycle Assessment, Vol. 1, No. 4, pp. 199-207, 1996 https://doi.org/10.1007/BF02978693
  12. Owens, J. W., 'LCA Impact Assessment Categories: Technical Feasibility and Accuracy,' International Journal of Life Cycle Assessment, Vol. 1, No. 3, pp. 151-158, 1996 https://doi.org/10.1007/BF02978944
  13. Powell, J. D., 'Approaches to Evaluation in LCA Impact Assessment,' International Journal of Life Cycle Assessment, Vol. 2, No. 1, pp. 11-15, 1997 https://doi.org/10.1007/BF02978709
  14. Clemen, T. R., 'Extraneous Expert Information,' Journal of Forecasting, Vol. 4, pp. 329-348, 1985 https://doi.org/10.1002/for.3980040403
  15. Linstone, H. A. and Turoff, M., The Delphi Method: Techniques and Applications, Addison & Wesley. Reading, MA, 1975
  16. Ayton, P., Ferrel, W. R. and Stewart, T. R., 'Commentaries on The Delphi Techniques as a Forecasting Tool; Issues and Analysis,' International Journal of Forecasting, Vol. 15, pp. 377-381, 1999 https://doi.org/10.1016/S0169-2070(99)00013-8
  17. Al-Alawi, S. M. and Islam, S. M., 'Principles of Electricity Demand Forecasting, Part I Methodology,' Power Journal, June, pp. 139-143, 1996 https://doi.org/10.1049/pe:19960306
  18. Vose, D., Quantitative Risk Analysis: A Guide to Monte Carlo Simulation Modeling, John Wiley & Sons Ltd, England, 1996