https://scholars.lib.ntu.edu.tw/handle/123456789/77340
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Lo, Shih-Chi | en |
dc.contributor.author | Ma, Hwong-wen | en |
dc.contributor.author | Lo, Shang-Lien | en |
dc.creator | Lo, Shih-Chi;Ma, Hwong-wen;Lo, Shang-Lien | - |
dc.date.accessioned | 2009-01-14T03:38:43Z | - |
dc.date.accessioned | 2018-06-28T23:28:27Z | - |
dc.date.available | 2009-01-14T03:38:43Z | - |
dc.date.available | 2018-06-28T23:28:27Z | - |
dc.date.issued | 2005 | - |
dc.identifier.uri | http://ntur.lib.ntu.edu.tw//handle/246246/96821 | - |
dc.identifier.uri | http://ntur.lib.ntu.edu.tw/bitstream/246246/96821/1/46.pdf | - |
dc.description.abstract | The traditional life cycle assessment (LCA) does not perform quantitative uncertainty analysis. However, without characterizing the associated uncertainty, the reliability of assessment results cannot be understood or ascertained. In this study, the Bayesian method, in combination with the Monte Carlo technique, is used to quantify and update the uncertainty in LCA results. A case study of applying the method to comparison of alternative waste treatment options in terms of global warming potential due to greenhouse gas emissions is presented. In the case study, the prior distributions of the parameters used for estimating emission inventory and environmental impact in LCA were based on the expert judgment from the intergovernmental panel on climate change (IPCC) guideline and were subsequently updated using the likelihood distributions resulting from both national statistic and site-specific data. The posterior uncertainty distribution of the LCA results was generated using Monte Carlo simulations with posterior parameter probability distributions. The results indicated that the incorporation of quantitative uncertainty analysis into LCA revealed more information than the deterministic LCA method, and the resulting decision may thus be different. In addition, in combination with the Monte Carlo simulation, calculations of correlation coefficients facilitated the identification of important parameters that had major influence to LCA results. Finally, by using national statistic data and site-specific information to update the prior uncertainty distribution, the resultant uncertainty associated with the LCA results could be reduced. A better informed decision can therefore be made based on the clearer and more complete comparison of options. © 2004 Elsevier B.V. All rights reserved. | - |
dc.format | application/pdf | en |
dc.format.extent | 262538 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language | en | en |
dc.relation.ispartof | Science of the Total Environment | en_US |
dc.subject | Bayesian Monte Carlo simulation; Coefficients of variation; Life cycle assessment; Probabilistic uncertainty analysis | - |
dc.subject.classification | [SDGs]SDG7 | - |
dc.subject.classification | [SDGs]SDG12 | - |
dc.subject.classification | [SDGs]SDG13 | - |
dc.subject.other | Characterization; Climate change; Correlation methods; Greenhouse effect; Life cycle; Maximum likelihood estimation; Monte Carlo methods; Parameter estimation; Probability distributions; Reliability; Uncertain systems; Emission estimation; Intergovernmental panel on climate change (IPCC); Life cycle assessment (LCA); Gas emissions; emission inventory; greenhouse gas; life cycle analysis; Monte Carlo analysis; waste treatment; article; Bayes theorem; climate change; correlation coefficient; environmental impact; greenhouse effect; greenhouse gas; intermethod comparison; life cycle assessment; Monte Carlo method; priority journal; quantitative analysis; reliability; waste management; Bayes Theorem; Environmental Pollution; Materials Testing; Monte Carlo Method; Reproducibility of Results; Risk Assessment | - |
dc.title | Quantifying and reducing uncertainty in life cycle assessment using the Bayesian Monte Carlo method | en |
dc.type | journal article | en |
dc.identifier.doi | 10.1016/j.scitotenv.2004.08.020 | - |
item.fulltext | with fulltext | - |
item.grantfulltext | open | - |
dc.relation.pages | 23-33 | - |
dc.relation.journalvolume | 340 | - |
dc.relation.journalissue | 1-3 | - |
dc.identifier.uri.fulltext | http://ntur.lib.ntu.edu.tw/bitstream/246246/96821/1/46.pdf | - |
item.openairetype | journal article | - |
item.fulltext | with fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.grantfulltext | open | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | Environmental Engineering | - |
crisitem.author.orcid | 0000-0002-7595-2343 | - |
crisitem.author.orcid | 0000-0003-1668-6513 | - |
crisitem.author.parentorg | College of Engineering | - |
顯示於: | 環境工程學研究所 |
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