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首页> 外文期刊>Environmental Science & Technology >How to Conduct a Proper Sensitivity Analysis in Life Cycle Assessment: Taking into Account Correlations within LCI Data and Interactions within the LCA Calculation Model
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How to Conduct a Proper Sensitivity Analysis in Life Cycle Assessment: Taking into Account Correlations within LCI Data and Interactions within the LCA Calculation Model

机译：如何在生命周期评估中进行适当的敏感性分析：考虑LCI数据内的相关性以及LCA计算模型内的相互作用

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摘要

Sensitivity analysis (SA) is a significant tool for studying the robustness of results and their sensitivity to uncertainty factors in life cycle assessment (LCA). It highlights the most important set of model parameters to determine whether data quality needs to be improved, and to enhance interpretation of results. Interactions within the LCA calculation model and correlations within Life Cycle Inventory (LCI) input parameters are two main issues among the LCA calculation process. Here we propose a methodology for conducting a proper SA which takes into account the effects of these two issues: This study first presents the SA in an uncorrelated case, comparing local and independent global sensitivity analysis. Independent global sensitivity analysis aims to analyze the variability of results because of the variation of input parameters over the whole domain of uncertainty, together with interactions among input parameters. We then apply a dependent global sensitivity approach that makes minor modifications to traditional Sobol indices to address the correlation issue. Finally, we propose some guidelines for choosing the appropriate SA method depending on the characteristics of the model and the goals of the study. Our results clearly show that the choice of sensitivity methods should be made according to the magnitude of uncertainty and the degree of correlation.
机译：敏感性分析（SA）是研究结果的稳健性及其对生命周期评估（LCA）中不确定性因素的敏感性的重要工具。它突出显示了最重要的一组模型参数，以确定是否需要改善数据质量并增强结果的解释。 LCA计算模型中的交互作用以及生命周期清单（LCI）输入参数中的相关性是LCA计算过程中的两个主要问题。在这里，我们提出了一种考虑到这两个问题的影响而进行适当SA的方法：本研究首先介绍了不相关情况下的SA，比较了局部和独立的全局敏感性分析。独立的全局灵敏度分析旨在分析由于不确定性整个域中输入参数的变化以及输入参数之间的相互作用而导致的结果变异性。然后，我们采用一种依赖的全局敏感性方法，该方法对传统的Sobol指数进行了较小的修改以解决相关性问题。最后，我们根据模型的特征和研究目标提出一些选择合适的SA方法的指南。我们的结果清楚地表明，应根据不确定性的大小和相关程度来选择敏感度方法。

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  • 来源
    《Environmental Science & Technology》 |2015年第1期|377-385|共9页
  • 作者

    Wei Wei; Pyrene Larrey-Lassalle; Thierry Faure; Nicolas Dumoulin; Philippe Roux; Jean-Denis Mathias;

  • 作者单位

    Irstea, UR LISC, 9 avenue Blaise Pascal, F-63178 Aubiere, France;

    Irstea, UMR-Itap, 361 rue Jean-Francois Breton, F-34196 Montpellier, France;

    Irstea, UR LISC, 9 avenue Blaise Pascal, F-63178 Aubiere, France;

    Irstea, UR LISC, 9 avenue Blaise Pascal, F-63178 Aubiere, France;

    Irstea, UMR-Itap, 361 rue Jean-Francois Breton, F-34196 Montpellier, France;

    Irstea, UR LISC, 9 avenue Blaise Pascal, F-63178 Aubiere, France;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
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