Design of experiments for global sensitivity analysis in life cycle assessment: The case of biodiesel in Vietnam
Design of experiments for global sensitivity analysis in life cycle assessment: The case of biodiesel in Vietnam
复制标题
DOI：
10.1016/j.resconrec.2016.08.016
复制
发表时间：
2017-04-01
影响因子：
13.2
通讯作者：
Razon, Luis F.
中科院分区：
文献类型：
--
作者：
Khang, Dinh S.;Tan, Raymond R.;Razon, Luis F.
生物柴油作为化石燃料的替代品已被广泛提出，生物柴油对环境的影响通常采用生命周期评价（LCA）进行评价。然而，LCA的结果会受到参数不确定性的影响。因此，严格处理这种不确定性对于改进基于LCA的决策至关重要。本文提出了LCA全局灵敏度分析的拉丁超立方体实验设计（DOE）方法。在这种新方法中，LCA输入参数被用作实验设计的因素。本研究选择越南在当前条件下以麻风树、废食用油（WCO）和鱼油（FO）为原料制备生物柴油的LCA作为试验案例。LCA侧重于生物柴油系统的全球变暖潜势（GWP）、光化学臭氧形成潜势（POFP）、酸化潜势（AP）和富营养化潜势（EP）。然后使用层次分析法（AHP）将这些影响类别合并为总体环境影响（OEI）评分。采用拉丁超立方体设计，通过计算实验观察了LCA模型参数变化对OEI的影响。通过计算实验，识别出对LCA结果有显著影响的输入参数，并建立了代理多项式回归模型，实现了全局灵敏度分析。结果表明，农业产量、麻疯树种子含油量、酯交换率、总运输量和生物柴油掺混率是影响麻疯树生物柴油OEI的主要因素；在WCO柴油情况下，生物柴油混合分数和总运输量是显著的，而在FO生物柴油情况下，生物柴油混合分数是唯一显著的影响因素。生物柴油混合分数是所有原料中最重要的参数。(C) 2016 Elsevier B.V.版权所有
Biodiesel has been widely proposed as an alternative to fossil fuels and its environmental impacts have been commonly assessed using life cycle assessment (LCA). However, the results of LCA can be affected by parameter uncertainties. The rigorous treatment of such uncertainties is thus essential to improve decision-making based on the LCA. In this work, the Latin hypercube design of experiments (DOE) approach is proposed for global sensitivity analysis in LCA. In this novel approach, the LCA input parameters are used as the factors for the experimental design. The LCA of biodiesel from different feedstocks, namely, jatropha, waste cooking oil (WCO), and fish oil (FO), under the current conditions in Vietnam was chosen as a test case. The LCA focuses on the global warming potential (GWP), photochemical ozone formation potential (POFP), acidification potential (AP), and eutrophication potential (EP) of the biodiesel system. These impact categories were then combined into an overall environmental impact (OEI) score using the analytic hierarchy process (AHP). The effect of changes in the LCA model parameters on the OEI was then observed through computational experiments using a Latin hypercube design. From the computational experiments, the input parameters significantly affecting the results of LCA were identified, and a proxy polynomial regression model was derived to enable global sensitivity analysis to be performed. The results show that agricultural yield, oil content of jatropha seed, transesterification yield, total transportation, and biodiesel blending fraction are the factors that have significant effects on the OEI of jatropha biodiesel; biodiesel blend fraction and total transportation are significant in the case of WCO diesel, while the only significant effect factor in FO biodiesel case is biodiesel blend fraction. Biodiesel blend fraction is the most significant parameter for all feedstocks. (C) 2016 Elsevier B.V. All rights reserved.