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Uncertainty Implications of Hybrid Approach in LCA: Precision versus Accuracy

机译:LCA中混合方法的不确定性含义:精度与精度

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摘要

The hybrid approach in Life Cycle Assessment (LCA) that uses both input-output and process data has been discussed in the context of mitigating truncation error and burdens of data collection. However, the implication of introducing input-output data on the overall uncertainty of an LCA result has been debated. In this study, we selected an existing process LCA, performed a Monte Carlo simulation after hybridizing each truncated flow at a time, and analyzed the dispersion and position of the distribution in the results. The results showed that hybridization effectively moved the mean of the life cycle greenhouse gas (GHG) emissions 38% higher while maintaining the standard deviation within the 0.62-0.78 range (relative standard deviation, 3-4%). We identified key activities contributing to the overall uncertainty and simulated the potential effect of collecting higher quality supplier-specific data for those activities on the overall uncertainty. The results showed that replacing as few as 10 of the largest uncertainty contributors with high precision supplier-specific data substantially narrowed the distribution. Our results suggest that hybridizing truncated inputs improves accuracy of LCA results without compromising their precision, and prioritizing supplier specific data collection can further enhance precision in a cost-effective manner.
机译:在缓解截断错误和数据收集负担的背景下,已经讨论了使用生命周期评估(LCA)的混合方法,该方法同时使用输入-输出和过程数据。但是,已经讨论了引入输入输出数据对LCA结果的整体不确定性的含义。在这项研究中,我们选择了一个现有的过程LCA,在一次混合每个截断的流之后执行了Monte Carlo模拟,并分析了结果中分布的离散性和位置。结果表明,杂交有效地将生命周期温室气体(GHG)排放的平均值提高了38%,同时标准偏差保持在0.62-0.78范围内(相对标准偏差为3-4%)。我们确定了导致总体不确定性的关键活动,并模拟了为这些活动收集更高质量的特定于供应商的数据对总体不确定性的潜在影响。结果表明,用高精度的特定于供应商的数据替换最多的不确定性贡献者中只有10个,大大缩小了分布范围。我们的结果表明,将截短的输入进行混合可以提高LCA结果的准确性,而又不会影响其精度,而对供应商特定的数据进行优先排序可以以经济高效的方式进一步提高精度。

著录项

  • 来源
    《Environmental Science & Technology》 |2019年第7期|3681-3688|共8页
  • 作者

    Perkins Jessica; Suh Sangwon;

  • 作者单位

    Univ Calif Santa Barbara, Bren Sch Environm Sci & Management, Santa Barbara, CA 93106 USA;

    Univ Calif Santa Barbara, Bren Sch Environm Sci & Management, Santa Barbara, CA 93106 USA;

  • 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
  • 中图分类
  • 关键词

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