Reproducibility of LCA models of crude oil production.
Reproducibility of LCA models of crude oil production.
复制标题
原油生产 LCA 模型的再现性。
DOI：
10.1021/es501847p
复制
发表时间：
2014
影响因子：
11.4
通讯作者：
A. Brandt
中科院分区：
文献类型：
--
作者：
Kourosh Vafi;A. Brandt
科学模型在理想情况下是可复制的，尽管方法不同，结果却趋于一致。实际上，模型之间的分歧往往是由于不同的假设、不完整性，或者仅仅是因为可避免的缺陷而存在的。我们检验了LCA温室气体（GHG）排放模型，以测试其对油井到炼油厂入口门（WTR）温室气体排放估计的可重复性。我们使用基于开源工程的生命周期评估（LCA）模型——石油生产温室气体排放估算器（OPGEE）作为本分析的参考模型。我们研究了基于六个模型的七个先前的研究。我们通过连续的实验来检验先前结果的可重复性，这些实验使模型假设和边界保持一致。当模型输入未对齐时，结果之间的均方根误差（RMSE）在~ 1和8 g CO2当量/MJ LHV之间变化。在模型对齐之后，RMSE通常只会略微下降。一些模型的专有性质阻碍了对结果之间差异的解释。由于通常不可能通过直接测量来验证LCA温室气体排放的结果，我们建议开发开源模型用于能源政策。这种做法将导致反复的科学审查、模型的改进和对排放更可靠的了解。
Scientific models are ideally reproducible, with results that converge despite varying methods. In practice, divergence between models often remains due to varied assumptions, incompleteness, or simply because of avoidable flaws. We examine LCA greenhouse gas (GHG) emissions models to test the reproducibility of their estimates for well-to-refinery inlet gate (WTR) GHG emissions. We use the Oil Production Greenhouse gas Emissions Estimator (OPGEE), an open source engineering-based life cycle assessment (LCA) model, as the reference model for this analysis. We study seven previous studies based on six models. We examine the reproducibility of prior results by successive experiments that align model assumptions and boundaries. The root-mean-square error (RMSE) between results varies between ∼1 and 8 g CO2 eq/MJ LHV when model inputs are not aligned. After model alignment, RMSE generally decreases only slightly. The proprietary nature of some of the models hinders explanations for divergence between the results. Because verification of the results of LCA GHG emissions is often not possible by direct measurement, we recommend the development of open source models for use in energy policy. Such practice will lead to iterative scientific review, improvement of models, and more reliable understanding of emissions.