title: Reproducibility of LCA models of crude oil production.
abstract: 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.
authors.affiliation: Department of Energy Resources Engineering, Stanford University , Stanford, California 94305-2220, United States.
authors.forename: Kourosh
authors.initials: K
authors.lastname: Vafi
authors.forename: Adam R
authors.initials: AR
authors.lastname: Brandt
mesh_terms: D017752:Greenhouse Effect; D008962:Models, Theoretical; D010578:Petroleum / Q000032:analysis; D015203:Reproducibility of Results
chemical_list: D010578:Petroleum