LCA results are typically reported as deterministic, while reality is uncertain and variable. Through a systematic review, we studied which methodologies and associated visualizations have already been used to assess both uncertainty and variability, as separate concepts, in the same LCA study. We aim to select the most appropriate one(s) that allow to decide whether uncertainty or variability is dominating in the results.

562 studies were identified by combining four topics (uncertainty, variability, LCA and methodology) of which eleven were eligible. These studies used a multi-step approach, often combining Monte Carlo simulations with a local and/or global sensitivity analysis and statistical measures.

Based on our review, we recommend Monte Carlo simulations visualized in uncertainty and variability ratios and global sensitivity analysis visualized using total sensitivity indices for future use in LCA. Ratios allow to clearly decide whether uncertainty or variability is dominating and sensitivity indices allow to identify essential parameters.

LCA结果通常被报告为确定性的，而现实是不确定的且易变的。通过系统的审查，我们研究了哪些方法和相关的可视化已在同一LCA研究中作为独立的概念用于评估不确定性和可变性。我们旨在选择最合适的一个或多个变量，以决定不确定性或可变性是结果的主导。

通过将四个主题（不确定性，变异性，LCA和方法论）相结合，确定了562项研究，其中11项是合格的。这些研究采用了多步骤方法，通常将蒙特卡洛模拟与局部和/或全局敏感性分析以及统计量相结合。

根据我们的评论，我们建议以不确定性和可变比可视化的蒙特卡洛模拟，以及使用总灵敏度指标可视化的全局灵敏度分析，以供将来在LCA中使用。通过比率可以清楚地确定不确定性或可变性是主要因素，而灵敏度指数则可以确定基本参数。