Life Cycle Assessment (LCA) characterises all the exchanges between human driven activities and the environment, thus representing a powerful approach for tackling the environmental impact of a production system. However, LCA practitioners must still choose the appropriate Life Cycle Impact Assessment (LCIA) method to use and are expected to justify this choice: impacts should be relevant facing the concerns of the study and misrepresentations should be avoided. This work aids practitioners in evaluating the adequacy between the assessed environmental issues and studied production system. Based on a geometrical standpoint of LCA framework, Life Cycle Inventories (LCIs) and LCIA methods were localized in the vector space spanned by elementary flows. A proximity measurement, the Representativeness Index (RI), is proposed to explore the relationship between those datasets (LCIs and LCIA methods) through an angular distance. RIs highlight LCIA methods that measure issues for which the LCI can be particularly harmful. A high RI indicates a close proximity between a LCI and a LCIA method, and highlights a better representation of the elementary flows by the LCIA method. To illustrate the benefits of the proposed approach, representativeness of LCIA methods regarding four electricity mix production LCIs from the ecoinvent database are presented. RIs for 18 LCIA methods (accounting for a total of 232 impact categories) were calculated on these LCIs and the relevance of the methods are discussed. RIs prove to be a criterion for distinguishing the different LCIA methods and could thus be employed by practitioners for deeper interpretations of LCIA results.

生命周期评估（LCA）表征了人类驱动的活动与环境之间的所有交流，因此代表了一种解决生产系统对环境影响的有效方法。但是，LCA从业者仍必须选择适当的生命周期影响评估（LCIA）方法来使用，并有望证明这一选择的合理性：面对研究的关注，影响应是相关的，应避免虚假陈述。这项工作可帮助从业人员评估所评估的环境问题与所研究的生产系统之间的充分性。基于LCA框架的几何观点，生命周期清单（LCI）和LCIA方法位于基本流所跨越的向量空间中。接近度测量，代表性指数（RI），提出通过角距离探索那些数据集（LCI和LCIA方法）之间的关系。RI突出显示了LCIA方法，这些方法可以衡量LCI可能特别有害的问题。高RI表示LCI和LCIA方法之间非常接近，并突出显示了通过LCIA方法更好地表示基本流量。为了说明所提出方法的好处，提出了有关来自ecoinvent数据库的四种电力生产LCI的LCIA方法的代表性。在这些LCI上计算了18种LCIA方法的RI（共计232个影响类别），并讨论了这些方法的相关性。RI被证明是区分不同LCIA方法的标准，因此从业人员可以使用RI对LCIA结果进行更深入的解释。