Differences between LCA for analysis and LCA for policy: A case study on the consequences of allocation choices in bio-energy policies

Purpose: The increasing concern for adverse effects of climate change has spurred the search for alternatives for conventional energy sources. Life cycle assessment (LCA) has increasingly been used to assess the potential of these alternatives to reduce greenhouse gas emissions. The popularity of LCA in the policy context puts its methodological issues into another perspective. This paper discusses how bio-electricity directives deal with the issue of allocation and shows its repercussions in the policy field. Methods: Multifunctionality has been a well-known problem since the early development of LCA and several methods have been suggested to deal with multifunctional processes. This paper starts with a discussion of the most common allocation methods. This discussion is followed by a description of bio-energy policy directives. The description shows the increasing importance of LCA in the policy context as well as the lack of consensus in the application of allocation methods. Methodological differences between bio-energy directives possibly lead to different assessments of bio-energy chains. To assess the differences due to methodological choices in bio-energy directives, this paper applies three different allocation methods to the same bio-electricity generation system. The differences in outcomes indicate the importance of solving the allocation issue for policy decision making. Results and discussion: The case study focuses on bio-electricity from rapeseed oil. To assess the influence of the choice of allocation in a policy directive, three allocation methods are applied: economic partitioning (on the basis of proceeds), physical partitioning (on the basis of energy content), and substitution (under two scenarios). The outcomes show that the climate change score is assessed quite differently; ranging from 0.293 kg to 0.604 kg CO ₂ eq/kWh. It is argued that this uncertainty hampers the optimal use of LCA in the policy context. The aim of policy LCAs is different from the aim of LCAs for analysis. Therefore, it is argued that LCAs in the policy context will benefit from a new guideline based on robustness. Conclusions: The case study confirms that the choice of allocation method in policy directives has large influence on the outcomes of an LCA. With the growing popularity of LCA in policy directives, this paper recommends a new guideline for policy LCAs. The high priority of robustness in the policy context makes it an ideal starting point of this guideline. An accompanying dialog between practitioners and commissioners should further strengthen the use of LCA in policy directives.