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|Title:||A distance-to-target weighting method for Europe 2020|
|Authors:||CASTELLANI VALENTINA; BENINI LORENZO; SALA SERENELLA; PANT Rana|
|Citation:||INTERNATIONAL JOURNAL OF LIFE CYCLE ASSESSMENT vol. 21 no. 8 p. 1159–1169|
|Type:||Articles in periodicals and books|
|Abstract:||Purpose Distance-to-target (DTT) methods are weighting methods aimed at assessing the distance of an existing situation from a desired state (the target). Weighting factors in DTT methods could be based on calculation which is performed on normalization factors (NFs) developed for life cycle assessment (LCA). At present, some DTT weighting sets have been developed. However, there is no DTT weighting set assessing the distance of EU domestic impacts from the desired state set by EU binding or non-binding policy targets (e.g., those related to the “Climate and Energy Package” and the “Roadmap to a Resource Efficient Europe”). Methods In the present work, a methodology to derive target references from policy-based targets in 2020 (TRs2020), both binding (A) and non-binding (B), is presented. Resulting target factors and DTT weighting factors are then compared to the current normalisation factors (based on 2010 normalization references). The resulting weighting factor (WF) sets are presented and discussed in light of their use for decision support in policy and business contexts. We applied the WF sets to characterization results to an example (the EU energy mix process) aiming at illustrating key differences and effects on the results. Results and discussion The three reference sets (NRs2010, TRs2020A, and TRs2020B) show, in some impact categories, a relatively small difference. WFs referred to set A and set B result to be quite similar, with the only exception of water depletion impact category, for which a very relevant change is foreseen when considering the effect of the non-binding target of limiting the abstraction of water resource to 20 % of the available renewable water resources. This is mainly due to the higher difficulty in deriving quantitative targets from non-binding strategies and policies rather than from binding ones. Conclusions The resulting weighting sets present strengths and limitations. The translation of policy targets into quantitative modifications to the baseline inventories appeared to be not a straightforward task, due to several reasons discussed in the paper (e.g., not all the policy targets are expressed in quantitative terms or can be translated into quantitative reductions and modifications of the elementary flows in the existing baseline inventories). Aiming at improving the effectiveness in supporting policies, further development of the methodology may be the integration with other DTT approaches such those based on carrying capacity, developed to integrate Earth’s carrying capacity concept and planetary boundaries.|
|JRC Directorate:||Sustainable Resources|
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