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Review of LCA datasets in three emerging economies: a summary of learnings



In response to a need for interoperable LCA databases of adequate quality, a review of 40 datasets from emerging economies has been conducted with UNEP support by independent LCA experts, with the purpose to encourage improvements, either prior to publication or as part of a continuous improvement cycle. We discuss the lessons learned during this reviewing process.


The review effort had to be delivered in a set and limited timeline of 9 months and covered 20 datasets from Malaysia, ten from Brazil, and ten from Thailand. The developed review process consisted in, among others, (i) developing a set of review criteria for this specific effort, (ii) pairing a local sector reviewer with an international LCA expert to enhance capacity development, (iii) establishing a legal relationship via a non-disclosure agreement (NDA) between the data provider and the data reviewers, and (iv) providing a review report for each dataset that assesses the presence and magnitude of gaps or deficiencies relative to the criteria, as well as their implications for qualifying usage.

Results and discussion

The reviews provided solid recommendations for improvement to the majority of the datasets submitted by the three countries. This review exercise has been conducted in the given timeframe for the majority of the datasets. Many challenges have been faced along the way; among them agreeing on an NDA, the need for sufficient information, and the question of the confidentiality of the data. The developed set of criteria for this exercise have not been presented or discussed outside of the narrow review exercise and therefore can be seen as a starting point for further debates and improvements that should involve the broad LCA community.


This hands-on exercise provided some valuable insights into the road towards global consensus and guidance on data review. Beyond this time-constrained effort, a broader discussion and consensus at international level on the review of datasets and a continuous effort in reviewing datasets is desirable. Four key aspects were identified as necessary to consider: review criteria, review process, reviewers’ selection criteria, and development of a legal basis which protects the confidentiality of the data, as well as the position of the reviewers. This last aspect is sensitive as, in LCA datasets reviews, companies and/or countries might disclose some information with high stakes regarding competition and trade.

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  1. Precision refers to the likeliness to obtain the same values by repeating an experiment. Variability encompasses the range of obtained values due to different input parameters, such as the use of different technologies.


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The financial support provided by Solvay and the French National Association for Technical Research (CIFRE Convention N° 2013/1146) for the PhD thesis of Dieuwertje Schrijvers is acknowledged. Furthermore, the authors and project coordinators gratefully acknowledge the contributions of the many individuals and organizations who made this review possible. Mr. Chris Foster, Manchester University and EuGeos, Dr. Jutta Hildenbrand, Chalmers University and Swerea, and Dr. Alessandra Zamagni, ENEA and Ecoinnovazione, developed and refined the review criteria in a very short amount of time. Without their diligence, the completion of this review would not be possible. In a related vein, appreciation is extended to the experts who provided feedback on the draft criteria and evaluation system and those who participated in a workshop in Bordeaux, France ahead of the actual review. Last, but certainly not least, we thank all of the datasets reviewers for their major contributions to this effort, as well as the anonymous reviewers of this paper for their feedback.

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Correspondence to Guido Sonnemann.

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Responsible editor: Thapat Silalertruksa

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Vigon, B., Sonnemann, G., Asselin, A. et al. Review of LCA datasets in three emerging economies: a summary of learnings. Int J Life Cycle Assess 22, 1658–1665 (2017).

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  • Capacity development
  • Data quality
  • Data review
  • Emerging economies
  • LCI
  • Review criteria