Evaluating and ranking secondary data sources to be used in the Brazilian LCA database - SICV Brasil

The generation of reliable life cycle inventories is essential towards Life Cycle Assessment (LCA) development, and the use of literature inventories as data sources can serve as a driving force for emerging LCA databases. The aim of this paper was to propose a method to select and rank scientific publications to be used as possible data sources for supplying LCA databases with new datasets. A case study was designed to identify eligible datasets to compose the emergent Brazilian Life Cycle Inventory Database System the SICV Brasil launched in 2016. The methodology used was based on an exploratory research composed of three steps: i) a bibliographic survey on the scientific productions of Life Cycle Inventories (LCI) in Brazil from 2000 to 2017; ii) a cross-check of LCI data and information based on the 40 selected requirements used in order to analyze the quality of LCI datasets in terms of mandatory, recommended and optional requirements; and iii) an analysis of the data quality requirements for those datasets with support of principles of Analytical Hierarchy Process (AHP) to elect possible datasets to be included in the SICV Brasil database. In total, 57 publications were analyzed and the results indicated that mandatory requirements had under 50% acceptance and only 10 requirements (less than 25%) were fully met. The best LCI dataset received 73 points (90%) with the scoring method, while 16 datasets were given less than 40 points (50%). Therefore, it is necessary to improve data quality of LCI datasets found in literature before using them to integrate LCA databases. In this regard, this study proposed a guide with short, medium, and long-term measures to mitigate this problem. The idea is to put an action plan into practice to gather more LCI datasets from literature which may be eligible for publication to SICV Brasil to improve this national database with more and relevant high-quality datasets. (c) 2020 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Automated summary

This paper proposed a method to select and rank scientific publications as possible data sources for LCA databases, aiming to improve the quality of LCA datasets. The study found that the quality of LCI datasets in literature needs improvement and suggested short, medium, and long-term measures to address this issue.