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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Quality of data for estimating GHG emissions in biofuel regulations is unknown: A review of default values related to sugarcane and corn ethanol

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Author(s):
Bicalho, Tereza [1] ; Sauer, Ildo [1] ; Patino-Echeverri, Dalia [2]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Inst Energy & Environm, Av Prof Luciano Gualberto 1289, BR-05508010 Sao Paulo, SP - Brazil
[2] Duke Univ, Nicholas Sch Environm, Durham, NC 27708 - USA
Total Affiliations: 2
Document type: Review article
Source: JOURNAL OF CLEANER PRODUCTION; v. 239, DEC 1 2019.
Web of Science Citations: 0
Abstract

European and United States' (U.S.) regulatory schemes mandate the use of biofuels based on estimates of life cycle GHG emissions that indicate their environmental superiority compared with conventional fuels. This paper analyzes the quality of the activity data used in calculating these estimates for Brazilian sugarcane and U.S. corn ethanol, in terms of completeness, reliability, and transparency. The findings demonstrate that it is impossible to determine the completeness of the data because the regulation's texts and related documents, and their sources fail to provide information on the representativeness or origins of the data. Moreover, there is no transparency about the sample from which data is extracted. To obtain this information it is necessary to review the literary sources referenced in the regulation's documents. Among the 37 sources of data examined in this analysis, 23 are no longer available, and only 3 sources contain information allowing for the characterization of the adequacy of the sample. In addition, none of the data items analyzed were subject to a verification process. These findings highlight the urgent need to modify biofuel regulation to set minimum standards for data quality and the reporting of data sources, paying particular attention to default activity data. (C) 2019 Elsevier Ltd. All rights reserved. (AU)

FAPESP's process: 14/00935-2 - Data quality assessment for LCA: a management science approach
Grantee:Tereza Cristina Assis Bicalho de Menezes
Support Opportunities: Scholarships in Brazil - Post-Doctoral