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HERO ID
5037894
Reference Type
Journal Article
Title
A comparison of land use change accounting methods: seeking common grounds for key modeling choices in biofuel assessments
Author(s)
de Bikuna, KS; Hamelin, L; Hauschild, MZ; Pilegaard, Kim; Ibrom, A
Year
2018
Is Peer Reviewed?
1
Journal
Journal of Cleaner Production
ISSN:
0959-6526
EISSN:
1879-1786
Volume
177
Page Numbers
52-61
DOI
10.1016/j.jclepro.2017.12.180
Web of Science Id
WOS:000424186600005
Abstract
Five currently used methods to account for the global warming (GW) impact of the induced land-use change (LUC) greenhouse gas (GHG) emissions have been applied to four biofuel case studies. Two of the investigated methods attempt to avoid the need of considering a definite occupation -thus amortization period by considering ongoing LUC trends as a dynamic baseline. This leads to the accounting of a small fraction (0.8%) of the related emissions from the assessed LUC, thus their validity is disputed. The comparison of methods and contrasting case studies illustrated the need of clearly distinguishing between the different time horizons involved in life cycle assessments (LCA) of land-demanding products like biofuels. Absent in ISO standards, and giving rise to several confusions, definitions for the following time horizons have been proposed: technological scope, inventory model, impact characterization, amortization/occupation, plantation lifetime and harvesting frequency. It is suggested that the anticipated technical lifetime of biorefineries using energy crops as feedstock stands as the best proxy for the cut-off criterion of lands occupation period and the inventory modeling period. Top-down LUC models are suggested as a gross reference benchmark to evaluate LUC results from bottom-up models, since the former represent average GHG emissions from deforestation statistics at different spatial resolutions. Reporting LUC emissions per area and implementing a corporate accounting system that ascribes deforestation emissions to responsible companies could avoid the critical uncertainty related to yield estimations. (C) 2017 Published by Elsevier Ltd.
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Third Biofuels Report to Congress
01% to 05%
01% to 05%
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