How robust are reductions in modeled estimates from GTAP-BIO of the indirect land use change induced by conventional biofuels?
Evidence from modeling studies shows that Indirect land use change (ILUC) emissions associated with biofuel policies play an important role in determining the climate performance of those policies, but the magnitude of these emissions for any given biofuel is contentious and subject to uncertainty....
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Published in | Journal of cleaner production Vol. 258; p. 120716 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
10.06.2020
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Subjects | |
Online Access | Get full text |
ISSN | 0959-6526 1879-1786 |
DOI | 10.1016/j.jclepro.2020.120716 |
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Summary: | Evidence from modeling studies shows that Indirect land use change (ILUC) emissions associated with biofuel policies play an important role in determining the climate performance of those policies, but the magnitude of these emissions for any given biofuel is contentious and subject to uncertainty. In this study, we examine the development since 2008 of the computable general equilibrium model of the Global Trade Analysis Project (GTAP-BIO) as an ILUC modeling tool. While developments to this model over the past decade have resulted in much lower ILUC values being proposed for U.S. corn ethanol and soy biodiesel by the most recent papers than in earlier work, we find that these developments have been adopted based on limited or disputed evidence. Adjustments to the model and its input parameters have strengthened the assumed role of productivity increases as compared to land use changes in meeting feedstock demand without compelling justification, while new emission factors developed for use with the GTAP-BIO results systematically underestimate ILUC emissions. We argue that the combination of these effects has introduced a significant optimism bias into the ILUC emissions results reported in more recent studies using the GTAP-BIO framework. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0959-6526 1879-1786 |
DOI: | 10.1016/j.jclepro.2020.120716 |