Publication:
Consequential and attributional environmental assessment of biofuels: implications of modelling choices on climate change mitigation strategies

dc.contributor.authorTrakarn Prapaspongsaen_US
dc.contributor.authorShabbir H. Gheewalaen_US
dc.contributor.otherMahidol Universityen_US
dc.contributor.otherKing Mongkut s University of Technology Thonburien_US
dc.contributor.otherPERDOen_US
dc.date.accessioned2018-12-21T07:43:45Z
dc.date.accessioned2019-03-14T08:03:40Z
dc.date.available2018-12-21T07:43:45Z
dc.date.available2019-03-14T08:03:40Z
dc.date.issued2017-11-01en_US
dc.description.abstract© 2017, Springer-Verlag GmbH Germany. Purpose: The study aims to assess climate change mitigation potentials when using biomass-based fuels to replace fossil energy under consequential and attributional modelling approaches. The objectives are also to determine policy implications and to recommend the specific contexts suitable for each modelling choice by using specific illustrative cases on biofuels. Methods: Consequential and attributional modelling approaches are chosen for life cycle greenhouse gas emission assessment of several bioenergy options. The assessed functional unit is 1 MJ of energy from molasses-based ethanol, palm-based biodiesel and electricity production from rice straw. The fossil fuel comparators are gasoline (for molasses-based ethanol), diesel (for palm-based biodiesel) and coal and gas (for rice straw). The substituted and substituting product systems are modelled under the global and national markets depending on the market delimitation of each product. Results and discussion: The climate change mitigation potentials when using different approaches are dissimilar, because the affected product systems being included in the analysis are not the same. The palm biodiesel could reduce greenhouse gas emissions. The molasses-based ethanol and rice straw-based electricity may or may not mitigate the climate change, since it depends on the methodological choices as well as the baseline situations of the product systems being investigated. The main characteristics of consequential modelling as additionality and the inclusion of only actually affected processes under market-based mechanisms while those of attributional modelling as specification and attribution/allocation have limitations. The limitations lead to potential risks on unintended and undesirable consequences (for the attributional model), unfairness and sub-optimisation (for the consequential model) in policy recommendations. Conclusions: This research clearly illustrates how certain modelling choices affect the climate change mitigation potentials of biomass-based fuels in comparison with fossil energy. Specific questions and conditions which could be more suitable for each modelling choice are addressed. The attributional modelling is more suitable for national environmental taxation and emission labelling/accounting for import-export, while the consequential modelling is more appropriate for new production development and eco-design. Due to the potential environmental risks arising from the modelling limitations, the consideration of both the widely applied approaches could support decisions more comprehensively.en_US
dc.identifier.citationInternational Journal of Life Cycle Assessment. Vol.22, No.11 (2017), 1644-1657en_US
dc.identifier.doi10.1007/s11367-017-1355-2en_US
dc.identifier.issn16147502en_US
dc.identifier.issn09483349en_US
dc.identifier.other2-s2.0-85021304167en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/42643
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85021304167&origin=inwarden_US
dc.subjectEnvironmental Scienceen_US
dc.titleConsequential and attributional environmental assessment of biofuels: implications of modelling choices on climate change mitigation strategiesen_US
dc.typeArticleen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85021304167&origin=inwarden_US

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