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Title: Assessing the greenhouse gas emissions of transport biofuels
Author: Brown, Gareth D.
ISNI:       0000 0004 2727 9662
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2012
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Many fuel cycle greenhouse gas (GHG) emissions assessments of varying scope, detail and methodology have been carried out for various biofuels in recent years, and these have largely concluded that biofuels provide GHG reduction benefits as substitutes for fossil fuels. As more attention is focused on biofuels, however, doubts have been raised about the reliability of previous GHG assessments of these fuels. From a scientific perspective, three main observations give reason to doubt these assessments: 1. There are widely varying results for what appear to be identical fuels. 2. The assessment methodologies involve inherently subjective elements. 3. There is still significant scientific uncertainty in characterisations of important processes that need to be accounted for in most GHG assessments of biofuels. For accurate determination of the GHG emissions impacts of biofuels, there is a need for further development of standardised, demonstrably reliable assessment methods. This research investigates methods used for assessing net GHG emissions from biofuels. It identifies remaining methodological deficiencies that prevent the generation of definitive results. A methodological framework is developed for optimising the reliability of biofuel GHG assessments within the limits of currently available knowledge and methods, and the most important developments required for extending those limits are identified. A new calculation tool and database are developed to facilitate the carrying out of biofuel GHG assessments with optimal reliability. It is concluded that uncertainties associated with existing GHG assessments can significantly limit our ability to draw firm conclusions from comparisons of GHG impacts among biofuels and between biofuels and fossil fuels. Reliable GHG assessments of biofuels require very precise specifications of the systems being described, with clear definitions of the limitations of applicability of the assessment results, explanations of the methodological choices adopted and their implications, and acknowledgement of the limits set by all relevant scientific uncertainty.
Supervisor: Woods, Jem ; Shah, Nilay Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral