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1.
Bioresour Technol ; 100(21): 4919-30, 2009 Nov.
Article in English | MEDLINE | ID: mdl-19553106

ABSTRACT

The promotion of biofuels as energy for transportation in the industrialized countries is mainly driven by the perspective of oil depletion, the concerns about energy security and global warming. However due to sustainability constraints, biofuels will replace only 10 to 15% of fossil liquid fuels in the transport sector. Several governments have defined a minimum target of GHG emissions reduction for those biofuels that will be eligible to public incentives, for example a 35% emissions reduction in case of biofuels in Members States of the European Union. This article points out the significant biases in estimating GHG balances of biofuels stemming from modelling choices about system definition and boundaries, functional unit, reference systems and allocation methods. The extent to which these choices influence the results is investigated. After performing a comparison and constructive criticism of various modelling choices, the LCA of wheat-to-bioethanol is used as an illustrative case where bioethanol is blended with gasoline at various percentages (E5, E10 and E85). The performance of these substitution options is evaluated as well. The results show a large difference in the reduction of the GHG emissions with a high sensitivity to the following factors: the method used to allocate the impacts between the co-products, the type of reference systems, the choice of the functional unit and the type of blend. The authors come out with some recommendations for basing the estimation of energy and GHG balances of biofuels on principles such as transparency, consistency and accuracy.


Subject(s)
Bioelectric Energy Sources , Gases/chemistry , Greenhouse Effect , Ethanol/metabolism , Gasoline , Motor Vehicles , Thermodynamics , Triticum/metabolism , Vehicle Emissions
2.
Bioresour Technol ; 96(9): 985-1002, 2005 Jun.
Article in English | MEDLINE | ID: mdl-15668196

ABSTRACT

Reducing the use of non-renewable fossil energy reserves together with improving the environment are two important reasons that drive interest in the use of bioethanol as an automotive fuel. Conversion of sugar and starch to ethanol has been proven at an industrial scale in Brazil and the United States, respectively, and this alcohol has been able to compete with conventional gasoline due to various incentives. In this paper, we examined making ethanol from the sugar extracted from the juice of sweet sorghum and/or from the hemicellulose and cellulose in the residual sorghum bagasse versus selling the sugar from the juice or burning the bagasse to make electricity in four scenarios in the context of North China. In general terms, the production of ethanol from the hemicellulose and cellulose in bagasse was more favorable than burning it to make power, but the relative merits of making ethanol or sugar from the juice was very sensitive to the price of sugar in China. This result was confirmed by both process economics and analysis of opportunity costs. Thus, a flexible plant capable of making both sugar and fuel-ethanol from the juice is recommended. Overall, ethanol production from sorghum bagasse appears very favorable, but other agricultural residues such as corn stover and rice hulls would likely provide a more attractive feedstock for making ethanol in the medium and long term due to their extensive availability in North China and their independence from other markets. Furthermore, the process for residue conversion was based on particular design assumptions, and other technologies could enhance competitiveness while considerations such as perceived risk could impede applications.


Subject(s)
Carbohydrates/biosynthesis , Carbohydrates/economics , Energy-Generating Resources/economics , Ethanol/economics , Ethanol/metabolism , Sorghum/metabolism , Bioreactors/economics , Chemical Industry/economics , China , Computer Simulation , Conservation of Natural Resources , Cost-Benefit Analysis/methods , Energy Metabolism , Industrial Microbiology/economics , Models, Econometric
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