Browse Editions : 2008 / Biofuels
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Biofuel feedstock: is there enough?

 Rene Gonzalez, PTQ

2008 / Biofuels

A wider variety of feedstocks needs to be considered for biodiesel production.  Processing costs and undesirable byproduct formation are the reasons for considering entirely new technical routes.

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Agri-energy: the new technology frontier

Michael Schwartz, Triple Point Technology

2008 / Biofuels

Supply chain complexities and technology for managing risk in biofuels production and trading.  Systems deployed to manage risk in agri-energy should aggregate risk factors across multiple commodities from the agriculture and energy side of the equation.

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Catalytic conversion of cellulosic biomass

 Paul O'Connor and Rob van der Meij, BIOeCON BV

2008 / Biofuels

Future process routes based on heterogeneous catalysis will enable effective and economical conversion of solid biomass into sustainable fuels, chemicals and energy.  This conversion is based on the effective opening or unlocking of solid biomass.        

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Quality control of biofuels

A Steinbach, U Loyall, B Zumbragel, C Haider, G Spinnler, R Schlink and A Wille, Metrohm AG

2008 / Biofuels

For quality control of biofuels, determination of oxidation stability, iodine and acid number as well as water, alkali metal and alkaline earth metal content are important.  Titrimetric and ion chromatographic analyses are also addressed.

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New standards of efficiency for biogas installations

Alexandre Bouriant, Siemens AG

2008 / Biofuels

Case studies show that benefits from automation and control of biogas installations are being realised at facilities of various capacities.  For these facilities, plant operation was made substantially easier, and availability and reliability were conserably improved.    

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Biodiesel concentration measurements

David Wooton and David Armstrong, Wooton Consulting and Perkin Elmer.

2008 / Biofuels

Methods providing greater accuracy over the AFNOR method for determining biodiesel  concentration in fuel blends are discussed.  Principal component regression is explored as a means of alleviating errors when FAME is produced from varying feedstocks.

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