Quantitative Determination by 14C Analysis of the Biological Component in Fuels
MetadataShow full item record
CitationDijs, I. J., van der Windt, E., Kaihola, L., & van der Borg, K. (2006). Quantitative determination by 14C analysis of the biological component in fuels. Radiocarbon, 48(3), 315-323.
AbstractRadiocarbon analysis was performed by liquid scintillation counting (LSC) and accelerator mass spectrometry (AMS) to assess whether the content of biological components in hydrocarbon fuels could be derived. Different fuel mixtures were prepared containing bioethanol, fossil ethanol, and fossil gasoline. The specific 14C activity of these mixtures was obtained from LSC measurements and directly related to the concentration of carbon originating from the bioethanol (biocarbon). The results were checked via standardized carbon dating procedures and AMS. A good linear correlation exists between the fuel mixtures specific 14C activity and the concentration of biocarbon. Also, the biocarbon fraction of the fuel mixture (the ratio biocarbon : total carbon) and the normalized fraction of biocarbon (%M) showed good linear correlation. Therefore, both relations provide a possibility to quantitatively determine a fuels biocarbon content by 14C analysis. When the sample composition is known (e.g. Resolved by gas chromatography-mass spectroscopy [GC-MS] and nuclear magnetic resonance [NMR]), the amount of particular biological components in a fuel sample can be derived subsequently. For mixtures of bioethanol, fossil ethanol, and gasoline with bioethanol contents in the range of 0.52% m/m, it was found that errors in the normalized fraction of biocarbon (%M) were in the range of 2510%, respectively. For samples with a higher bioethanol content (up to pure bioethanol), the errors in %M were 10%. Errors might be larger if substantial changes in the concentration of atmospheric 14C took place during the growth period of the biofuel feedstock. By taking into account the variation in specific 14C activity of carbon over the last decades, and by modeling simple tree-growth, it could be illustrated that this effect becomes significant only if the biofuel feedstock stopped growing more than 1 decade ago, e.g. With wood from constructions.