Application of Fourier Transform Infrared Spectroscopy (FTIR) for assessing biogenic silica sample purity in geochemical analyses and palaeoenvironmental research
- 1School of Geography, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
- 2Department of Chemical and Process Engineering, University of Strathclyde, James Weir Building, 75 Montrose Street, Glasgow, G1 1XJ, UK
Abstract. The development of a rapid and non-destructive method to assess purity levels in samples of biogenic silica prior to geochemical/isotope analysis remains a key objective in improving both the quality and use of such data in environmental and palaeoclimatic research. Here a Fourier Transform Infrared Spectroscopy (FTIR) mass-balance method is demonstrated for calculating levels of contamination in cleaned sediment core diatom samples from Lake Baikal, Russia. Following the selection of end-members representative of diatoms and contaminants in the analysed samples, a mass-balance model is generated to simulate the expected FTIR spectra for a given level of contamination. By fitting the sample FTIR spectra to the modelled FTIR spectra and calculating the residual spectra, the optimum best-fit model and level of contamination is obtained. When compared to X-ray Fluorescence (XRF) the FTIR method portrays the main changes in sample contamination through the core sequence, permitting its use in instances where other, destructive, techniques are not appropriate. The ability to analyse samples of <1 mg enables, for the first time, routine analyses of small sized samples. Discrepancies between FTIR and XRF measurements can be attributed to FTIR end-members not fully representing all contaminants and problems in using XRF to detect organic matter external to the diatom frustule. By analysing samples with both FTIR and XRF, these limitations can be eliminated to accurately identify contaminated samples. Future, routine use of these techniques in palaeoenvironmental research will therefore significantly reduce the number of erroneous measurements and so improve the accuracy of biogenic silica/diatom based climate reconstructions.