Signal-to-noise ratio optimization in X-ray fluorescence spectrometry for chromium contamination analysis

In most cases, direct X-ray fluorescence (XRF) analysis of solutions entails technical difficulties due to a high Xray scattering background resulting in a spectrum with a poor signal-to-noise ratio (SNR). Key factors that determine the sensitivity of the method are the energy resolution of the detector and the amount of scattered radiation in the energy range of interest. Limiting the width of the primary spectrum by the use of secondary targets, or filters, can greatly improve the sensitivity for specific portions of the spectrum. This paper demonstrates a potential method for SNR optimization in direct XRF analysis of chromium (Cr) contamination. The suggested method requires minimal sample preparation and achieves higher sensitivity compared to existing direct XRF analysis. Two states of samples, fly ash and leachate from municipal solid waste incineration, were investigated. The effects of filter material, its absorption edge and filter thickness were analyzed using the combination of Monte Carlo N-Particle (MCNP) code and energy-dispersive XRF spectrometry. The applied filter removes primary photons with energies interfering with fluorescence photons from the element of interest, thus results in lower background scattering in the spectrum. The SNR of Cr peak increases with filter thickness and reaches a saturation value when further increased thickness only increases the measurement time. Measurements and simulations show that a Cu filter with a thickness between 100 mu m and 140 mu m is optimal for detecting Cr by taking into account both the SNR and the exposure time. With direct XRF analysis for solutions, the limit of quantitation (LOQ) of the achieved system was 0.32 mg/L for Cr, which is well below the allowed standard limitation for landfills in Sweden. This work shows that XRF can gain enough sensitivity for direct monitoring to certify that the Cr content in leachate is below environmental limits.