ArticleResearch square2024
A comparison of field portable X-ray fluorescence (FP XRF) and inductively coupled plasma mass spectrometry (ICP-MS) for analysis of metals in the soil and ambient air.
Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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0 citing papers in PubMed, 3 citations in OpenAlex.
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
When analyzing metal concentrations in the soil and ambient air, accurate and reliable results are essential. Inductively coupled plasma mass spectrometry (ICP-MS) is considered the benchmark analytical method for environmental soil and air filter samples containing metals. Field portable X-ray fluorescence (FP XRF) can provide more timely results with lower ongoing costs, but the results are not as accurate as ICP-MS. The primary goal of this study was to find an optimal method to maximize the level of agreement between FP XRF results and ICP-MS results when analyzing metal concentrations in soil and ambient air samples in a U.S. Superfund community. Two different correction factor methods were tested to improve the prediction of ICP-MS concentrations using FP XRF for arsenic and lead in soil and ambient air. Ninety-one residential soil samples and 42 ambient air filter samples were analyzed in a split-half design, where half the samples were used to create the correction factors and the other half to evaluate the level of agreement between the analytical methods following FP XRF correction. Paired t-tests, linear regression plots, and Bland-Altman plots were utilized to examine which correction factor provided the highest level of agreement between the two methods. Based on the results from this study, it was determined that a ratio correction factor method provided the best fit for this FP XRF analytical device.
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