Matrix Effects in ICP–MS and XRF Analysis of Soil Samples With High Organic Matter Content

Sorption and desorption characteristics of sulfamethazine in three different soils before and after removal of organic matter

Zinc and selenium are essential minerals for human nutrition. Reliable biomarkers of zinc status and selenium status in humans are therefore important. This work investigates a novel portable X-ray fluorescence (XRF) method with the ability to rapidly assess zinc and selenium in nail clippings. This approach used a mono-energetic X-ray beam to excite characteristic X-rays from the clippings. Nail clippings were obtained from the Mother and Infant Nutrition Investigation (MINI), a study designed to assess nutrition in a population of women and their breastfed children in New Zealand. Twenty mother-infant pairings were selected to provide nail clippings at two time points (visit 1 at 3 months postpartum; visit 2 at 6 months postpartum). Nail clippings from each mother-infant pairing were divided into three groupings of clippings prior to analysis: those obtained from a big toe of the mother, those from the other toes of the mother, and those from the toes and fingers of the infant. Clippings were prepared and mounted prior to XRF measurement, providing four distinct fragments from each clipping grouping. These fragments were assessed by XRF using a measurement time of either 300 s (visit 1) or 180 s (visit 2). XRF results were determined through both an automated system output and an analysis of the X-ray energy spectrum. Following this assessment of zinc and selenium with the non-destructive XRF method, clippings were measured for zinc and selenium concentration using a “gold standard” technique of inductively coupled plasma mass spectrometry (ICP-MS). Mean ICP-MS concentrations ranged from 122 μg/g to 127 μg/g for zinc, and from 0.646 μg/g to 0.659 μg/g for selenium. Precision, assessed by a relative standard deviation of measurement, was superior for ICP-MS relative to XRF. For both zinc and selenium, XRF results were compared with ICP-MS concentrations. Linear equations of best fit were determined for each comparison between XRF and ICP-MS results. Coefficients of determination (r2) were stronger for zinc (from 0.74 to 0.95) than selenium (from 0.53 to 0.70). A decrease in XRF measurement time from 300 s to 180 s did not appear to adversely affect the correlation between XRF and ICP-MS results. Using the mono-energetic portable XRF method, the correlation of XRF zinc results with ICP-MS zinc concentrations was improved over previous findings, and selenium measurement was reported for the first time. The method may prove useful for future applications to trace element analysis using nail clippings as a biomarker.

This review explores the use of Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and X-ray Fluorescence (XRF) for quantifying metals and metalloids in biological matrices such as hair, nails, blood, bone, and tissue. It provides a comprehensive overview of these methodologies, detailing their technological limitations, application scopes, and practical considerations for selection in both laboratory and field settings. By examining traditional and novel aspects of each method, this review aims to guide researchers and clinical practitioners in choosing the most suitable analytical tool based on their specific needs for sensitivity, precision, speed, and sample preparation. Recent studies highlight enhanced capabilities of both ICP-MS and XRF technologies, making them more adaptable to various analytical needs. ICP-MS is renowned for its unmatched sensitivity and precision in detecting ultra-trace metals and metalloids in complex biological samples, such as lead in plasma or seawater. XRF advancements include lower detection limits and reduced sample preparation time, enabling rapid, non-destructive analyses, ideal for quick field assessments. Portable XRF analyzers have revolutionized on-the-spot testing, providing robust data without traditional wet-lab constraints. Moreover, hybrid techniques combining ICP-MS and XRF features are emerging, offering rapid and precise metal analysis for environmental monitoring, clinical diagnostics, and epidemiological studies. Matching analytical methods to specific research demands is critical. ICP-MS is the gold standard for detailed quantitative analysis in laboratories, while XRF excels in non-destructive, immediate field applications. Selection should consider sample complexity, sensitivity, speed, and cost-efficiency. Integrating ICP-MS and XRF offers a versatile approach to metals analysis, transforming practices in environmental science and healthcare diagnostics. As these technologies evolve, they are promising to expand capabilities in detecting and understanding the roles of metals and metalloids in health and the environment.

Particulate matter (PM) concentrations have decreased dramatically over the past 20 years, thus lower method detection limits (MDL) are required for these measurements. Energy-dispersive X-ray fluorescence (XRF) spectroscopy is used to quantify multiple elements simultaneously in the U.S. Environmental Protection Agency (EPA) Chemical Speciation Network (CSN). Inductively-coupled plasma mass spectrometry (ICP-MS) is an alternative analysis with lower MDL for elements. Here, we present a side-by-side comparison of XRF and ICP-MS for elements in PM2.5 samples collected via the EPA’s CSN. For ICP-MS, a simple extraction and ICP-MS analysis technique was applied to a wide variety of samples to minimize effort and cost and serve as a feasibility test for a large monitoring network. Filter samples (N = 549) from various urban locations across the US were analyzed first analyzed via XRF at UC Davis and then ICP-MS at RTI International. Both methods measured 29 of the same elements out of the 33 usually reported to CSN. Of these 29, 14 elements (Na, Mg, Al, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Pb) were found to be frequently detected (i.e. had more than 10% of values above both XRF and ICP-MS MDL). ICP-MS was found to have lower MDL for 26 out of 29 elements, namely Na, Mg, Al, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, As, Se, Rb, Sr, Zr, Ag, Cd, In, Sn, Sb, Cs, Ba, Ce, Pb; conversely, XRF had lower MDL for 3 elements, namely, P, K, Zn. Intra-method quality checks using (1) inter-elemental inspection of scatter plots using a priori knowledge of element sources and (2) scatter plots of routine versus collocated measurements reveal that ICP-MS exhibits better measurement precision. Lower detection limits for element measurements in nationwide PM monitoring networks would benefit human-health and source apportionment research. Implications: We demonstrate that ICP-MS with adilute-acid digestion method would significantly improve the element detection rates and thus be avaluable addition to the current analysis techniques for airborne PM samples in anationwide monitoring network. In this paper, we show that a hybrid method of elemental analysis for airborne particulate matter (PM) would significantly improve the detection rates for elements in PM. This would be a valuable addition to the current analysis techniques for airborne PM samples in nationwide and other large-scale monitoring networks, such as the EPA’s Chemical Speciation Network (CSN). The techniques explored in this study (i.e., X-ray Fluorescence Spectroscopy or XRF and Inductively Coupled Plasma-Mass Spectrometry or ICP-MS) are relevant to the PM monitoring and regulatory community audience of JAWMA, especially agencies and states that are already involved in CSN. In addition, our results outline considerations that give insight on factors to consider for other large-scale and long-term ambient air monitoring efforts.

Adsorption-desorption behavior of difenoconazole onto soils: Kinetics, isotherms, and influencing factors.

To clarify the impact of soil type variability on the quantitative analysis of heavy metals using X-ray fluorescence (XRF), the feasibility of establishing XRF quantitative analysis curves based on 15 different soil types was investigated. Pearson's correlation coefficient was employed to analyze the relationship between the XRF results and soil matrix constituents. The analysis was focused on four specific soil types: grey fluvo-aquic soil, fluvo-aquic soil, purple soil, and rice soil. The differences in the XRF quantitative analysis curves for heavy metals across these soil types were assessed by examining the overlap of the 95% confidence intervals and the cosine distances between the curves. The accuracy of heavy metal content determinations in grey fluvo-aquic soil was evaluated using the quantitative analysis curves derived from the four soil types. It was found that the linear coefficients of determination for the XRF quantitative analysis curves of heavy metals (Zn, Pb, Ni, Cu, Cr, and Cd) established from the 15 soil types were all below 0.2, indicating a poor fit and rendering them unsuitable for accurate analysis. This highlights that variability in soil types, attributed to differences in soil matrix compositions, significantly affects the accuracy of heavy metal quantification by XRF. When the quantitative analysis curves from fluvo-aquic soil, purple soil, and rice soil were applied to assess heavy metal concentrations (Cr, Ni, Cu, Zn, Pb, Cd, As, and Hg) in grey fluvo-aquic soil, significant increases in the average relative errors were noted. Specifically, these errors rose from 9.89%, 8.56%, 13.51%, 7.10%, 9.86%, 26.19%, 6.71%, and 30.97% to the following ranges: 29.74% to 34.80% (minimum 29.74%, maximum 34.80%), 59.82% to 96.34%, 41.12% to 78.33%, 25.33% to 32.64%, 16.92% to 70.36%, 24.07% to 68.79%, 48.91% to 128.98%, and 130.29% to 238.70%, increasing as much as 0.11 to 18.22 times. Such increases indicate that variability among soil types greatly impacts the accuracy of heavy metal quantitative analysis using XRF. This study establishes an important foundation for the precise quantitative detection of heavy metals via XRF across various soil types.

Objective: Metal exposures have been linked with many adverse health outcomes affecting nearly every system in the body. Exposure to metals has been tracked primarily using blood. Blood metal concentrations have drawbacks as biomarkers stemming from the metals’ short biologic half-lives, shipping and storage requirements, and invasive collection procedures. Toenails, which capture a longer exposure period, can be collected non-invasively and stored at room temperature, and can be more feasible and cost-effective for large-scale population studies. Approach: Inductively coupled plasma mass spectrometry (ICP-MS) has been used for analysis of toenail metal concentrations, but x-ray fluorescence (XRF) has many advantages in versatility and cost effectiveness over these analyses. This study compared toenail concentrations of manganese (Mn) and lead (Pb) measured with XRF against ICP-MS, in samples collected from 20 adults in Nigeria. To do this we developed a novel calibration method that corrects XRF measurements for toenail weight and thickness to reduce the variability in XRF measurements of toenail clippings. Main results: We found a high correlation (R = 0.91) between toenail manganese metal measurements made with XRF and ICP-MS and a correlation of (R = 0.32) between toenail lead XRF and ICP-MS with over half of the lead results below the detection limit of the instrumentation. Significance: XRF can be used effectively to quantify metals at the part per million level or lower depending on the XRF equipment used in the measurements.

Soil contamination by potentially toxic elements (PTEs) poses a major environmental concern. The distribution and concentration of these elements can vary significantly in polluted areas, making detailed assessments crucial. A comprehensive analysis is essential to accurately characterise contamination patterns, as a foundation for effective site evaluation and remediation efforts. This study evaluates the effectiveness and reliability of X-ray fluorescence (XRF) and inductively coupled plasma mass spectrometry (ICP-MS) for determining PTEs in soil samples. Statistical analyses reveal significant differences between the two techniques for Sr, Ni, Cr, V, As, and Zn, likely due to variations in detection sensitivity, calibration methods, or matrix effects. Pb exhibits a weaker difference, suggesting a potential, yet statistically insignificant, difference between methods. Correlation analyses indicate a strong linear relationship for Ni and Cr, while Zn and Sr display high variability, limiting direct comparability. Bland–Altman plots highlight systematic biases, particularly for V, where XRF consistently underestimates concentrations compared to ICP-MS. These findings underscore the importance of selecting the appropriate analytical technique based on detection limits, sample characteristics, and measurement reliability. While both methods provide valuable insights for environmental monitoring, carefully considering their limitations is crucial for accurate contamination assessment.

Influence of soil texture and organic matter content on bulk density, air content, compression index and crop yield in field and laboratory compression experiments

X-ray fluorescence (XRF) imaging for metal nanoparticles (MNPs) is a promising molecular imaging modality that can determine dynamic biodistributions of MNPs. However, it has the limitation that it only provides functional information. In this study, we aim to show the feasibility of acquiring functional and anatomic information on the same platform by demonstrating a dual imaging modality of pinhole XRF and computed tomography (CT) for gold nanoparticle (GNP)-injected living mice. By installing a transmission CT detector in an existing pinhole XRF imaging system using a two-dimensional (2D) cadmium zinc telluride (CZT) gamma camera, XRF and CT images were acquired on the same platform. Due to the optimal X-ray spectra for XRF and CT image acquisition being different, XRF and CT imaging were performed by 140 and 50kV X-rays, respectively. An amount of 40mg GNPs (1.9nm in diameter) suspended in 0.20ml of phosphate-buffered saline were injected into the three BALB/c mice via a tail vein. Then, the kidney and tumor slices of mice were scanned at specific time points within 60min to acquire time-lapse in vivo biodistributions of GNPs. XRF images were directly acquired without image reconstruction using a pinhole collimator and a 2D CZT gamma camera. Subsequently, CT images were acquired by performing CT scans. In order to confirm the validity of the functional information provided by the XRF image, the CT image was fused with the XRF image. After the XRF and CT scan, the mice were euthanized, and major organs (kidneys, tumor, liver, and spleen) were extracted. The ex vivo GNP concentrations of the extracted organs were measured by inductively coupled plasma mass spectrometry (ICP-MS) and L-shell XRF detection system using a silicon drift detector, then compared with the in vivo GNP concentrations measured by the pinhole XRF imaging system. Time-lapse XRF images were directly acquired without rotation and translation of imaging objects within an acquisition time of 2min per slice. Due to the short image acquisition time, the time-lapse in vivo biodistribution of GNPs was acquired in the organs of the mice. CT images were fused with the XRF images and successfully confirmed the validity of the XRF images. The difference in ex vivo GNP concentrations measured by the L-shell XRF detection system and ICP-MS was 0.0005-0.02% by the weight of gold (wt%). Notably, the in vivo and ex vivo GNP concentrations in the kidneys of three mice were comparable with a difference of 0.01-0.08wt%. A dual imaging modality of pinhole XRF and CT imaging system and L-shell XRF detection system were successfully developed. The developed systems are a promising modality for in vivo imaging and ex vivo quantification for preclinical studies using MNPs. In addition, we discussed further improvements for the routine preclinical applications of the systems.

Portable X-ray fluorescence of zinc and selenium with nail clippings - visit 3 of the Mother and Infant Nutrition Investigation (MINI).

The ln(Zr/Rb) count ratio derived from X‐ray fluorescence (XRF) core scanning holds potential as a high‐resolution tracer for grain‐size variations of glaciomarine sediments, and hence current strength. To evaluate this approach, we conducted high‐resolution grain‐size measurements, together with Rb and Zr measurements by XRF core scanning and inductively coupled plasma‐mass spectrometry (ICP‐MS), on a series of sediment cores from different regions of the Southern Ocean. Downcore changes of the ln(Zr/Rb) count ratio from XRF core scanning are consistent with Zr/Rb concentration ratios derived from ICP‐MS analyses, even though Rb and Zr counts deviate significantly from concentrations due to specimen and matrix effects. The ln(Zr/Rb) count ratio displays discrepancies with the bulk mean grain‐size, but correlates well with the mean grain‐size of the sediment fractions that do not include unsorted sand delivered by ice‐rafting. These observations are supported by evidence from a grain‐size separation experiment, which indicates that Zr and Rb are concentrated in different grain‐size fractions. Consistent with its lack of sensitivity to coarse grain‐size fractions derived from ice‐rafting, the ln(Zr/Rb) ratio records similar trends to the sortable silt percent (SS%) and sortable silt mean ( ) grain‐size. Universal gradients exist in plots of SS% versus ln(Zr/Rb), and versus ln(Zr/Rb), such that the ln(Zr/Rb) ratio provides a convenient way to estimate the magnitude of changes in SS% and . Overall, our results support the use of the ln(Zr/Rb) ratio as an indicator of bottom current strength in cases where the sediment is current‐sorted.

Structural characterization of humic acids isolated from typical soils in China and their adsorption characteristics to phenanthrene

Comparison of two conventional analytical techniques such as X-ray fluorescence (XRF) and inductively coupled plasma mass spectrometry (ICP-MS) for measuring Pb concentrations in soil samples was achieved using field and laboratory work. Seventy-three samples were collected from urban areas surrounding the large lead smelter at South Australia, as an indicator of the environment impact of smelter activity. Soil Pb concentrations were determined using hand-held XRF analyser under laboratory conditions. ICP-MS analysis on digested soils (using a microwave-assisted nitric acid digestion-extraction) was applied to validate p-XRF data. The analysis showed that Pb concentrations determined by XRF correlated with high linearity with Pb concentrations determined by ICP-MS measurements (R2 = 0.89). Statistical test (t test) was applied to the data of both methods applied without any significant difference between the two techniques. These results indicated that ICP-MS corroborated XRF for Pb soil measurements and suggests that XRF was a reliable and quick alternative to traditional analytical methods in studies of environmental health risk assessment, allowing for much larger sampling regimes in relatively shorter times and could be applied in the field.

Soil microaggregate size composition and organic matter distribution as affected by clay content