As a technique capable of rapid, nondestructive, and multi-elemental analysis, portable X-ray fluorescence (pXRF) has applications to mineral exploration, environmental evaluation, and archaeological analysis. However, few applications have been conducted in the smelting industry especially when analyzing the metal concentration in ore concentrate samples. This research analyzed the effectiveness of using pXRF in determining the metal concentration in Fe concentrate. For this proof of concept study, Fe ore samples dominated by Fe and Si were collected from the Northeastern University Mineral Processing Laboratory (Shenyang, China) and directly analyzed using pXRF, laboratory-based XRF, and titration methods. The compactness (density) of the ore concentrate was found to have very little effect on pXRF readings. The pXRF readings for Fe and Si were comparative to laboratory-based XRF results. Based on the strong correlations between the pXRF and XRF results (Fe: R ² > 0.99, Si: R ² > 0.96), linear calibrations were adopted to improve the accuracy of pXRF readings. Linear regression equations derived from the relations between XRF results and pXRF results of 21 Fe ore concentrate samples were used to calibrate the pXRF, and then validation was performed on five additional samples. Results from this preliminary study suggest that ordinary least squares (OLS) regression improves the accuracy dramatically, especially for Fe with relative errors (REs) decreasing to 0.03%–3.27% from 4.26%–8.32%. Consequently, pXRF shows strong promise for rapid, quantitative analysis of Fe concentration in Fe ore concentrate. Based on the results obtained in this study, a larger, more comprehensive study is warranted to confirm the results obtained.

In the study of the inversion of soil multi-species heavy metal element concentrations using hyperspectral techniques, the selection of feature bands is very important. However, interactions among soil elements can lead to redundancy and instability of spectral features. In this study, heavy metal elements (Pb, Zn, Mn, and As) in entisols around a mining area in Harbin, Heilongjiang Province, China, were studied. To optimise the combination of spectral indices and their weights, radar plots of characteristic-band Pearson coefficients (RCBP) were used to screen three-band spectral index combinations of Pb, Zn, Mn, and As elements, while the Catboost algorithm was used to invert the concentrations of each element. The correlations of Fe with the four heavy metals were analysed from both concentration and characteristic band perspectives, while the effect of spectral inversion was further evaluated via spatial analysis. It was found that the regression model for the inversion of the Zn elemental concentration based on the optimised spectral index combinations had the best fit, with R² = 0.8786 for the test set, followed by Mn (R² = 0.8576), As (R² = 0.7916), and Pb (R² = 0.6022). As far as the characteristic bands are concerned, the best correlations of Fe with the Pb, Zn, Mn and As elements were 0.837, 0.711, 0.542 and 0.303, respectively. The spatial distribution and correlation of the spectral inversion concentrations of the As and Mn elements with the measured concentrations were consistent, and there were some differences in the results for Zn and Pb. Therefore, hyperspectral techniques and analysis of Fe elements have potential applications in the inversion of entisols heavy metal concentrations and can improve the quality monitoring efficiency of these soils.

This research explored the feasibility of using portable X-ray fluorescence (pXRF) spectrometry to quantify Fe, Cu, Zn, and As concentrations in dried and ground organic materials (fungi, vegetation, and animal tissues) with intermediate thickness.

Determination of elemental concentrations in animal tissues is critically important due to the extensive use of animal tissues in food and medicine. Traditionally, elemental analysis has mostly relied on laboratory-based methods, such as inductively coupled plasma atomic emission spectrometry (ICP-AES) and inductively coupled plasma mass spectrometry (ICP-MS). Portable X-ray fluorescence (XRF) spectrometry, which has been widely applied in soil and rock analysis, has rarely been used to quantify elements in animal tissues. In this pilot study, the effectiveness of using pXRF to determine elemental concentrations in leeches was demonstrated. The effects of the moisture content and compaction (density) on pXRF readings were experimentally quantified. The penetration depth of X-rays in leech samples is generally <15 mm. For leech samples with different thicknesses (thicknesses ranging from 2.5 mm to 15 mm), measured pXRF elemental concentrations were found to decrease with increasing sample thickness in a power function, the square of the correlation coefficient (R²) of which was 0.96 and 0.89 for Zn and Fe, respectively. Therefore, the thickness correction for intermediate sample thickness is possible in future analysis, enabling a more accurate analysis for samples with insufficient sample mass. The detection limits determined for As and Cu in dried and ground leech samples with a thickness of ∼15 mm were ∼5 and ∼20 mg kg⁻¹, respectively, which were equal to/lower than the regulatory limits for both food and medicine. The pXRF measured concentrations of S, K, Fe, Cu, Zn, and As were highly correlated with ICP results (R² ≥ 0.92), with the exception of Ca (R² = 0.81). Simple linear regression models were employed to predict the ICP-based elemental composition of 15 leech samples using pXRF elemental data as inputs; the validation results were quite good for all the studied elements (R² ≥ 0.92). Thus, pXRF shows great potential for safety control of elemental concentrations in food and medicine.

This case study employed portable X-ray fluorescence (pXRF) spectrometry to evaluate elemental concentrations in edible mushrooms from the Bailing Cu–Zn mining area, China, and micro-X-ray fluorescence (micro-XRF) imaging to document elemental spatial extent in mushroom samples. pXRF-determined concentrations were calibrated, and the mean relative errors (MREs) after calibration were <14% for all elements (S, K, Ca, Cu, Zn, As and Rb) except for Fe (MRE = 20%). Arsenic concentrations in Lepista nuda (wood blewit) from mining areas reached 42 mg kg ⁻¹ , significantly higher than nearby non-mining areas (2–5 mg kg ⁻¹ ) and far exceeding the Chinese food safety limit of 0.5 mg kg ⁻¹ . Arsenic concentrations in wood blewits were positively correlated with soil As levels (coefficient of determination (R ² ) = 0.434, P < 0.01), highlighting their potential as bioindicators for mineral exploration. Copper concentrations in Lepista nuda were also high, with some reaching up to 548 mg kg ⁻¹ . Micro-XRF imaging reveal that Cu is primarily concentrated on the margin (edge) of the cap of wood blewits. Mining activities in the research area caused elevated As and Cu concentrations in wild edible mushrooms ( Lepista nuda and Armillaria gallica ), posing a significant health risk to local residents through mushroom consumption as a pathway for toxic exposure.