Portable X-ray Fluorescence Spectrometer Research Articles

Adding Rare Earth Oxide Markers to Polyoxymethylene to Improve Plastic Recycling through Tracer-Based Sorting.

Engineering plastics, such as polyoxymethylene (POM), are high-performance thermoplastics designed to withstand high temperature or mechanical stress and are used in electronic equipment, the automotive industry, construction, or specific household utensils. POM is immiscible with other plastics but due to a low volume of production, no methods were developed to separate it from the residual plastic waste stream. Therefore, POM recycling is minimal despite its high market value. This paper provides a proof of concept for tracer-based sorting (TBS) as a potential solution for increasing the separation efficiency of low-volume, high-quality polymers. For this purpose, yttrium oxide (Y2O3) and cerium (IV) oxide (CeO2) have been embedded into the POM matrix. Mechanical tests of samples at varying concentrations (0.1 to 1000 ppm) of both tracers were conducted, followed by an analysis of detectability and dispersibility using a portable X-ray fluorescence spectrometer (p-XRF), subsequently optimizing detection time and tracer concentration. Finally, an experimental scenario was developed to test the fate and potential recovery of the tracer material after the thermal treatment of plastics. A low detectable concentration, short measurement time, low influence on mechanical parameters of the compound, and low loss ratio after simulated recycling prove Y2O3 to be a suitable tracer for the industrial implementation of TBS.

Advancing Leaf Nutritional Characterization of Blueberry Varieties Adapted to Warm Climates Enhanced by Proximal Sensing

Blueberries offer multiple health benefits, and their cultivation has expanded to warm tropical regions. However, references for foliar nutritional content are lacking in the literature. Proximal sensing may enhance nutritional characterization to optimize blueberry production. We aimed (i) to characterize the nutrient contents of healthy plants of three blueberry varieties adapted to warm climates (Emerald, Jewel, and Biloxi) using a reference method for foliar analysis (inductively coupled plasma (ICP)) and a portable X-ray fluorescence (pXRF) spectrometer on fresh and dry leaves and (ii) to differentiate blueberry varieties based on their nutrient composition. Nutrient content was statistically compared per leaf moisture condition (fresh or dry) with ICP results and used to differentiate the varieties via the random forest algorithm. P and Zn contents (ICP) in leaves were different among varieties. Dry leaf results (pXRF) were strongly correlated with ICP results. Most nutrients determined using ICP presented good correlation with pXRF data (R2 from 0.66 to 0.93). The three varieties were accurately differentiated by pXRF results (accuracy: 87%; kappa: 0.80). Predictions of nutrient contents based on dry leaves analyzed by pXRF outperformed those based on fresh leaves. This approach can also be applied to other crops to facilitate nutrient assessment in leaves.

Rapid detection and risk assessment of soil contamination at lead smelting site based on machine learning

A general prediction model for seven heavy metals was established using the heavy metal contents of 207 soil samples measured by a portable X-ray fluorescence spectrometer (XRF) and six environmental factors as model correction coefficients. The eXtreme Gradient Boosting (XGBoost) model was used to fit the relationship between the content of heavy metals and environment characteristics to evaluate the soil ecological risk of the smelting site. The results demonstrated that the generalized prediction model developed for Pb, Cd, and As was highly accurate with fitted coefficients (R2) values of 0.911, 0.950, and 0.835, respectively. Topsoil presented the highest ecological risk, and there existed high potential ecological risk at some positions with different depths due to high mobility of Cd. Generally, the application of machine learning significantly increased the accuracy of pXRF measurements, and identified key environmental factors. The adapted potential ecological risk assessment emphasized the need to focus on Pb, Cd, and As in future site remediation efforts.

Assessment of marine and urban-industrial environmental impact on stone acting as the base of a quaternary bronze sculpture

This work investigates the influence of a marine and urban-industrial environment on the deterioration of a funerary memorial in Getxo (Basque Country, Spain). The sculpture and artificial stone materials as well as their degradation products were characterised via a multi-analytical approach. An in situ characterisation of the bronze statue and its artificial limestone base was carried out with portable Energy Dispersive X-Ray Fluorescence (ED-XRF) and Raman spectrometers. In addition, several samples of white crusts as well as metal runoff crusts and biological patina were collected and some of them were prepared as cross-sections. High Resolution Micro-X-ray fluorescence and micro-Raman spectroscopy were used as non-destructive methods to detect original and degradation compounds. The test of soluble salts was also carried out on the samples and ion chromatography was employed in the laboratory. Exclusively calcite salt-efflorescences were found at the monument side with ED-XRF and Raman spectroscopy. While their morphology was compact at unsheltered sites, they showed a lamellar structure at sheltered locations, whose increased volume strongly influences the destruction of the memorial. The spectroscopic characterization of metal runoff showed that its excessive occurrence on the memorial surface was due to the dissolution of the copper-alloy caused by chemical reactivity with the surrounding acidic atmosphere. The formation of brochantite Cu4(SO4)(OH)6, posnjakite Cu4(SO4)(OH)6·(H2O), langite Cu4(SO4)(OH)6·2(H2O), or malachite Cu2(CO3)(OH)2 was favored exclusively in metal runoff crusts at unsheltered locations. However, much thinner crusts collected at sheltered sites showed a different composition, with copper species such as moolooite (Cu(C2O4)·nH2O) and atacamite Cu2Cl(OH)3. The soluble salt extraction showed a variable concentration of soluble ions depending on the area where the samples come from. The sample from north west sheltered location showed the highest content of sulfate, nitrate and chloride compounds. In addition, the concentration of fluoride and nitrate reflects the impact of contamination of surrounding industries.

Modeling soil moisture from in situ portable X-ray spectrometer measurements: A novel approach for correcting geochemical data across different environments and climatic conditions

The portable X-ray fluorescence (pXRF) spectrometer is widely employed for in situ analysis of both contaminated and uncontaminated soils. However, the accuracy of the measurements can be significantly affected by soil moisture, resulting in unreliable soil pollution monitoring. This effect has already been studied and quantified, but this is ineffective if the soil moisture in the field is unknown. Given the considerable variability of soil moisture conditions across time and space, significant bias during in situ investigations remains a main issue. This study introduces a novel method to estimate soil moisture directly from pXRF field measurements, enabling its reliable use in almost any field condition. The study was conducted using soil samples and in situ pXRF soil surface measurements in Estarreja (Portugal) and Vicdessos (France). In the first experiment, the innovative approach involved modeling soil moisture directly from the raw XRF measurement errors obtained in moist soils using multiple regression. In the second experiment, metal concentrations were modeled as an exponential function of the moisture content. The final model integrates both approaches to correct field data from geochemical mapping in diverse environments, including a coastal region in Portugal and a mountainous region in France. Our findings demonstrate that this simple, efficient and cost-effective method accurately predicts soil moisture (U) using pXRF, as shown by the equation Umeasured = 1.0028 x Uestimated (r2 = 0.9715). The model effectively corrected up to 70% of moisture-induced errors in metal concentrations in the wettest soils and produced more reliable soil Fe, Pb, and Zn maps. Specifically, the accuracy improvement was at least 32% in drier soils (Portugal) and at least 55% in wetter soils (France). This study offers a cost-effective, efficient solution for employing pXRF in geochemical mapping across different climatic conditions and soil environments.

The use of a portable X-ray fluorescence spectrometer for measuring nickel in plants: sample preparation and validation.

X-ray fluorescence is a fast, cost-effective, and eco-friendly method for elemental analyses. Portable X-ray fluorescence spectrometers (pXRF) have proven instrumental in detecting metals across diverse matrices, including plants. However, sample preparation and measurement procedures need to be standardized for each instrument. This study examined sample preparation methods and predictive capabilities for nickel (Ni) concentrations in various plants using pXRF, employing empirical calibration based on inductively coupled plasma optical emission spectroscopy (ICP-OES) Ni data. The evaluation involved 300 plant samples of 14 species with variable of Ni accumulation. Various dwell times (30, 60, 90, 120, 300s) and sample masses (0.5, 1.0, 1.5, 2.0g) were tested. Calibration models were developed through empirical and correction factor approaches. The results showed that the use of 1.0g of sample (0.14gcm-2) and a dwell time of 60s for the study conditions were appropriate for detection by pXRF. Ni concentrations determined by ICP-OES were highly correlated (R2 = 0.94) with those measured by the pXRF instrument. Therefore, pXRF can provide reliable detection of Ni in plant samples, avoiding the digestion of samples and reducing the decision-making time in environmental management.

A feasible approach to measure metal concentrations in drill hole waters on site for mineral exploration

The new technologies used in the green transition towards carbon-free societies typically demand extensive use of metals. This leads to a heavily growing need for exploration and extraction of ore deposits. Exploration can be facilitated by measuring metal concentrations in ground and surface waters carrying trace concentrations of metals leached from nearby deposits. Currently, measuring metal concentrations in water is slow and expensive and it cannot be done on-site, which hinders the discovery of new ore deposits. To address this challenge, we have developed a method to collect and concentrate the dissolved metals in a solid filter and measure the metal concentrations directly from the filter with a portable X-ray fluorescence spectrometer. The permeable filter is made of mesoporous silicon modified with bisphosphonates. Two types of adsorbing materials for the filters were prepared based on scalable production methods: i) regenerative etching of metallurgical grade silicon powder, and ii) magnesiothermic reduction of silica from barley husks. Empirical calibrations were prepared in a concentration range of 10–200 μg/L for Mn, Co, Ni, Cu, Zn, and Pb using water samples prepared by spiking well water with standard metal solutions. Both filter types were tested for their ability to adsorb metals from the real water samples taken from drill holes. The developed system was able to detect metal concentrations down to 12 μg/L (ppb) showing its potential for on-site measurements of dissolved metals in water samples, which could be feasible in the discovery of new mineral deposits. This innovation enables smart sampling during exploration and provides real-time information on metal concentrations in water.

The use of computed tomography and X-ray fluorescence analysis in the research of printed book from the seventeenth century: book binding, tomographic reading of the text, dendrochronological dating, pigments analysis

This paper presents the use of X-ray computed tomography and X-ray fluorescence in the analysis and expert research of the seventeenth century printed book "Eukhologīon albo Molitoslov, ili Trebnik" from Kiev. The main purpose of the survey was to confirm whether the book binding is original or whether it is a rebinding, and whether there are any fragments of the hidden older texts. Commonly used radiography is usually not able to provide sufficient information for these purposes. On the other hand, computed tomography allows a detailed and three-dimensional documentation of the bookbinding technology and the structure of the materials used, including the wooden boards. It will be presented that all elements of the weave are clearly visible, making it possible to show that there are no internal defects in the stitching and materials. It has also been convincingly shown that there are no fragments or layers of older texts in the binding, so no further invasive intervention will be necessary regarding this aspect. The paper also demonstrates the possibility of reading the text in a closed book utilising X-ray computed tomography data; this option may be advantageous for massively damaged manuscripts. It will also be shown, that thanks to detailed tomographic imaging of the wood structure of the boards, a dendrochronological survey can be successfully carried out without invasive intervention into their outer layers. From the CT data it was also found that the pigments of the letters have significantly different densities. Therefore, as part of the survey, elemental analysis of the writing was also carried out using a portable X-ray fluorescence spectrometer to confirm and clarify this finding.

Recognition of Yuan blue and white porcelain produced in Jingdezhen based on graph anomaly detection combining portable X-ray fluorescence spectrometry

The blue and white porcelain produced in Jingdezhen during China’s Yuan Dynasty is an outstanding cultural heritage of ceramic art that has attracted wide attention for its identification. However, the traditional visual identification method is susceptible to misjudgment, thermoluminescence dating damages the samples, and the methods based on chemical analysis are limited by the accuracy and specificity of the elemental features. In this paper, we address the identification challenge by using machine learning techniques combined with portable X-ray Fluorescence Spectrometer (pXRF) analysis. We collect a large dataset of chemical compositions of Yuan blue and white porcelain from Jingdezhen using pXRF, and propose a graph anomaly detection method based on gradient attention map (GRAM) to identify the porcelain from different dynasties. We treat the porcelain produced in the Yuan dynasty as normal samples and those from other dynasties as abnormal samples. For GRAM, we merely train the variational graph autoencoder (VGAE) model with normal graphs and then use its encoder to extract graph features and compute the anomaly scores by utilizing the GRAM of the graph representations with respect to the node feature embeddings. Finally, we compare GRAM with state-of-the-art graph anomaly detection techniques and show that it achieves superior performance.

Lateral and temporal constraints on the depositional history of the Bonneville Salt Flats, Utah, USA

Abstract The depositional history of the Bonneville Salt Flats, a perennial saline pan in Utah's Bonneville basin, has poor temporal constraints, and the climatic and geomorphic conditions that led to saline pan formation there are poorly understood. We explore the late Pleistocene to Holocene depositional record of Bonneville Salt Flats cores. Our data challenge the assumption that the saline pan formed from the desiccation of Lake Bonneville, the largest late Pleistocene lake in the Great Basin, which covered this area from 30 to 13 cal ka BP. We test two hypotheses: whether climatic transitions from (1) wet to arid or (2) arid to wet led to saline pan deposition. We describe the depositional record with radiocarbon dating, sedimentological structures, mineralogy, diatom, ostracode, and portable X-ray fluorescence spectrometer measurements. Gypsum and carbonate strontium isotope ratio measurements reflect changes in water sources. Three shallow saline lake to desiccation cycles occurred from >45 and >28 cal ka BP. Deflation removed Lake Bonneville sediments between 13 and 8.3 cal ka BP. Gypsum deposition spanned 8.3 to 5.4 cal ka BP, while the oldest halite interval formed from 5.4 to 3.5 cal ka BP during a wetter period. These findings offer valuable insights for sedimentologists, archaeologists, geomorphologists, and land managers.

Robust parameter design of the measurement procedure for determining the chemical composition of copper alloys by X-ray fluorescence

A brief overview of contemporary methods for determining the chemical composition of copper alloys and the analytical control methods used is given. It has been shown that to obtain reliable and comparable results of measuring the mass fractions of copper alloys elements in wide ranges of values, the most suitable procedures are based on the X-ray fluorescence method, implemented using portable X-ray fluorescence spectrometers. In order to select the optimal values of the influencing quantities when determining the chemical composition of copper alloys, a robust parameter design of a quantitative chemical analysis procedure was carried out on the X-50 Mobile X-ray fluorescence spectrometer. The use of robust parameter design, as opposed to conducting a full factorial experiment when developing a measurement procedure, makes it possible to optimize measurement conditions and obtain results of the required accuracy with a limited number of experiments and a maximum number of control factors. An example of drawing up an experimental plan for the parameter design of this procedure is given and a statistical analysis of the measurement results is carried out. The optimal measurement conditions (influencing quantities) were analyzed and selected, under which the minimum error in the results of measuring the mass fraction of elements is ensured. The selection of optimal values of the influencing quantities based on the results of robust parameter design of the quantitative chemical analysis procedure made it possible to increase the accuracy of the results of determining the chemical composition of copper alloys and, as a consequence, the reliability of the results of product quality control at relatively low costs for its implementation. This approach can be recommended to analytical laboratories developing procedures of quantitative chemical analysis for metallurgical industry enterprises.

X-ray fluorescent method for the analysis of trace elements in bio-materials with correction of the matrix effect.

A method for correcting the matrix effect by measuring the intensity of fluorescent radiation and its absorption by the sample material in the same x-ray optical scheme is proposed. The use of a complex secondary Ag-Ge emitter as a primary radiation source provides a low detection limit for a wide range of chemical elements from Ca (Z = 20) to Mo (Z = 42) in the K-series and from Cd (Z = 48) to Bi (Z = 83) in the L-series. To measure the absorption, the radiation of an additional secondary emitter is used, of which the wavelengthcan be varied in the range from 0.633 to 3.38 Å, depending on the measured impurity. An example of determining the mass fraction of an impurity in a sample of unknown composition prepared from a mixture of state standard samples of aqueous solutions is given. The x-ray optical scheme was assembled on the basis of a portable Energy Dispersive X-ray Fluorescence(EDXRF) spectrometer. The method is designed to study materials with a base consisting of chemical elements with a low atomic number.

Comparative analysis and visualization of soil profiles at the meter spatial scale utilizing novel matrix and volume rendering techniques

This research introduces a soil characterization technique involving four data visualization tools to help researchers and stakeholders interpret high dimensional soil data at the field scale. This technique involves visualizing a reduced dimensionality representation of elemental concentration and color data gathered via portable X-ray fluorescence (pXRF) spectrometer and NixPro color proximal sensors, respectively. Soil cores were collected from sites located in Lubbock and Lamb Counties, West Texas, USA. Thirteen core samples were collected from these sites in a star pattern with readings from proximal sensors at depths ranging between 0 and 100 cm at 10 cm intervals. The dimensionality reduction techniques utilize four visualization tools to represent soil composition data through multiple user-adjustable variables (i.e., mg kg−1 elemental concentrations and soil profiles), offering more insight and control compared to a single-variable approach. Through these tools and techniques, qualitative and quantitative conclusions regarding soil characteristics (e.g., elemental concentration variation, delineation of soil horizons, changes in soil color) can be formulated from the data and used in various applications. Areas where these novel software tools can be utilized potentially include rapid contaminant mapping in soils, characterization of diagnostic soil horizons (e.g., calcic, spodic, gypsic, etc.), micronutrient distribution at a field scale for precision agricultural purposes, and pedometrics.

Portable EDXRF spectrometer: determination of linearity, LOD, LOQ, and working range for the analysis of base and precious metals in liquid matrices

Utilizing a portable energy dispersive X-ray fluorescence (EDXRF) spectrometer and certified reference materials, this study aimed to determine the linearity, limit of detection (LOD), limit of quantification (LOQ), and working range of the method for quantitative analysis of base and precious metals in liquid matrices. As the EDXRF method lacks standardization and is highly susceptible to matrix effects, these calculations play a crucial role in the analytical validation process. The obtained R2 values in this study exceeded 0.99, and the residuals exhibited a random distribution pattern. The LOD and LOQ values were determined to be exceptionally low, approaching the resolution limit of the spectrometer. Consequently, our calculations confirmed the analytical validation of the portable EDXRF method for analyzing elements in liquid matrices. The utilization of portable EDXRF equipment in quantitative measurements of elements in liquid matrices represents an innovative approach, unveiling new areas of application for this type of instrument.

Uncovering the effects of Urmia Lake desiccation on soil chemical ripening using advanced mapping techniques

Urmia Lake in Iran has been gradually drying up since the 2000 s, revealing soil that was once underwater. There is limited research on how this drying process affects the distribution of soil chemical ripening in the lakebed sediments. To investigate this, 131 surface soil samples were collected in July 2017 from six zones based on their distance from the lake's shoreline. Elemental concentrations in the samples were measured using a portable X-ray fluorescence (XRF) spectrometer. Five geochemical indices (GCIs) were calculated: Titanium/Zirconium, Barium/Strontium, Silicon/Aluminium, Silicon/R2O3, and the Darmody index. A remote sensing image (Landsat-8 OLI) from the same sampling period was used as environmental covariates to explain the spatial distribution of GCIs. Random forests (RF) and cubist tree models were employed to model and map these GCIs. The bootstrapping method was used to assess the uncertainty of the maps. Results indicated that the RF model performed better than the cubist model based on the concordance values in the validation dataset. Remotely sensed clay minerals ratio and normalized burn ratio were identified as the most significant covariates in making predictions. The study found that the distribution of all geochemical indices was directly related to their distance from the shoreline. Ba/Sr emerged as the best index for detecting soil chemical ripening in the study area. The index displayed the most significant differences between the drying zones. This research demonstrated that combining satellite imagery with GCIs using the digital soil mapping (DSM) technique can effectively detect soil ripening progression.

Laboratory comparison of field portable X-ray fluorescence spectrometer (FP-XRF) and inductively coupled plasma mass spectrometry (ICP-MS) for determination of airborne metals in stainless steel welding fume

Welding fume is a common exposure in occupational settings. Gravimetric analysis for total particulate matter is common; however, the cost of laboratory analyses limits the availability of quantitative exposure assessment for welding fume metal constituents in occupational settings. We investigated whether a field portable X-ray fluorescence spectrometer (FP-XRF) could provide accurate estimates of personal exposures to metals common in welding fume (chromium, copper, manganese, nickel, vanadium, and zinc). The FP-XRF requires less training and is easier to deploy in many settings than traditional wet laboratory analyses. Filters were analyzed both by FP-XRF and inductively coupled plasma mass spectrometry (ICP-MS). We estimated the FP-XRF limit of detection for each metal and developed a correction factor accounting for the non-uniform deposition pattern on filter samples collected with an Institute of Medicine (IOM) inhalable particulate matter sampler. Strong linear correlation was observed for all metals (0.72<r < 0.96). The median percent bias for chromium and nickel was less than 15%. The linear slope between the two methods for some metals (copper, manganese, and zinc) was greater than 1, indicating that the FP-XRF overestimated metal mass (median percent bias for vanadium was the largest at 94%), but the linearity of the response suggests that appropriate correction factors could be developed.

Sumaki Höyük (Batman, Türkiye) Neolitik Yerleşiminde Bulunan Bazalt Parçalarının Çok Perspektifli Jeokimyasal ve Mineralojik Analizi

This study aims to determine the provenance of grinding stone tools unearthed from the Neolithic phases of Sumaki Höyük settlement using a portable Energy Dispersive X-ray Fluorescence Spectrometer (P-EDXRF) and X-ray Diffraction spectrometer (XRD). Sumaki Höyük is located in the Lower Garzan Basin of Batman province, Turkey. The settlement is dated to 9084 - 8123 cal BP. Grinding stone tools in this settlement are usually made of basalt. Albeit at low amounts, limestone was also used in the production of grinding stones. The Lower Garzan Basin, located to the east of Diyarbakır Basin, is surrounded by Mount Kıradağı and Mount Raman to the west and the Garzan and Kentalan Anticlinal to the east with Kıradağı extending in a northwest-southeast direction. The basalt flow occurred in the Quaternary period. Samples collected from different parts of the Neolithic phase of Sumaki Höyük and the Kıradağı basalt flows were analyzed using P-EDXRF to determine their chemical composition. The same samples were also analyzed using XRD to determine their mineral composition. P-EDXRF and XRD analyses reveal that the samples from Sumaki Höyük and Kıradağı are in good accordance with each other. It is therefore understood that the basalt stone tools used in the settlement were taken from the Kıradağı basalts. Data gathered on the characteristics of potential source locations provide an insight into the settlement strategy and mobility of Neolithic communities.

Soil parent material spatial modeling at high resolution from proximal sensing and machine learning: A pilot study

Although parent material (PM) is one of the five soil formation factors providing key information on soil variability, the complexity of PM distributions and the difficulty of reaching PM in deep soils prevent its detailed assessment. Proximal sensors such as portable X-ray fluorescence (pXRF) spectrometer and magnetic susceptibility (MS) may be helpful in predicting soil PM in a more practical and accessible way. This pilot study aimed to create spatial PM predictive models for three distinct PMs (charnockite, mudstone, and alluvial sediments) of an experimental farm (Brazil) through random forest (RF) algorithm based on soil samples analyzed via pXRF and MS. Soils were sampled in A and B horizons following a regular-grid design covering the whole study area. The RF algorithm was calibrated to predict PMs using samples from the B horizon of soils with known PM. The prediction model was applied to the area for mapping PM across the whole farm. For validation, PM was identified at 15 different sites and compared with the predicted PM shown on the maps via overall accuracy, Kappa coefficient, producer's and user's accuracies. Al, Fe, Si, Ti, and MS proximal sensor data discriminated well among soils derived from charnockite, mudstone, and alluvial sediments. The map built based on B horizon data showed greater accuracy (overall accuracy = 0.93, Kappa coefficient = 0.85, user's accuracy = 0.92, and producer's accuracy = 0.97) than the map built from the model using A horizon samples (0.73, 0.48, 0.48, and 0.58). These results could represent alternative methods for reducing costs and accelerating the assessment of soil PM spatial variability, supporting soil mapping, and optimized agronomic and environmental decision-making.

Metal accumulation patterns in Pittsburgh, PA (United States) green infrastructure soils: road connections and legacy soil inputs

Aging water infrastructure renewal in urban areas creates opportunities to systematically implement green infrastructure (GI) systems. However, historical soil contamination from gasoline lead additives, steel manufacturing by-products, and other historical industry raise the potential that novel GI drainage patterns and geochemical environments may mobilize these legacy pollutants to green infrastructure sites previously isolated from most hydrologic flows. Characterization of GI soil chemistries across GI type to build on previous observations in other cites/regions is fundamental to accurate assessments of these emerging management scenarios and the resultant risk of increased metal exposures in downstream environments. In particular, clarification of ecosystem services this metal sequestration may provide are vital to comprehensive assessment of green infrastructure function. During 2021, soil metal chemistry, specifically, As, Cr, Cu, Fe, Mn, Ni, Pb, V, and Zn was measured at a high spatial resolution in six Pittsburgh (Pennsylvania, United States) GI installations using a portable X-ray Fluorescence Spectrometer. Patterns of trace metal accumulation were identified in these installations and evaluated as a function of site age and GI connection to road systems. Trace metals including chromium, copper, manganese, and zinc all seem to be accumulating at roadside edges. Remobilization of historically contaminated soils also seems to be a potential mechanism for transporting legacy trace metal contamination, particularly lead, into GI systems. However, metals were not clearly accumulating in installations less connected to road inputs. These findings are consistent with literature reports of trace metal transport to GI systems and reconfirm that clarification of these processes is fundamental to effective stormwater planning and management.

Revisiting the Côte d’Ivoire tektite strewn field

The tektites of the Côte d’Ivoire strewn field, called “ivorites”, come from the Bosumtwi meteorite impact crater formed 1.07 Ma ago in Ghana. Unlike other tektite strewn fields in the world, this tektite strewn field has remained under-explored after the pioneering works of A. Lacroix in the 1930s who reported the first tektites on the African continent, followed by a few explorers in the 1960s. To date, the geochemical properties of only slightly more than 20 ivorites have been measured, while there are potentially thousands to be discovered by analogy with other strewn fields. Based on these earlier works, the ivorites strewn field is considered to form an ellipse of about 1500 km2 around the town of Ouellé and Daoukro, setting apart three isolated finds. We conducted six exploratory missions in Côte d’Ivoire between 2019 and 2023 and report 174 new finds. These discoveries are mostly within the known limits of the strewn field, but several discoveries outside these limits extend the strewn field to an area of 4100 km2. The furthest discovery considered to be part of the strewn field is more than 45 km south of its previous limits. These new ivorites present various shapes (teardrops, dumbbells, spheres, ellipsoids) with masses ranging from 1 to 96 g. A geochemical analysis of 172 of these ivorites was performed using a portable X-ray fluorescence spectrometer. In addition, 87 ivorites (unknown locations), made available by the SODEMI museum (Côte d’Ivoire's governmental mining development company in Abidjan) were also analyzed. Their geochemical composition is clearly distinct from that of tektites from other strewn fields. However, these analyses reveal a more variable chemical composition than the apparent homogeneity previously inferred from a small number of specimens. The magnetic susceptibility of these tektites, measured with the SM150 device, is homogeneous and the small variations are essentially related to the iron content. The measured density of ivorites is comparable to the pore-free densities estimated from their chemical composition, implying that the abundant vesicles commonly observed at the surface, associated with bubbles and degassing of the silicate melt, are not present in the interior.