The New Brunswick segment of the Canadian Appalachians contains a variety of gold deposits and occurrences that formed at different stages of the Appalachian orogeny. The Tobique-Chaleur Zone, situated in the northern part of New Brunswick hosts several orogenic and epithermal gold mineralization systems that are spatially related to large-scale crustal faults or their subsidiary splays, e.g., the Rocky Brook-Millstream Fault. Although gold mineralization in northern New Brunswick is hosted by auriferous quartz veins, finding pathfinder elements, indicator minerals, and alteration associated with gold mineralization remains challenging. Herein, the portable X-ray fluorescence (pXRF, Olympus Vanta™) spectrometer, in conjunction with micro-X-Ray Fluorescence (µXRF) Energy Dispersive Spectrometry (EDS), was applied to selected core intervals from four gold systems in the region, namely the Williams Brook, McIntyre Brook, Mulligan Gulch, and Simpson Field occurrences. We generated pXRF-based multielement datasets from selected intervals, then applied compositional data analysis (CoDA), including principal component analysis (biplots) and cluster analysis, to interpret them. Although the pXRF analysis and subsequent multivariate compositional data analysis provide geochemical patterns and highlight indicator elements associated with gold mineralization, the study also includes a comprehensive mineralogical analysis. The pXRF geochemical data help the interpretation of the mineralogy, but the explicit mineralogical composition is confirmed through detailed petrographic and μ XRF analyses. Gold-bearing minerals were further identified by µXRF-EDS analysis, revealing that gold is mainly associated with sulfide minerals, namely pyrite, chalcopyrite, pyrrhotite, stibnite, and arsenopyrite. In addition to the above, our mineralogical studies further indicate that fine-grained muscovite and illite, produced by potassic and silicification alteration styles, are associated with gold-bearing quartz veins.

Hydrogeochemical exploration is a promising technique that uses groundwater as a medium to explore for mineral deposits. To evaluate the potential of hydrogeochemistry for gold exploration in the Canadian Shield, we conducted a case study near the Windfall gold deposit, a deep (>1 km) intrusion-related deposit of world-class scale and grade. This unmined deposit, located in a remote area of the Abitibi subprovince, provides an ideal setting to investigate the hydrogeochemical signature of gold mineralization in a cold and humid climate. This study proposes a combined knowledge-based and data-driven multivariate approach to identify dissolved elements that compose the multielement footprint of the Windfall mineralization. Four distinct hydrogeochemical poles (clusters) are defined from hierarchical cluster and principal component analyses: 1) recharge groundwater, 2) recharge-gold groundwater, 3) saline groundwater, and 4) saline-gold groundwater. Multielement enrichment (Ag, Tl, Th, Sn, Bi, U, La, and Ce) associated with ore minerals or alteration minerals is observed in samples of the gold-bearing recharge and saline clusters, and is particularly striking for Ag, Tl, and Th. Gold-type cluster samples, representing the mineralization footprint, are found in an approximately 1 km wide ENE–WSW corridor centered around the Mazères fault, a major ENE-trending regional-scale structure.

In this study, we demonstrate the use of single-particle inductively coupled plasma–mass spectrometry (spICP–MS) as a new tool for exploration hydrogeochemistry through a case study at the Bear Lodge alkaline complex in Wyoming, USA. Nanoparticulate forms of gold and associated pathfinder elements (Ag, Sb, Bi, Tl and Te) were detected in well waters proximal to rare earth element (REE) and Au mineralization, resulting in stronger geochemical anomalies compared with conventional acidified water analysis. Using the multi-elemental capability of spICP–time-of-flight MS (spICP–ToF-MS) to analyse waters, we detected REE particles that were hypothesized to be nanoscale REE mineral grains originating from the oxidized zone of carbonatite mineralization. For the first time, we present chondrite-normalized REE patterns from individual nanoparticles, allowing for geochemical interpretations based on light rare earth element enrichment and Ce anomalies. This study demonstrates that spICP–MS analysis of waters could be a valuable tool to detect concealed mineralization in environments with weak hydrogeochemical signatures. Moreover, the detection of indicator minerals using spICP–ToF-MS represents a novel use of the technique that may provide additional, previously unattainable information from water samples.

Geochemical data for the UK Lake District including both G-BASE stream sediment data and newly collected samples are shown here as a tool for modelling whole rock geochemistry at a regional scale and as a case study for identifying potential As-Bi-Co-Cu-Fe-Ni mineralisation. Regional whole rock concentrations for the Skiddaw Group and Borrowdale Volcanic Group (BVG) were modelled using G-BASE stream sediment data and found to align closely with newly collected in-situ XRF measurements of host rock samples. Average concentrations of elements such as Ag, Al, As, Fe, Ni, and Ti differed by only 1–2 wt.% or ∼20 ppm between the two datasets. Six areas identified by G-BASE as potential As-Co-Cu-Ni targets were visited. Of these, Keld and Devoke Water showed evidence for sulphide dissemination within the host rock rather than visible veins, while Black Combe, Seathwaite, Coniston, and Tilberthwaite were confirmed to host vein-type, quartz-sulphide mineralisation geochemically similar to known deposits at Dale Head North, Scar Crag, and Ulpha. This study highlights the successful application of G-BASE data for regional geochemical modelling and exploration targeting. The workflow could be adapted for other areas covered by preexisting stream sediment geochemical data or integrated into exploration strategies for new regions.

Geochemical exploration criteria for relatively LREE-enriched IOCG deposits have been tested and are applicable across multiple Proterozoic terranes in eastern Australia. The criteria were established using monazite from E1 (Cloncurry District, Queensland) and compared to existing data from Prominent Hill and Carrapateena (Gawler Craton, South Australia) and are effective in REE-rich deposits. The criteria use La, Ce and Nd chemistry in combination with Th and Y, where La + Ce > 65 wt.%, Nd < 12.5 wt.% and Y and Th are both < 1 wt.%. However, the criteria are not as effective in REE-poor deposits such as Osborne and SWAN (Cloncurry District). For these deposits, other trends in the monazite REEs such as changing Y and Dy contents are better to use, which can discriminate between mineralisation-associated hydrothermal monazite that formed at low temperatures (low Y and Dy), from metamorphic monazite that formed at high temperatures and are not associated with mineralisation (high Y and Dy). In metamorphosed terranes like the Cloncurry District where metamorphism is well constrained, chemical and temperature information using monazite chemistry can give information on the formation conditions of monazite, potentially hinting at a nearby IOCG system.

Surface water quantity and quality is important for arid and semi-arid regions where many people, including underserved and Indigenous communities, rely on a scarce resource for drinking water, irrigation, livestock, and ceremonial uses. The southwestern United States, and specifically the Four Corners Region (Colorado, Arizona, New Mexico, Utah), is an example of this situation. Elevated concentrations of metals including aluminum, arsenic, and lead were identified in previous studies and this study in the San Juan River from below the Navajo Dam, through the Navajo Nation to Mexican Hat, Utah. An interdisciplinary team applied approaches and principles of geology, geochemistry, geomorphology, hydrology, and statistics to gain a better understanding of the tributaries supplying the source(s) of metals to the San Juan River. This paper provides an overview of the thematic issue titled Metal geochemical fingerprinting to identify sub-watershed source contributions to surface water at a regional arid watershed scale, Four Corners Region, USA. An overview of sampling sites, techniques, and potential sources of metals is provided. Approaches used in this study could be applied to investigations in similar systems globally.

Deposit scale biogeochemical surveys have been conducted in many parts of Australia, but there have been few conducted at regional scales. The Cobar Basin in NSW hosts a range of mineral deposits and regolith-landform settings. 3,300 samples of Callitris glaucophylla (cypress pine) needles have been collected from road traverses within a 43,000 km 2 area with detailed sampling incorporated over various mineral deposits. Dried and milled samples were analysed by both ICP-MS following microwave-assisted aqua regia digestion, and directly by pXRF. The concentrations of most elements in the needles largely reflect variations in underlying lithology including areas with alluvial cover. The concentration of ”ballast” trace elements Au, Ag, Bi, Pb, As and W are typically higher over the Siluro-Devonian clastic sediments than felsic intrusives and volcaniclastic or Ordovician siliciclastic units, whereas the micronutrients Ni and Co are elevated over ultramafic units. For some major and nutrient trace elements, including Cu and Zn, the pines restrict uptake and limit the response to lithological changes, mineralisation or contamination. Minor seasonal variations or site variability in element concentrations do not substantially alter the biogeochemical contrast between regional background and mineralisation signatures. The needles display effects of dust or contamination from current or historical mining operations in some areas, but variation in the distance of samples from road edges or road type display no systematic relationship with needle composition, except for Fe and Al. C. glaucophylla needles are an effective sampling media for mineral exploration in the Cobar region and for environmental monitoring.

The 2015 Gold King Mine spill released 11.3 million liters of metal-laden water into the Animas River. To determine its impact downstream, we monitored Al, As, Cr, Fe, Mn, Pb, Zn, Ca, and Cu concentrations in irrigation ditch sediments fed by the Animas River during the 2017-2020 growing seasons. The elements, chosen for their presence in the original contaminant plume, were compared to regulatory risk assessment guidelines for soil. Sediments were collected from the mid-point and one side (at the high-water level mark) of fifteen irrigation ditch transects. Mixed models assessed for sampling time, sampling point (center or side), and their interaction for repeated measures in time and location in the ditch. Total concentrations collected from ditch sides were higher than the center concentrations for all elements except Mn. Only As exceeded the New Mexico Environment Department soil screening level of 7.07 mg kg⁻¹, increasing from 6.38 ± 0.47 mg kg⁻¹ (2017 pre-growing season) to 12.24 ± 2.67 mg kg⁻¹ (2019 post-growing season), a net increase of 5.86 ± 2.72 mg kg⁻¹. The Pb concentrations in ditch center sediments also increased over time, rising from 30.29 ± 6.90 mg kg⁻¹ to 49.87 ± 10.63 mg kg⁻¹, but remained below the U.S. EPA Residential Soil Screening Level of 400 mg kg⁻¹. In contrast, Mn and Zn fluctuated over the sampling period, while the other metal(loid) concentrations did not vary significantly. Monitoring sediment metal(loid) concentrations in irrigation ditches is essential not only for tracking the legacy impacts of upstream mining activities, but also for protecting downstream agricultural systems that depend on diverted river water, particularly in regions where irrigation infrastructure directly influences soil health, crop safety, and community resilience.

The timeline from exploration through to extraction of a mineral deposit often spans decades, resulting in multi-generational geochemical data collected utilizing a variety of digestion and analytical methods. To extract value from these diverse datasets is challenging. This is due to lack of comparability in elemental concentrations produced by different digestion and analysis methods. Relationships between these multi-generational, variable digest geochemical datasets are typically non-linear, requiring a more sophisticated approach to data integration. Two case studies are presented to address this integration problem using simple machine learning workflows. Case study 1 outlines a workflow to derive a common molar element ratio used in porphyry deposit exploration and alteration quantification (2Ca-Na-K/Al) from 4-acid digestion data as a proxy for the degree of feldspar destruction caused by hydrothermal metasomatism. It further illustrates the prediction of this ratio (derived from 4-acid digestion geochemistry) using aqua regia digestion geochemical data as an input. Case study 2 illustrates the use of aqua regia-derived Ca as a proxy for neutralization potential in mineralogical systems dominated by carbonate dissolution in aqua regia digestion, and presents a workflow to predict neutralization potential from 4-acid data, trained to aqua regia Ca. Both case studies showcase the integration of aqua regia and 4-acid datasets via non-linear machine learning algorithms, which exploit the mineralogical and elemental controls governing differences between digestion methods.

Radon represents a global health risk, and so accurate delineation of radon-prone areas is a prerequisite for evidence-based radon mitigation and public health protection. National probabilistic radon models of Ireland, based on 1:1 M bedrock geological maps that group the Clare Shales with limestones achieve ∼74% accuracy. Despite the high accuracy of Ireland's national radon map, some discrepancies still exist. Using geochemical and geostatistical methods, we investigated a significant and persistent radon anomaly over the Clare Shale Formation at Castleisland, Co. Kerry, Ireland. Fifty-six topsoil samples collected from the A-horizon within a 6 km 2 grid, with samples spaced every 250–500 m apart, were included in the analysis and compared to co-located soil-gas radon measurements. Following centred and isometric log-ratio transformations of inductively coupled plasma mass spectroscopy (ICP-MS)/optical emission spectroscopy (OES) data for 37 elements, soils above the Clare Shales exhibited a median U concentration of 4 mg kg −1 (range 1.4–37 mg kg −1 ). Pearson correlations between log 10 soil-gas radon and individual elements peaked at a Pearson correlation coefficient ( r ) = 0.57 for Sr (coefficient of determination ( R 2 ) = 0.32), with similarly strong associations for V ( r = 0.54), Ag ( r = 0.52), P ( r = 0.47), Au ( r = 0.46), U ( r = 0.45) and Tl ( r = 0.43) (all P < 0.001). One-way ANOVA indicates radon class categories explain a median 43.8% of variance in 14 trace elements, while bedrock geology explains 27.8%. Shared tracers (U, V, P, Ag, Sb) underscore overlapping lithological and radiogenic controls. Principal components 1–3 (PC1–PC3) capture 62.9% of total variance (PC1 = 31.8%, PC2 = 17.2%, PC3 = 13.9%). PC1 is defined by strong positive loadings on Sc, Mg, Fe, Al, Th, Ni and Co, and negative loadings on Sr, Ag, U, P and V, neatly contrasting shale-derived, high-radon soils from carbonate terrains. This study demonstrates that local-scale lithogeochemical proxies, resolved at 250 m and calibrated against a 1:100 k geological framework, can effectively delineate elevated radon sources. This approach offers a systematic means to investigate map anomalies, refine national radon models, enhance spatial accuracy, and support evidence-based radon risk assessment and public health protection initiatives.