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Article

Geochemical Assessment of Mineral Resource Potential in a Hg-Sb-Pb-Zn Mining Area: The Almadén and Guadalmez Synclines (South-Central Spain)

by
José Ignacio Barquero
1,2,*,
Saturnino Lorenzo
1,2,
José M. Esbrí
3,
Sofía Rivera
1,4,
Ana C. González-Valoys
5,
Efrén García-Ordiales
6,* and
Pablo Higueras
1,2
1
Instituto de Geología Aplicada, Universidad de Castila-La Mancha, Pl. Manuel Meca 1, 13400 Almadén, Spain
2
Escuela de Ingeniería Minera e Industrial de Almadén, 13400 Almadén, Spain
3
Departamento de Mineralogía y Petrología, Universidad Complutense de Madrid, Antonio Nováis 12, 28040 Madrid, Spain
4
IES Maestro Juan de Ávila, Ronda de Calatrava 1, 13003 Ciudad Real, Spain
5
Centro Experimental de Ingeniería, Universidad Tecnológica de Panamá, Vía Tocumen, Panama City 0819-07289, Panama
6
ISYMA Research Group, Mining, Energy and Materials Engineering School, University of Oviedo, c/Independencia 13, 33011 Oviedo, Spain
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2022, 12(22), 11351; https://doi.org/10.3390/app122211351
Submission received: 29 September 2022 / Revised: 1 November 2022 / Accepted: 3 November 2022 / Published: 9 November 2022
(This article belongs to the Section Environmental Sciences)
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Abstract

:
The geochemical data from surface soils are often neglected or questioned when prospecting for ore deposits within active mining districts due to the “background noise” produced by anthropogenic pollution derived from mining activity. Large datasets on a national and international scale offer interesting possibilities to discover prospective zones. In the present work, data from the Geochemical Atlas of Castilla–La Mancha were treated in an area with an intense history of mining Hg, Pb, Zn, and Sb: the Almadén and Guadalmez synclines and the Alcudia Valley. The sampling grid was densified to adapt it to the scale of the main geological formations, and a cluster analysis was carried out to establish the relationships between the variables and a factor analysis to distinguish between geogenic and metallogenic factors. The results showed very high concentrations of some elements of prospective interest in local background areas: Hg (51 mg kg−1), Pb (1190 mg kg−1), and Sb (45 mg kg−1), with high variation coefficients. Cluster analysis unveiled a relationship between most of the local ore-forming metals (As, Sb, Hg, Pb, and Ag) with a clear correlation between Hg and organic matter, suggesting a notable contribution of Hg in soil. The factor analysis highlighted five factors, three geogenic and two ore-forming elements. Despite Hg being the main candidate to form a separate factor, its aerial deposition and a large number of outliers in the Almadén syncline contributed to integrating the element into a geogenic factor. Instead, factors F4 (Pb and Zn) and F5 (As and Sb) delimited the prospective areas in both synclines far from the known and the exploited mines. Some of these areas coincided with discovered mineralized zones, specifically in the area SE of a derelict Sb mine, confirming the usefulness of these datasets and statistical tools in areas with recent mining activity.

1. Introduction

The SW of the Ciudad Real Province (Castilla–La Mancha, south-central Spain) is particularly well-known from the geological and mining points of view, mainly as the location of an important Hg mining deposit, the Almadén district, which has historically produced one-third of the total industrial production of this element ([1] among others). The district is restricted to the so-called Almadén syncline, constituted by the Paleozoic (Lower Ordovician to Upper Devonian) (meta)sedimentary rocks with the frequent presence of mafic magmatic rocks, both volcanic and subvolcanic [2,3,4,5]. The Guadalmez syncline extends adjacent and to the south of this syncline, with some minor Sb deposits that were exploited in the early 20th century [6,7], and, from the geological point of view, is relatively similar to the Almadén syncline but includes a more complete stratigraphic succession and a lesser abundance of magmatic rocks [8]. Furthermore, the Alcudia Anticline extends between these two synclines and is the site of the Valle de Alcudia Pb-Zn-Ag mining district, including a significant number of small-to-medium-sized vein deposits exploited from Roman times to the mid-20th century [9]. The tectonic structure of the area corresponds to the effects of the Variscan orogenic event, developed in Devonian–Carboniferous times (370–290 Ma), producing the folding and faulting of the area and low-grade metamorphism [10]. In more detail, the Almadén and Guadalmez synclines are ̴N120° E tending tectonic structures. Their stratigraphic succession includes four quartzitic layers of decametric thickness separated by sequences of shales and/or alternations of shales and quartzites (ASQ) (Figure 1). These sequences are among the most complete records of the Paleozoic in the Iberian Peninsula, from the Lower Ordovician to the Lower Carboniferous [3,4,8,11]. There is a conspicuous presence of igneous mafic rocks at the Almadén syncline, particularly in the Upper Devonian, constituting an authentic volcano-sedimentary sequence [12]. It is noteworthy that in lower stratigraphic levels, the presence of these rocks is sporadic in time and space, in the form of sills and dikes of basaltic rocks (rarely identified as concordant bodies undoubtedly interpretable as lava flows), pipe-like structures filled by mafic pyroclasts with ultramafic enclaves (the so-called Frailesca rock), and sills and lopolith-shaped bodies of doleritic rocks [5,13]. In the Guadalmez syncline, the presence of magmatic rocks is minor with respect to Almadén, with only the sporadic presence of diabase in irregular masses, intruded with preference in the Silurian shales [14]. Higueras et al. (2013) [13] and Villaseca et al. (2022) [15] characterize these rocks as two magmatic series of alkaline affinity for the volcanic varieties present in Almadén (ALK-1) and of tholeiitic affinity to the diabase present in both synclines (THOL-1). The Almadén syncline hosts the huge Almadén mercury mining district [1,15], interpreted as genetically related to the ALK-1 episode [5], while the Guadalmez syncline hosts several small Sb mineralizations, related, at least geographically, to the THOL-1 diabases.
Regional soil geochemistry, which involves soil samples collected over wide grids, has its main application in the determination of baseline and reference levels for the different elements and usually allows for the characterization of the differential composition and variability of the lithologies represented over a broad area. However, it also allows for the identification of large-extension anomalies, which can correspond to geogenic variations, as well as to anthropogenic contributions. The best examples of regional soil geochemistry datasets correspond to a continental or national scale geochemical atlas, such as those for Europe [16] or Spain [17], among many others. Many regions in developed countries have also produced this type of data, published or not, but used by regional governments to implement reference and/or intervention levels used in environmental management and planning. Most Spanish regions have implemented these guidelines, but not Castilla–La Mancha, a region for which only partial data are found [18,19].
The area corresponds to the Csa Köppen–Geiger climatic area, warm and temperate. Hydric balance indicates that rains are concentrated in winter and are scarce in summer, with annual precipitation averages of 520 mm, 963 mm potential evapotranspiration, and 16.2 °C temperature [20].
The present study corresponds to a synergy between two projects, financed by different sources, and with different final objectives: The BiGeoQCLM project, funded by the Castilla–La Mancha regional R + D plan, and the AUREOLE project, funded by the Spanish national R + D plan and integrated into an ERA-MIN3 project led by the French Bureau de Recherches Géologiques et Minières (BRGM). The BiGeoQCLM project is aimed at the geochemical characterization of the complete Castilla–La Mancha region (some 79.500 km2 in extension). The methodology design is based on a sampling density of one sample every 100 km2, with a total extent of 2300 km2. The aim of the AUREOLE project is the establishment of geological research criteria for the critical elements Sb and W and included an increase in the density of the geochemistry soil survey with 110 additional samples, thus increasing the sample density to 6 samples every 100 km2 covering the entire area of the Almadén and Guadalmez synclines, as well as a significant part of the Valle de Alcudia (Figure 1).
The objective of the present work was to characterize this area from the geochemical point of view, searching for relationships between the lithologies represented in the regional substrate and their composition and for relationships to the presence of metallic ore deposits, in particular of Hg and Sb.

2. Materials and Methods

2.1. Sampling

Samples were taken in the area comprising the Almadén and Guadalmez synclines, as well as in the Alcudia anticline located between them. The area is some 2.300 km2 wide, and the sampling grid was designed to be regular, comprising 150 cells. The sampling site locations were chosen with the aim of obtaining a balanced distribution among the different lithologies present in the area. Due to access restrictions, instead of the forecasted 150 samples, it was only possible to take a total of 129 samples (Figure 1).
The samples were taken using an Ejkelkamp soil sampler, from the A horizon (0–15 cm. after eventually cleaning the litterfall) of poorly developed soils (mainly Inceptisols); three subsamples were taken in an area of some 100 m2 per site and two different samples per site. Due to access restrictions, instead of the forecasted 150 samples, it was only possible to take a total of 129 samples of Almadén syncline (N = 40), Guadalmez syncline (N = 55), and Alcudia anticline (N = 18) (Figure 1). The sampling tools were cleaned with deionized water after each sampling.

2.2. Sample Preparation and Analysis

Once in the laboratory, the samples were dried at room temperature for 15 days. After this procedure, they were disaggregated, homogenized, and sieved to discard the >2 mm fraction. Two aliquots were obtained: one for determination of the physicochemical parameters and the second one for milling in an agate mortar for 2 min to obtain a grain size <100 µm for analysis.
The non-milled samples were used to determine the pedological parameters. The grain size distribution was assessed by means of a Fritsch ANALYSETTE MicroTec Plus, following the methodology described by Garcia-Ordiales et al. (2018) [21] using the classical sand–silt–clay notation [22].
The determination of pedological parameters was carried out on a 20 g portion of a non-milled sample. Reactivity (pH) and salt contents (Electric conductivity, EC) were assessed using a 1/5 (w/v) suspension of the sample, following the ASTM Norm 4972 [23], using a CRISON GLP22 pH meter and a CRISON GLP 32 conductivity meter. Proportions of soil organic matter (SOM) were determined via weight loss after heating at 450 °C in a muffle furnace [24].
The milled samples were analyzed by using ICP-AES and ICP-MS in a certified lab (ALS Laboratory Group, SL), applying the ME-ICP41 method based on aqua regia digestion. QC/QA included the analysis of sample duplicates (7% of total samples), blanks, and certified reference materials (EMOG-17, MRGeo08, OGGeo08, and OREAS 905) with recovery ratios between 97% and 100% (ICP-AES). Duplicate samples were taken at random locations within a radius of 500 m at the same sites. Larger data dispersions were observed in major elements (SiO2, among others), and significant dispersions of some trace elements were observed, especially Pb, As, S, and Zn (>25% relative standard deviation), which represent local anomalies in the geological materials (Precambrian). The determination of total Hg concentrations was carried out by means of atomic absorption spectrometry with the Zeeman effect, using a Lumex RA-915M device (LUMEX Instruments, St. Petersburg, Russia) combined with a PYRO-915 pyrolizer [25]. The total Si concentrations were obtained by means of energy-dispersive X-ray fluorescence (ED-XRF), using an Epsilon1 XRF Spectrometer. QC/QA was based on the use of certified reference material NIST 2710A (Montana soil), with recovery ratios between 80% and 120% (ED-XRF).

2.3. Statistical Analyses and Mapping

Data treatment included multivariate analyses obtained with Minitab 19.1 software and STATGRAPHICS Centurion V.19.1.2. Spatial distribution patterns were obtained by squared inverse distance using Surfer 21.1.158 (Golden Software) and ArcMAP 10.8.1. (ArcGIS).

3. Results and Discussion

3.1. Pedological Parameters

The studied soils showed pH values from 4.5 to 7.8, with an average of 6.1 (Table 1). The values of EC were generally low, with an average of 30 ± 20 µS cm−1, and the higher value (110 µS cm−1) was found in a substrate with a predominance of slate materials in the presence of basic volcanic rocks of Silurian age in the Almadén syncline. Soil organic matter (SOM) values were of a wide range, from 1.5% to 13.3%, the average being 4.9 ± 1.8%. The higher SOM values were found in a shady area in the presence of a high density of trees and shrubs and a thick layer of litterfall.
The grain size distribution of the samples showed a variable texture with a generally high proportion of silt, from silty loam to sandy loam, with variable sand content from the less sandy terms in the volcanic rocks and slates to the richest in sand samples found on the quartzites and sandstones. ASQ demonstrated remarkable granulometric variability, presenting samples in the three categories (Figure 2).

3.2. Major and Trace Elements

From the geochemical point of view, the samples were of a high siliceous character, reaching 30.2%, with significantly high Fe contents (max: 8.0%) in some samples (Table 2). The high Al contents indicated a high proportion of clays. The generally low concentrations of Ca confirmed the absence or scarcity of carbonates and sulfates in these soils. Trace elements showed concentrations lower than the reference values published by Jimenez-Ballesta et al. (2010) [18], confirming the lithological baseline character of the values considered in this study. The reference values described by Jimenez-Ballesta et al. (2010) [18] belong to a more restricted soil samples dataset, in terms of sample number, but from the entire Castilla–La Mancha region, including siliceous and carbonated materials; therefore, the lower values presented in this work can be considered as baseline values for siliceous units. A group of trace elements reached concentrations greater than a hundred (Mn > P > Ba), but most were higher than ten (Pb > Zn > V > Cr > Ni > Cu > As > Co > Sr), with a third group having very low concentrations (Sb > Hg > Be > Ag) (Table 2). The trace elements of the second group were found to be common in the mineral paragenesis of the Pb-Zn-Ag vein deposits of the Alcudia Valley, mainly hosted in the Precambrian substrate, but with their presence also in Almadén and Guadalmez syncline materials. It is noteworthy that the most representative deposits of the two synclines were elements belonging to the third group (Hg and Sb), with concentrations below tens of ppm but with a very high variation coefficient (VC).
As shown in Table 2, some elements showed higher concentrations than the reference values for Spanish soils [17]: Hg (2.9 mg kg−1), Pb (56.5 mg kg−1), and Sb (4.1 mg kg−1). These are elements related to ore deposits in the southwest sector of Ciudad Real Province, and their higher contents can be related to low-grade regional anomalies but also to the anthropogenic pollution related to mining. The mines in this sector have been in operation from Roman times to the present, and ancient mining techniques were very ineffective and likely caused the wide dispersion of these elements. This anthropogenic distortion can be more complicated for Sb, a low-mobility metalloid with a very low possibility of creating a dispersion halo around an ore deposit or even a derelict mine. For Hg, however, anthropogenic and geogenic dispersion are processes that are certainly almost equal in importance since the mining district comprises a huge mine and several much smaller mines in the Almadén syncline [26].
Elements such as Fe, Mn, Ag, and Co were found to have a slightly higher average than Spanish soils, showing a great variation for both synclines; these elements are likely related to the presence of granitic rocks, mafic volcanic rock outcrops and clayey rocks rich in these elements [17]. An opposite trend could be observed for Al, Ca, K, Ba, and Sr, with values well below the reference levels for Spanish soils. This may be due to the predominant lithology of the area, generally deficient in these elements, and their higher mobility rates from parent materials. Other elements, including Mg, As, Be, Cr, Cu, Ni, V, and Zn, showed concentrations slightly below or similar to the reference values for Spanish soils. The average concentration of P was lower than the reference values for Spanish soils, likely suggesting an agronomic factor, possibly the use of manure instead of P-based fertilizers in the area.

3.3. Statistical Treatment

A Pearson correlation coefficient study was performed taking into consideration the different domains in order to detect similarities and differences. As can be seen in Figure 3, the elements with significant correlations in the Almadén syncline were found to be those related to volcanic activity (Fe, Ni, Ca, Cu, Cr, Mg), but in the Guadalmez syncline, fewer significant correlations were found in the Almadén syncline, which is caused by a variety of factors. Lower correlations were found for Hg, Pb, Sb, and As in both synclines (pictured in green in Figure 3), all of which are mineral-deposit-forming elements of quasi-monoelemental mineralizations. Moreover, pedological parameters appeared to be related to rock-forming elements and showed higher correlations for pH than for OM and EC in both synclines. Finally, SiO2 showed very low correlation coefficients with other rock-forming elements but not very low for mineral-deposit-forming elements. Although this change between such low correlations cannot be considered significant, it may be a consequence of the presence of almost all mineral deposits in the quartzite layers of both synclines.
Cluster analysis (Figure 3) differentiated two groups and three subgroups from each dataset. The group that differed most clearly was that of the mineral-deposit-forming elements (Hg, Sb, Pb, and As) (marked as E in Figure 3b–d), which appeared together with EC, OM, and S in the Almadén syncline, and together with P and Ag in the Guadalmez syncline. In the Almadén syncline, a large amount of cinnabar in its monomineralogic deposits produces a remarkable level of dissemination of Hg and S and significant emissions of gaseous Hg uptake by the soil organic fraction (humic and fulvic acids) [27,28,29,30,31]. As described by Higueras et al. (2003) [27], the soils of the Almadén region are poor in smectites, thus reducing the possibility of cation exchange and increasing the availability of metals from the inorganic matrix, leaving organic matter as the only metal retention agent. However, in the Guadalmez syncline, there are only two new elements: Ag related to Pb due to the Pb-Zn-Ag deposits of the Valle de Alcudia mining district; and P, related to Pb-Ag, which may be due to the more agronomic character of the soils from this syncline, less populated than the Almadén syncline and much less anthropized.
Another large group was formed by the rock-forming elements with a less clear distribution between the subgroups. In the Almadén syncline, the three subgroups differentiated ferromagnesian elements typical of mafic magmatic rocks (Subgroup C, see Figure 3c) from two other less well-defined ones. In the Guadalmez syncline, there was also a smaller subgroup related to mafic magmatic rocks (Subgroup B) and another with mobile elements (Cu and Zn) typical of Pb-Zn-Ag mineralizations (Subgroup A) (Figure 3b). Finally, there was a subgroup related to the carbonate-rich rocks outcropping in this Guadalmez syncline on which the OM and EC pedological parameters apparently depend (Subgroup C, Figure 3b).

3.4. Spatial Distribution

The spatial distribution of the major elements highlights the differences between both synclines (Figure 4). The Guadalmez syncline was found to be more siliceous than that of the Almadén, with higher Si contents in the quartzite–sandstone levels that exhibit a bimodal profile in the violin plot, with higher probabilities in low and high values of the dataset. The distribution of Al was markedly displaced towards the Almadén syncline, related to the greater presence of phyllosilicate-rich shales. Both Ca and Mg showed the highest concentrations in the western part of the study area (the Almadén syncline), where it could be associated with the granite from Garlitos, an area with a geological predominance of igneous rocks (see granodiorites in Figure 1), presenting a general alteration of its primary igneous minerals, replaced by secondary minerals with high concentrations of Ca, Mg, and Fe. Several local anomalies also appeared further east in the Almadén syncline that could be a consequence of the presence of various volcanic tuffs or even localized outcrops of highly altered basalts. The maximum values of Ca-Mg corresponded to various areas heavily anthropized by Pb-Zn-Ag mining. These deposits were exploited in the past and in their surroundings the igneous rocks are highly altered, producing the replacement of primary igneous minerals by carbonates, chlorite, and silica [32].
Figure 5 offers the spatial distribution of the most relevant trace elements: Hg, Sb, Pb, and As. The highest concentrations of Hg were found in the Almadén syncline, specifically on the southern branch, drawing a dispersion halo that, on its edges, coincided with the location of cinnabar deposits, both stratabound and epithermal. In the violin graphs, it could be observed that the quartzite–sandstone levels contained Hg anomalous values, followed by magmatic rocks and ASQ. However, In the Guadalmez syncline, although the values were lower, the trend of anomalous values continued in the quartzites and ASQ, although not in the magmatic rocks. The distribution of the maximum values of Sb revealed it to be located in areas with low Hg values in both synclines, especially in Guadalmez, where the Sb maximum appears in dark blue areas on the Hg map (Figure 5). The violin graphs also showed a contrasting differentiation for this element, with anomalous values in the quartzite–sandstone levels and ASQ in Guadalmez and in the slates in the Almadén syncline. The other two elements (Pb and As) showed maximum concentrations in localized areas with markedly anomalous contents with respect to the rest of the dataset. The primary mineral samples obtained at the La Balanzona mine were identified with XRD as stibnite (Sb2S3), with bindehimite (Pb2Sb2O6(O,OH)), and stibiconite (Sb3+(Sb5+)2O6(OH)) as the main oxidized phases. In the Guadalmez syncline, the areas richest in Pb were found to coincide with the Sb maximum. It is not clear whether the presence of Sb and Pb has a genetic relationship or whether small Pb mineralizations were emplaced where Sb deposits would later form, but the result is that the weathering of secondary Sb-Pb minerals occurred [33].

3.5. Discussion

Regional geochemical soil datasets have been used to establish background values and generic reference values by lithological groups [16,17]. Sampling design often includes a random location of samples within the cell of a grid, or a supervised location in the cell following lithological criteria to obtain a representative sampling of all lithologies. Both approaches involve avoiding anthropogenically polluted areas, including cities, roads, dirt roads, waste dumps, etc. This is an important point when trying to find out the prospective significance of ore deposits to those data since the multi-element data are only able to reveal regional background anomalies with an expected low statistical significance. For this reason, a sufficient relationship must be established between the substrate and the soils developed on it, because many factors can compromise the correct interpretation of anomalies: compositional variations in bedrock, differential mobilities between groups of elements, as well as variations produced by pedogenesis processes. In the present work, we used a set of soil geochemistry data in two synclines with abundant mineral deposits (Hg in the Almadén syncline and Sb in the Guadalmez syncline) and determined through a cluster of variables that there was a significant relationship between the multi-elemental contents and the entirety of both synclines, and the four types of lithological units (ASQ, igneous rocks, quartzite–sandstones, and slates) present on each one [3,4,8,10].
The most commonly used statistical treatments for soil geochemical datasets are multivariate, principal component analysis (PCA), and factor analysis (FA). Both treatments are employed for different reasons: PCA is used to decompose the data into a smaller number of components, while FA is used to understand the underlying “cause” for which these factors (latent or constituents) capture much of the information of a set of variables in the dataset [34,35]. Therefore, while the aim of PCA is to explain the cumulative variance in as many variables as possible [36], FA focuses on explaining covariances or correlations between the variables. In this work, we followed the recommendations of Reimann et al. (2002) [37], removing outliers before a FA with varimax rotation. In order to select elements for each factor, a loading threshold of 0.5 was selected.
The distribution maps of the groups of factor elements were created using the factor scores of each element, the aim of which was to obtain a normalized value for each sampling point. The IDW method was used to avoid detecting trends in the data by kriging that would lead to errors in the interpretation [38,39].
Element grouping showed five factors: Factor 1 (Al, Be, Co, Cr, Cu, Fe, Ni, P, Sc, V, and Zn), representing 45.1% of the variance; Factor 2 (Al, K, Mg, Hg, La, Ni, and P), representing 13.7% of the variance; Factor 3 (Ca, Ba, Co, Mn, and Sc), explaining 7.5% of the variance; Factor 4 (Pb and Zn), representing 6.4% of the variance; and Factor 5 (As and Sb), representing 4.6% of the variance. It was possible to distinguish several factors with a clear lithological control (F1 and F3), others with a clear control by mineralized phases (F4 and F5), and a mixed factor (F2), dependent on certain lithological units but also on the dispersion of Hg in the largest mining district in the world [40].
Before interpreting the distribution of these factors in the two synclines, one must bear in mind that this statistical treatment offers possibilities in terms of detecting the prospective zones for certain types of mineralization, but it also has serious limitations. Reimann et al. (2002) [37] described some of them: the sampling scale with respect to the geological structures that it must represent, the number of elements that are counted to carry out the treatment, and the number of values below the detection limit that would homogenize the variables. The number of elements appears to be very important, depending more on the analytical capabilities of the measurement equipment than on the geochemical criteria of representativeness. Thus, geochemical surveys analyzed by ICP may show a different bias than the same campaign analyzed by EDXRF, for example.
The distribution of the lithological factors (F1 and F3) showed a concentration of the highest values in the interior of the two synclines, with lower values in the Precambrian materials (Figure 6). The group of ferromagnesian elements (F1) was found to be more present in the Almadén syncline, coinciding with the units with the most evident mafic magmatic activity. It is of note that the other lithological factor (F2) demonstrated a coincident distribution with the igneous units of the Almadén syncline, distributing towards the SE in the Precambrian materials, even though it was necessary to delete a large number of Hg data from the Almadén syncline for being outliers. In this case, it appears quite difficult to discriminate between anthropogenic pollution and geochemical anomaly, especially for Hg, a volatile element generally of atmospheric origin, as seen in the dendrogram (Figure 3b). Similar results were described by Martins-Ferreira et al. (2017) [41] for a gold province in Central Brazil. Their factor analysis results provided five correlation factors explaining 71.2% of the total variance of soil composition, very similar to our work. These factors identified the elemental associations influenced by the parental materials, such as F1, F2, and F3 factors in the Guadalmez and Almadén synclines.
Finally, the two “ore-deposit-forming” factors had a less regular distribution. Factor F4 (Pb, Zn) appeared to be distributed according to a band in the N120° E direction on the unit of black shales and basic magmatic rocks, with some local anomalies located on the edges of the Guadalmez syncline, close to the Precambrian materials. In this case, deleting the outliers in the Precambrian materials of the Alcudia Valley and the under-representation of these materials in the sampling allowed for the discrimination of favorable areas in both synclines. The last factor (F5) identified the areas favorable to the group of As-Sb elements, delimiting zones far from the core of the synclines. The delimitation of a favorable area to the SE of the main identified Sb deposits of the Guadalmez syncline is noteworthy and has been confirmed as productive in the first lithogeochemical prospecting works in the area [33]. Wu et al. (2020) [42] described a similar case study in a gold province, finding a Pb-Zn factor belonging to the primary halo of gold ore bodies.
The FA unveils the possibility of discovering relationships between the data that were not detectable in the cluster analysis [43], and avoiding the interference of anthropogenic pollution in an extensively mined area for Hg, Sb, Pb, and Zn. This first exploratory statistical treatment made it possible to establish the relationships between elements and soil parameters, revealing, for instance, that the presence of Hg in soils is primarily of atmospheric origin, as Hg did not appear in any metallogenic factor in the FA. In addition, elemental (Figure 4 and Figure 5) and factor distribution maps (Figure 6) revealed different levels of information. Elements such as Pb showed a high concentration in the southern part of the Almadén syncline, similar to the Sb deposits in the area. In contrast, the Factor 4 map shows that the main association of Pb was with Zn, in the Pb-Zn-Ag metallogenetic district of Valle de Alcudia [44]. Factor 5 corresponded to the Sb-As association in both synclines, offering data for the prospective zones in the SE area of the known mines of the Guadalmez syncline, where Esbrí et al. (2023) [33] described new findings of stibnite (Sb2S3) and bindehimite (Pb2Sb2O6O) in rock samples.

4. Conclusions

The soils from the Almadén and Guadalmez synclines demonstrated very high local background concentrations of some elements of metallogenic interest: Hg (2.9 mg kg−1), Pb (56.5 mg kg−1), and Sb (4.1 mg kg−1) on average.
Cluster analysis differentiated two groups of elements, the most distinct of which was composed of ore-deposit-forming elements (Hg, Sb, Pb, and As), which appeared together with EC, SOM, and S in the Almadén syncline and together with P and Ag in the Guadalmez syncline.
Factor Analysis differentiated three factors of geogenic elements: F1 (Al, Be, Co, Cr, Cu, Fe, Ni, P, Sc, V, and Zn); F2 (Al, K, Mg, Hg, La, Ni, and P); and F3 (Ca, Ba, Co, Mn, and Sc); and two factors related to ore deposits, F4 (Pb and Zn) and F5 (As and Sb).
The non-existence of a factor for Hg ore deposits can be explained by the predominantly atmospheric origin of the element fixed in the surface soil and the deleting of outliers of natural and anthropogenic origins.
The mineralization factors (F4 and F5) showed areas favorable to the discovery of new mineral deposits, partially confirmed in F5 maps, to the SE of the main Sb mines of the Guadalmez syncline.
Some of these areas coincided with discovered mineralized zones, specifically in the area SE of a derelict Sb mine, confirming the usefulness of these datasets and statistical tools in areas with recent mining activity.
A combination of cluster analysis and FA was useful in detecting prospective areas in datasets from mining districts, although some limitations were detected for the prospection of Hg, due to its ability to transform to a gaseous state and then be transferred to the soil.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app122211351/s1, Table S1: Pedological parameters and elemental composition of samples, major (in %) and elements (in mg kg−1).

Author Contributions

Data curation, J.I.B., S.L., S.R., A.C.G.-V. and E.G.-O.; Formal analysis, J.M.E.; Funding acquisition, J.I.B.; Investigation, J.I.B., S.R. and A.C.G.-V.; Methodology, S.L. and J.M.E.; Project administration, P.H.; Resources, A.C.G.-V.; Writing—original draft, J.I.B., S.L., J.M.E., E.G.-O. and P.H. All authors have read and agreed to the published version of the manuscript.

Funding

This study has been financed by project PCI2019-103779 (Spanish Ministry of Science and Education), and it is also a contribution to the AUREOLE Project, funded by the ERA-MIN2 European Project.

Institutional Review Board Statement

This study does not requite ethical approval.

Data Availability Statement

Raw analytical data are available for other researchers after justified requirement to the corresponding authors.

Conflicts of Interest

The authors declare no conflict of interest.

References

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Applsci 12 11351 g001 550
Figure 1. Sampling network in the syncline areas with a geological scheme.
Figure 1. Sampling network in the syncline areas with a geological scheme.
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Applsci 12 11351 g002 550
Figure 2. Texture of samples. ASQ: alternations of shales and quartzites.
Figure 2. Texture of samples. ASQ: alternations of shales and quartzites.
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Applsci 12 11351 g003 550
Figure 3. (a) Correlation matrix for the Almadén and Guadalmez synclines and dendrograms for all samples (b), Almadén syncline (c), and Guadalmez syncline (d). A–D correspond to the different subgroups obtained.
Figure 3. (a) Correlation matrix for the Almadén and Guadalmez synclines and dendrograms for all samples (b), Almadén syncline (c), and Guadalmez syncline (d). A–D correspond to the different subgroups obtained.
Applsci 12 11351 g003
Applsci 12 11351 g004a 550Applsci 12 11351 g004b 550
Figure 4. Spatial distribution maps (A) and violin plots (B,C) of major elements (all data are expressed as a percentage). ASQ: alternations of shales and quartzites, IR: igneous rocks, QS: quartzites and sandstones, Sl: slates.
Figure 4. Spatial distribution maps (A) and violin plots (B,C) of major elements (all data are expressed as a percentage). ASQ: alternations of shales and quartzites, IR: igneous rocks, QS: quartzites and sandstones, Sl: slates.
Applsci 12 11351 g004aApplsci 12 11351 g004b
Applsci 12 11351 g005a 550Applsci 12 11351 g005b 550
Figure 5. Spatial distribution maps (A) and violin plots (B,C) of trace elements (all data are expressed as mg kg−1). ASQ: alternations of shales and quartzites, IR: igneous rocks, QS: quartzites and sandstones, Sl: slates.
Figure 5. Spatial distribution maps (A) and violin plots (B,C) of trace elements (all data are expressed as mg kg−1). ASQ: alternations of shales and quartzites, IR: igneous rocks, QS: quartzites and sandstones, Sl: slates.
Applsci 12 11351 g005aApplsci 12 11351 g005b
Applsci 12 11351 g006 550
Figure 6. Spatial distribution of factors. A geological scheme is provided as a reference with the main mines indicated, separated by elements or genetic type.
Figure 6. Spatial distribution of factors. A geological scheme is provided as a reference with the main mines indicated, separated by elements or genetic type.
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Table
Table 1. Statistical summary of pedological parameters. Abbreviations: SD: standard deviation; SOM: soil organic matter; VC: variation coefficient. Complete data available in Table S1.
Table 1. Statistical summary of pedological parameters. Abbreviations: SD: standard deviation; SOM: soil organic matter; VC: variation coefficient. Complete data available in Table S1.
VariableAverageSDVCMinimumMaximum
All data
pH6.10.58.34.57.8
EC (µS cm−1)30.020.047.910.0110.0
SOM (%)4.91.836.91.513.3
Almadén syncline
pH6.00.58.24.87.0
EC (µS cm−1)30.020.050.420.0110.0
SOM (%)5.52.137.11.513.3
Guadalmez syncline
pH6.10.58.54.57.8
EC (µS cm−1)30.010.044.110.090.0
SOM (%)4.41.534.41.98.9
Table
Table 2. Statistical summary of major (in %) and trace elements (in mg kg−1). Abbreviations: standard deviation (SD); variation coefficient (VC). Complete data available in Table S1.
Table 2. Statistical summary of major (in %) and trace elements (in mg kg−1). Abbreviations: standard deviation (SD); variation coefficient (VC). Complete data available in Table S1.
UnitAverageSDVCMinMaxRef. values Spanish soils [17]Ref. values in Castilla–La Mancha soils [18]
Al%1.00.659.20.33.76.2---
Ca %0.20.2100.90.11.15.3---
Fe %3.51.749.40.68.03.0---
K %0.10.148.60.10.31.9---
Mg%0.20.3144.20.12.30.9---
Si %24.02.811.616.130.2------
Namg kg−1100.0100.053.6100.0200.07600.0---
As mg kg−115.319.4126.53.0190.021.716.1
Agmg kg−10.150.2143.10.11.90.11---
Ba mg kg−1114.387.476.430.0740.0400.31049.3
Be mg kg−11.00.442.00.32.02.7---
Co mg kg−114.310.372.31.065.011.720.8
Cr mg kg−134.237.9110.92.0292.070.2113.4
Cu mg kg−118.313.875.43.093.025.927.1
Hg mg kg−12.97.5258.30.151.50.1---
Mn mg kg−1619.0397.664.229.02300.0608.7---
Ni mg kg−126.830.3113.32.0216.032.742.6
P mg kg−1430.9313.172.7120.02000.0590.0---
Pbmg kg−156.5130.6231.015.01190.037.844.2
Sbmg kg−14.16.2151.71.045.02.1---
Sr mg kg−113.99.870.45.081.0159.41868.4
V mg kg−135.031.790.78.0226.060.0123.2
Zn mg kg−151.928.655.09.0146.074.286.5
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Barquero, J.I.; Lorenzo, S.; Esbrí, J.M.; Rivera, S.; González-Valoys, A.C.; García-Ordiales, E.; Higueras, P. Geochemical Assessment of Mineral Resource Potential in a Hg-Sb-Pb-Zn Mining Area: The Almadén and Guadalmez Synclines (South-Central Spain). Appl. Sci. 2022, 12, 11351. https://doi.org/10.3390/app122211351

AMA Style

Barquero JI, Lorenzo S, Esbrí JM, Rivera S, González-Valoys AC, García-Ordiales E, Higueras P. Geochemical Assessment of Mineral Resource Potential in a Hg-Sb-Pb-Zn Mining Area: The Almadén and Guadalmez Synclines (South-Central Spain). Applied Sciences. 2022; 12(22):11351. https://doi.org/10.3390/app122211351

Chicago/Turabian Style

Barquero, José Ignacio, Saturnino Lorenzo, José M. Esbrí, Sofía Rivera, Ana C. González-Valoys, Efrén García-Ordiales, and Pablo Higueras. 2022. "Geochemical Assessment of Mineral Resource Potential in a Hg-Sb-Pb-Zn Mining Area: The Almadén and Guadalmez Synclines (South-Central Spain)" Applied Sciences 12, no. 22: 11351. https://doi.org/10.3390/app122211351

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