Introduction

The Earth’s surface is covered by a thin layer of material known as soil, which is formed by the weathering of rocks. Geochemical analysis of soil can provide valuable insights, as immobile oxide major and trace elements have been identified as useful indicators of land sources, weathering, tectonic settings, and environmental evolution1,2,3.

The southern region of Cameroon, which is situated in the Gulf of Guinea, presents promising prospects for mineralogical and geological surveys. Exploration works carried out in this area by the French Office of Geological and Mining Research4 confirmed the existence of uranium-bearing formations in Lolodorf. Moreover, many investigations have defined the area as a high background radiation area (HBRA)4,5,6,7. Therefore, attention should mainly focus on environmental monitoring in these areas8. Several studies have been conducted to evaluate natural radioactivity in the uranium-bearing areas of Lolodorf and its surroundings4,5,6,7,9,10. There is limited information available on the area’s geochemical background. It is therefore essential to analyze the elemental composition of environmental samples, including soil, water, plants, and air, to obtain geochemical baseline data, which is a crucial component of strategic and systematic geoscience surveys11,12. This approach will aid in identifying any potential mass fraction enhancement of harmful elements in the area. The data collected will help to understand the environmental history of the area and will assist in identifying the geological provenance of the area under investigation.

To achieve this goal, energy-dispersive X-ray fluorescence (EDXRF) spectroscopy was used to characterize the environmental samples. Compared with the use of alpha particles, and other types of spectroscopy methods, such as atomic absorption spectrometry (AAS), inductively coupled plasma-atomic emission spectrometry (ICP‒AES), and inductively coupled plasma‒mass spectrometry (ICP-MS) which require delicate preparation and alteration of the sample during preparation, it is widely used as a non-destructive and relatively rapid technique13,14,15,16. EDXRF is a valuable analytical technique widely used in the fields of geochemistry and mineralogy to determine the elemental composition of rocks, minerals, and other geological materials and to assess the geological provenance of samples17,18,19,20,21. More recently, geochemical data from terrestrial deposits have been used as a provenance tool by researchers. In 2023, Carita et al. (2023) demonstrated that both K2O/Na2O and immobile trace-elements ratio are suitable indicators of geological deposits’ provenance22. Moreover, high-resolution XRF (X-ray fluorescence) core scanning could be used to reveal the depositional history of geological formations, as recently assessed by Shane et al. (2024)23 for the case of northeastern British Columbia in Canada. In Cameroon, a few studies have been performed on elemental composition and geological provenance of geological (sand) samples from Douala using the XRF method. Guembou et al. (2019) research showed that XRF yielded quantitative major, minor, and trace element mass fractions used in tectonic discrimination diagrams. They found that the investigated area was deposited in a passive margin environment19,20.

This study aims to perform a quantitative elemental analysis of soil samples collected around the high background radiation area (HBRA) in Lolodorf. The elemental mass fractions of oxide and minor elements are used thereafter to determine the geological origin of the investigated soil. Two locations surrounding the uranium deposit in Lolodorf (Awanda and Mvengue) yielded a total of ten soil samples. The analyzed soil samples were investigated using an energy dispersive X-ray fluorescence spectrometer (SPECTRO XEPOS) to obtain more sensitive and accurate results. This method has recently been used in Cameroon for accurate elemental characterization of samples and determination of the geological provenance of a certain type of soil17,18,19,20,21,24,25,26. While this study focuses on assessing the geological provenance of the soil through oxide geochemistry, understanding these characteristics is also relevant for evaluating soil behavior in agro-environmental settings near uranium-rich formations.

Materials and methods

Description of the study areas

The study area is located in the southern region of Cameroon in the Mvengue Subdivision, Ocean Division, close to the Lolodorf uranium deposit (see Fig. 1). Two sampling sites, Awanda and Mvengue, were chosen for their proximity to the uranium deposits. The rural district of Mvengue and the village of Awanda have populations of approximately 1326 and 936 inhabitants, respectively. The population density ranges from 8 to 11 individuals per km2. Over 80% of the population primarily engages in subsistence agriculture27.

The study area is located in an equatorial climate characterized by two rainy seasons and two dry seasons. The dry seasons are from December to February and from July to August, while the rainy seasons extend from September to November and from March to June. The annual rainfall ranges from 1500 to 2000 mm, with 70–80% relative humidity recorded throughout the year. The mean temperature of the zone varies from 25 to 26 °C. According to the world map of the Köppen-Geiger climate classification28this climate is classified as Am.

The investigated area belongs to the Nyong complex, with formations mainly composed of paleoprotozoic edges29. There are two types of soil: ferralitic soils with deep-red and yellow‒red colors and hydromorphic soils found in the southern region of Cameroon. These soils are globally acidic. The lithology in this region typically consists of syenites and radioactive source rocks, composed of syntectonic syenites that appear to be associated with a shear zone10.

Soil sampling and sample preparation

Ten soil samples were collected from Awanda and Mvengue, two areas close to Lolodorf’s uranium deposits, in the southern region of Cameroon, as depicted in Fig. 1. The sampling points are located in agricultural zones. To guarantee representativeness and prevent contamination, appropriate on-site sampling techniques were employed during the collection of all samples9. At each sampling point, an area of 1 m2 was identified. The humus layer was removed with a flat-bladed shovel to remove new soil formed as a result of weathering and erosion processes. Soil samples were taken at depths between 5 and 15 cm from each corner of the 1 m2 area and the center, ensuring that metric measurements and units were strictly adhered to. This method ensured that samples were collected to represent the natural soil matrix for provenance analysis, without targeting anthropogenic influence or agricultural amendment. The five subsamples of soil were pooled together to form a composite sample. A labeled polyethylene bag was used to store approximately 2 kg of each fresh sample. The geographic coordinates of sampling points and soil sample codes are given in Table 1. The soil samples collected were transported to the Institute of Geological and Mining Research in Yaoundé for proper preparation.

In the laboratory, every soil sample was prepared according to the Nuclear Technology Section of IRGM protocols as per30. Any large particles were removed from the samples, and the remaining particles were dried in a Gallenkamp Hotbox oven with a fan size of 2 m3 for 3 days at 100 °C. The samples were then ground using a Frisch Pulverizette from Germany at speeds up to 60 rpm and sieved at approximately 2 mm diameter. To ensure greater accuracy in the XRF analysis, 10 g of each sieved sample was crushed in an agate mortar to obtain diameters in the micron range (~ 2 μm).

Table 1 Geographic coordinates of sampling points and soil sample codes.
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Fig. 1
Fig. 1
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Map of the Awanda and Mvengue study areas, located in the Mvengue Subdivision, Ocean Division, close to the Lolodorf uranium deposit in the southern region of Cameroon31.

XRF spectrometry equipment and analysis

The elemental composition of the soil samples was determined using an energy dispersive X-ray fluorescence (EDXRF) Spectro Xepos spectrometer (XPOS05) at the National Radiation Protection Agency (in the laboratory of radioanalysis and spectrometry) in Yaounde, Cameroon. The Spectro EDXRF Analyzer Pro software interface was used for spectral acquisition and quantification. Mass fraction calculations of major, minor, and trace elements in the soil samples were conducted using TurboQuant II, a powerful tool for effortless analysis of unknown samples. This method uses automatic matrix correction without requiring specific calibration for every change in the matrix. A simplified schematic diagram of the equipment is presented in Fig. 2, along with a picture of the EDXRF Spectro Xepos Spectrometer. The spectrometer is fitted with a 30 mm2 Si-drift detector (SDD) equipped with a Peltier cooling system to attain high spectral resolution (FWHM ≤ 155 eV for Mn‒Kα), ultra-sensitivity, precision, a high-count rate (up to 1000000 cps), and low detection limits (to 1 ppm or lower). The detailed detector characteristics and measuring conditions are shown in Table 2.

Table 2 Measurement conditions for the EDXRF analysis of soil samples using the spectro Xepos spectrometer. The atmosphere is always air, the duration of each measurement is set to 150 s, and the anode material is made of Pd/Co.
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Fig. 2
Fig. 2
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Experimental setup. Up left: Picture of the Spectro XEPOS EDXRF equipment. Up right: Schematic picture of the operating principle of the equipment. Bottom: Schematic diagram of the basic operating principle of the EDXRF Spectro XEPOS spectrometer.

To ensure accurate and precise investigation of the soil data, in accordance with quality control protocols, we used Certified Reference Materials (CRMs) from the Wageningen Evaluating Programs for Analytical Laboratories (WEPAL), namely, Organic Ferrasol (ISE998) and Heavy Clay (ISE953). The obtained results, as displayed in Table 3, show excellent agreement between measured and certified values. An exception is observed for MgO with little effect, as the deviation was found around 20%.

Table 3 Measurement results (in mg/kg) of certified reference materials ISE953 and ISE998.
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Uncertainty calculations were performed for the EDXRF measurements. The relative uncertainty of the analyzed soil sample is given by the following equation:

$$\:\:U\left(A\right)/A\:=\:\text{k}\sqrt{{\left(u\left(I\right)/I\right)}^{2}\:+{\left(u\left(m\right)/m\right)}^{2}\:}$$
(1)

For the present work, we considered an enlargement factor k = 1; \(\:u\left(I\right)/I\:\)is the uncertainty linked to the counting statistic and given by the analysis report; I is the count rate of analyzed soil samples;\(\:\:u\left(I\right)\) is the absolute uncertainty of the count rate; and \(\:u\left(m\right)/m\:\)is the uncertainty in the measurement of soil sample masses. Given that the uncertainty in the measurement of soil sample masses follows a rectangular distribution, the uncertainty in the measurement of soil sample masses can be expressed as:

$$\:u\left(m\right)/m\:={\:m}_{min}/2\sqrt{3}m$$
(2)

where \(\:{m}_{min}\) is the minimum mass detectable by the balance and given by the manufacturer, and m is the measured soil sample mass. We note that the other sources of uncertainty are negligible.

Geological provenance assessment

To track the origin of geological materials, such as soil samples, the geochemical composition, particularly the distribution of major oxides and selected trace elements, is often used. Among these, TiO2 (or Ti) is widely regarded as one of the most robust and immobile indicators due to its resistance to chemical weathering and its strong lithological association with heavy accessory minerals such as rutile and ilmenite. Consequently, in the present study, TiO2 was employed as a key discriminator in the application of tectonic setting diagrams, specifically for classifying sedimentary provenance in relation to passive or active margin contexts. Additionally, SiO2 and Al2O3 were considered, as they are frequently used in sedimentary and soil provenance analyses due to their abundance and diagnostic value in reflecting source rock composition and weathering processes. However, their concentrations can be significantly influenced by textural parameters, namely grain size, sorting, and clay content, making them potentially misleading when used in isolation. To account for this, these oxides were interpreted in conjunction with other major oxides to minimize misclassification related to sediment maturity or sedimentary sorting effects22.

Furthermore, other oxides like CaO, MnO, Fe2O3, and MgO were included in the analysis, not only to provide a complete geochemical fingerprint but also because they may contribute to certain geochemical discrimination indices. While their provenance potential is more limited due to higher mobility under certain environmental conditions, such as acidic pH, redox fluctuations, they still offer valuable contextual information, particularly when interpreting the degree of weathering, diagenesis, or secondary enrichment. These parameters collectively inform the geochemical classification and provenance interpretations discussed in the following Sect22.

Results and discussion

Elemental composition of the investigated soil samples

The detailed description of the elemental composition of the samples can be found at31. The average mass fractions of major and minor elements in the ten soil samples under investigation are presented in Table 4 and illustrated in Fig. 4. SiO2 (44.32–53.89%, with a mean value of 49.81%) and Al2O3 (39.79–46.32%, with a mean value of 42.18%) were the most abundant elements across all the soil samples. The remaining elements follow a specific order. The mean values of the components in descending order were as follows: Fe₂O₃ (0.001033-0.9560%, with a mean value of 0.856%), TiO2 (1.183–1.607%, with a mean value of 1.360%), K₂O (0.2988–0.8478%, with a mean value of 0.5273%), CaO (0.0206–0.5666%, with a mean value of 0.2206%), P₂O₅ (0.0417–0.3503%, with a mean value of 0.1711%), MnO (0.0143–0.0715%, with a mean value of 0.0378%), and SO₃ (0.0000-0.0639%, with a mean value of 0.0106%). Na2O and MgO were not detected, likely because they were present in very low mass fractions in the sample and are light elements on the periodic table, making them difficult to detect by EDXRF.

The low levels of TiO2, K2O, CaO, P2O5, and SO3 in the soil samples investigated are attributed to the loss of these elements during alteration32. These elements are highly mobile in acidic soil33,34. Conversely, the high abundances of SiO2, Al2O3, and Fe2O3 are due to the enrichment of these elements, which have low mobility. The soil geochemistry results indicate that the primary components are SiO2, Al2O3, and Fe2O3, which is consistent with the elemental composition of other soil samples analyzed in various research studies18,33,35,36. SiO2 and Al2O3 are nearly equal in magnitude (SiO2/Al2O3 = 1.18). Of the samples analyzed, the highest and lowest levels of SiO2 are found in samples M4 at 53.89% and M3 at 44.32%, respectively. The highest and lowest levels of Al2O3 are obtained from samples M3 (46.32%) and M4 (39.79%), respectively. The Fe₂O₃ mass fraction is lower than that of SiO2 and Al2O3, with the lowest value obtained for M3 (0.001033%) and the highest value obtained for M1 (0.9560%).

Fig. 3
Fig. 3
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Plot of upper crust elements mass fraction provided by Rudnick & Gao. (2003)37 divided by the element’s mass fraction obtained in the present study.

The comparison of major elements mass fractions obtained in the present work with the upper crust major elements mass fraction provided by Rudnick & Gao. (2003)37 is illustrated in Fig. 3. The plot reveals substantial geochemical deviations. Notably, the elemental concentrations of Al2O3 and TiO2 in the present study were 2.81 and 2.13 times higher than those provided by Rudnick & Gao (2003), respectively; whereas, the mass fractions of CaO, Fe2O3, K2O, and MnO were about 16.24, 5.88, 5.31, and 2.63 times smaller than the upper crust values of Rudnick & Gao (2003)37, respectively. These variations are characteristic of tropical weathering profiles, where intense leaching under humid conditions depletes base cations and enriches immobile elements such as Al or Ti.

The high Al2O3 content combined with the marked deficiency of nutrient-bearing oxides such as CaO, K2O, and P2O5 confirms the feralitic nature of the soil in the study area, consistent with prior studies reported by Ben-Bolie et al. (2013)9. This could be explained by the fact that these soils are formed under sustained chemical weathering of aluminosilicate bedrock in the equatorial climate zone, leading to residual accumulation of aluminum oxides and iron oxides and loss of nutrient elements. Considering the fact that the study area lies within an agricultural zone adjacent to the uranium-bearing area of Lolodorf, the observed depletion in essential macronutrients such as potassium and calcium raises concern for long-term soil fertility and food crop productivity. Farmers relying on such soils may face challenges in maintaining yields without substantial amendments. Moreover, the natural geochemical background influenced by uranium mineralization may enhance the mobility and bioavailability of certain trace metal elements (TMEs), thereby posing potential risks to food safety and human health. These findings underscore the importance of integrating geochemical monitoring with agricultural land management and public health policies in uranium-bearing regions.

Table 4 Mass fractions (%) of major and minor elements in the investigated soil samples.
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Fig. 4
Fig. 4
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Chart of the elemental mass fractions of major and minor elements in the investigated soil samples.

Geological provenance of the soil in the investigated area

The positive correlation between K2O and Al2O3 presented in Fig. 5 indicates that the mass fraction of K-bearing minerals significantly affects the Al distribution. This suggests that clay minerals primarily control the relative abundance of Al33,38. The diagrams presented in Figs. 6 and 7 depict Herron’s classification39 of the investigated soil samples into two distinct categories and the frequency distribution of the classification. Shale accounted for 70% (M1, M4, M5, M6, A2, A3, and A4), and arkose accounted for 30% (M2, M3, A1) of the samples collected from the investigated area within the Gulf of Guinea coast and its environs. These findings reflect the continuous weathering process in the area23,40,41. Weathering is the most active effect in place in the investigated area. The elemental mass fraction of soil rock is affected by pre-, syn-, and post-depositional conditions and processes that are to be considered for tectonic classification. These conditions and processes include the soil type available for erosion, the meteorological conditions or climate, the sorting effects, the biogenic material (carbonate, phosphate, and silica), and secondary minerals22.

Fig. 5
Fig. 5
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A slightly positive correlation (R2 = 0.0005) between K2O and Al2O3 elemental mass fraction in the investigated soil samples.

Fig. 6
Fig. 6
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Diagram of Chemical classification of analyzed soil samples based on discrimination diagrams using log (SiO2/Al2O3) and log (Fe₂O₃/K2O) values (37). *Lith refers to litharenite, and Slith refers to sublitharenite.

Fig. 7
Fig. 7
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Frequency diagram showing the classification of the investigated soil samples into two groups.

Figure 8 shows TiO2 (%) as a function of Fe₂O₃+MgO (%). This diagram is compared with the well-known diagram for the tectonic discrimination of geological land or sediment provenance published by Bhatia42. As can be seen in Fig. 8, it is clear that all the investigated soil samples are representative of the residue from the passive margin. This finding is in line with the result published by Guembou et al. (2019) about sand samples collected from Douala, in the Littoral region of Cameroon, about 300 km away from the site investigated in the present study19.

Figure 9 illustrates the proportion of Al2O3/SiO2 (%) as a function of Fe₂O₃ + MgO (%). To understand the current processes in the research area, a tectonic discrimination diagram can be used to track the origin of the samples investigated to understand some processes that are continuing in the study area42,43. From the figures drawn here, it is evident from the comparison of the two diagrams that the investigated samples are all residual materials derived from passive margins. Similar conclusions were drawn in research studies published by Guembou et al. (2019)19. Compared to previous studies, the results obtained in this research support the data provided by previous authors. The investigated area is part or linked to the Gulf of Guinea characterized by low relief land and long river systems that extend from the shore land to the Atlantic Ocean, and a collection of thick piles of sedimentary detritus on the main shelves44,45. Therefore, weathering and erosion processes have a major effect on the geological provenance of the investigated areas. Moreover, the soil (geological materials) found in the Gulf of Guinea is acidic intrusive igneous resulting from the alteration of granite rock type and metamorphic as gneiss rock type. It also justifies the observed high levels of SiO2 and Al2O3 found in the investigated samples43,46.

The findings of this study suggest that the examined and surrounding regions were shaped by erosion and weathering processes rather than tectonic activity. The area mostly consists of acidic metamorphic rocks such as gneiss, syenite, and amphibolo-pyroxenite, and no evidence of tectonic activity has been found in the area. Previous research has confirmed that this location is situated within the Gulf of Guinea, a passive continental margin18,36. Using the elemental composition of soil samples to determine their geological origin is an active area of research, as demonstrated in this paper and in previous research18,19,20,47. In Cameroon, Schluter’s (2008) research reveals that the Douala and Rio-del-Rey offshore basins are classic examples of passive margin basins that originated during the opening of the Atlantic Ocean. This finding sheds light on the geological history of these regions and highlights their potential for further exploration and study19,48. Therefore, the conclusions drawn in the present research are plausible evidence of the extension of the passive margin to the Mvengue and Awanda localities.

Fig. 8
Fig. 8
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TiO2 (%) as a function of the Fe2O3 + MgO (%) diagram (a diagram for the tectonic discrimination of sediment provenance) plot for all investigated sample points: (a). Direct scale visualization; (b). The classification diagram indicates that the samples from the study area have passive margin provenances, with no samples having continental margin, continental arc, or oceanic arc provenances.

Fig. 9
Fig. 9
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AlO3/SiO2 (%) as a function of Fe2O3 + MgO (%): (a). Direct scale visualization; (b). A classification diagram showing that all the samples are from the passive margin.

The enrichment in Al2O3 and TiO2, along with the depletion of CaO, K2O, and P2O5, supports a ferrallitic weathering profile typical of equatorial passive margins. These compositional patterns reflect prolonged chemical weathering and the influence of local parent rock, possibly of granitic and metasedimentary origin. Such mineralogical compositions are consistent with soils derived from the weathering of Precambrian basement rocks commonly observed in Southern Cameroon. Although this study does not focus on trace metal mobility, it is important to note that the dominance of Al and Fe oxides may influence the retention of trace elements, including those of potential environmental concern. In agricultural zones near uranium-bearing formations, such as the Mvengue Subdivision, these geochemical properties can play an indirect role in nutrient cycling and metal transport, meriting further investigation in future studies using the overall elemental composition obtained31.

Conclusions

Quantitative analysis was carried out on soil samples collected from two localities, Mvengue and Awanda, located near the uranium deposit in South Cameroon, using an EDXRF Spectro Xepos spectrometer. The mass fractions of major oxide elements were utilized to determine the geochemistry of the area under investigation. Initially, the correlation between Al2O3 and K2O was studied by plotting Al2O3 as a function of K2O, which revealed a positive correlation. Next, chemical classification of the analyzed soil sample was carried out using Herron’s discrimination diagram, revealing two types of sediments: shale and arkose. Finally, tectonic diagrams illustrating the geological provenance of sediment and land were plotted. These diagrams demonstrate that the study area lies within the continental passive margin. The data obtained from this study are consistent with previous research, which showed that the study area is located in the Gulf of Guinea, a passive continental margin with no tectonic activity. The soil in this area is a product of weathering and erosion processes. The present findings help to elucidate the process of soil formation, and our future studies will focus on identifying the presence of uranium and petroleum resources in these localities. In addition, the data will serve as a baseline for the geochemistry of the area.

While the findings primarily inform the geological history of the study area, they also provide a foundational understanding of soil geochemistry relevant to evaluating trace element mobility and nutrient dynamics in surrounding agricultural environments. The results yielded by the present research can serve as an initial database for assessing the elemental composition of soils in the localities of Mvengue and Awanda and as a guide for future studies.