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Article

Geostatistical and Food Risk Assessment of Soils Contaminated by Trace Elements in the City of Dschang (Cameroon)

by
Denis Lekemo
1,
Thierry Lebeau
2,*,
Innocent Amani
1,3,
Emmanuel Rodrigue Kenne
1,
Honorine Ntangmo Tsafack
4,
Pierre Gaudin
2 and
Émile Temgoua
1
1
Department of Soil Sciences, Faculty of Agronomy and Agricultural Sciences, University of Dschang, Dschang P.O. Box 222, Cameroon
2
Laboratory of Planetology and Geosciences, LPG UMR 6112, Nantes University, National Center for Scientific Research (CNRS), 44322 Cedex 3 Nantes, France
3
Department of Crop Production, Catholic University La Sapientia of Goma, Kituku N02, Goma P.O. Box 50, Democratic Republic of the Congo
4
Department of Animal Biology, Faculty of Sciences, University of Dschang, Dschang P.O. Box 222, Cameroon
*
Author to whom correspondence should be addressed.
Urban Sci. 2025, 9(11), 467; https://doi.org/10.3390/urbansci9110467
Submission received: 31 July 2025 / Revised: 3 October 2025 / Accepted: 29 October 2025 / Published: 7 November 2025
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Abstract

Spatial distribution of trace elements (TEs) in soils of the city of Dschang (Cameroon) was studied to identify their origin (geogenic vs. anthropogenic). The topsoil (at different depths) of 71 sites was analyzed using the rapid portable X-ray fluorescence analysis method. Soils from locations associated with metal-related activities exhibited the highest levels of contamination (average concentrations in mg kg−1: As, 8.2; Cr, 213.7; Cu, 201.8; Pb, 97.4; Zn, 838.0), followed by household waste dumps and agricultural plots (levels close to those of cultivated low-lying areas). The observed decrease in TE concentrations with depth (notably for Zn) supports the hypothesis of a human origin (compared with soil-geochemical background of control sites). Geostatistical approach indicated an underestimation of health risks associated with the consumption of crops from several sites. Specifically, 87.32%, 49.30%, and 47.89% of the sites exceeded the Food Crops Reference Value (FCRV) for Cr, Zn, and Cu, respectively. Additionally, the number of contaminated sites for each TE varies depending on the method: Cu > Zn > Pb > Cr > As = Ni > Cd and Cr > Zn > Cu > Ni > Pb > As > Cd with the geostatistical and FCRV approach respectively. From the first step of the soil chemical quality investigation, our study highlights the need to use methods based on health risks, especially for sensitive uses of soils such as food production.

1. Introduction

With the growing increase in the number of inhabitants living in urban areas (quintupling of the urban population since 1950, representing 58% of the total population today and 68% projected in 2050 [1], the question of soil quality is becoming more and more acute, especially when they serve as a support for food. Yet urban areas also have the highest densities of human activities that generate (and have generated in the past) various contaminants depending on the activities, including trace elements (TEs) [2]. Thus, it is commonly recognized that urban soils are more contaminated than agricultural or “natural” surroundings soils [3].
Like most African cities, Dschang, a city in the West part of Cameroon, has experienced significant demographic and economic growth over the past two decades, with its population likely to double over the next twenty years [4]. This expansion is accompanied by an intensification of anthropogenic activities, confronting cities with the major challenge of waste management, including waste from artisanal and household activities [5], with obvious impacts on the environment.
Although it is a reference in Cameroon in terms of waste management and recovery [6,7], the city of Dschang is still currently experiencing difficulties in managing waste due to lack of adequate equipment and accessibility to certain districts [8]. This circumstance compels the community to adopt alternative palliative strategies for waste management, a scenario observed in numerous other urban areas [9]. Wastes are either dumped (sorted or not) in areas set aside for this purpose in the neighborhoods, spread over cultivated plots, buried, or incinerated, leading to the proliferation of illegal dumpsites. Wastes can contain TEs such as As, Cd, Cr, Cu, Hg, Ni, Pb and Zn, which can contaminate soil, water and air [10], with consequences on the quality of food crops in urban neighborhoods. Ultimately, all the direct and indirect exposure of residing populations to these TEs affects public health [11]. For example, the exposure of craftsmen to TEs in informal economy of recycling waste electrical and electronic equipment (WEEE) has been highlighted [12]. Similarly, artisanal activities such as metalworks, boiler fabrication, car repair, printing, agriculture, etc., contribute to environmental contamination of TEs, including soil contamination, in the absence of management of waste from these activities. It should be noted that diffuse contamination can occur alongside hotspots [13].
Spatial approach to contamination assessment provides a territorial assessment of soil quality that can be used as an initial approach to identify sources and origins of pollution and their degree of spatial heterogeneity. Associated with this, urban historical inventories provide, when sufficiently documented archives exist, valuable information to identify the sources of contamination. The exploitation of these archives then allows field diagnostics to be directed towards the contaminants likely to be found there [14]. The use of appropriate contamination threshold can also help to draw up an initial risk assessment. A number of studies in Europe [15,16] and China [17,18] have used this approach to spatialize soil contamination, which is essential for territorial management, but they are based on a geostatistical approach to the distribution of contamination values rather than on a risk approach in the case of crop soils, for example. Cities in Africa have been studied little [19,20] which was point out in a recent meta-analysis conducted by Hou et al. [21] where nearly 800,000 analyses worldwide reveals that 16% of soils for foods are polluted by TEs, with a high risk for public health (0.9 to 1.4 billion inhabitants living in these regions) and the environment. As for most African cities, in Dschang (Cameroon), there has been no study on spatial analysis of TEs in soils, nor any study of sources of contaminants or risks to the population. Thus, the potential effects of human activities on the environment need to be assessed, which requires a sufficiently robust, inexpensive and fast method for an initial diagnosis of environmental pollution risk assessment by TEs [22]. Full risk assessment methods are very time-consuming and expensive because they generally include 1/TEs analysis in soils and plants by analytical methods requiring soil treatment before ICP analysis in the laboratory, 2/evaluation of the quantities of soil ingested and inhaled and of vegetables consumed, 3/consideration of consumers’ eating habits, their frequentation of cultivated sites, etc. To reduce the costs for such studies and the time needed to conduct them, simplified studies are carried out that do not consider the spatial heterogeneity of soil contamination nor the diversity of contaminations. The use of portable X-ray fluorescence, which makes it possible to acquire data in situ, quickly, has made it possible to better consider this spatial heterogeneity and also to provide pre-diagnostics of soil contamination at a lower cost (crucial issue in developing countries). The measurement accuracy is now sufficient to quantify soil contamination by different TEs [23] and associate these values with guide or threshold concentrations that allow discriminating areas where cropping should be prohibited or the reverse is in no way risky, and other areas where it is necessary to more precisely assess the risks.
The aim of this study was to develop a method for establishing a first rapid diagnostic evaluation of soil contamination and the risk to cultivate it. To this end, the spatial distribution of As, Cd, Cr, Cu, Ni, Pb and Zn in the soils of the city of Dschang was systematically evaluated and we formulated the hypothesis of an anthropic origin based on the activities observed at the studied sites. Analysis of 71 sites with various activities in the city center was conducted, and for some sites, the distribution of the contamination according to depth was determined to help identify its origin (geogenic or anthropogenic). Spatialization of data based on a geostatistical approach to identify areas with anomalies, was compared with an approach of the risk to cultivate the soils, given the presence of crops in the heart of the city.

2. Material and Methods

2.1. Description of Study Area

Dschang city, headquarters of Menoua Division in the West Region of Cameroon, covers an area of 262 km2. It is located between Latitudes 5°25′ and 5°30′ North and Longitudes 9°50′ and 10°20′ culminating an altitude of 1500 m (Figure 1).
The region exhibits a bimodal rainfall pattern characterized by two distinct seasons: rainy season, which extends from March to November, and the dry season, occurring from December to February. Average annual rainfall is recorded at 1750 mm, with an average temperature of 22.5 °C [24].
According to World Reference Base (WRB) for Soil Resources [25], soils in the study area are Ferralsols, common on western Highlands of Cameroon and Gleysols in the down part of slopes. The main geological formation of Dschang are granite and gneiss [26,27,28].

2.2. Soil Sampling Protocol and Field Inventory of Human Activities

The study comprised 71 sampling sites (Figure 2) among which uncontrolled household waste dumps, agricultural plots, agricultural lowlands, metal-related activities with 2 sites considered to be control sites because they had not been influenced by anthropic activities (located on the outskirts of the city but whose pedological characteristics and geological origin are the same).
The sampling strategy was as follows: (i) denser density of samples in the most populated area of the city, at the same time the one with the most activities likely to pollute the soil, (ii) taking into account the diversity of human activities present in Dschang, (iii) areas where cultivated soils has been observed or would be likely to develop. The areas without analysis correspond to those that are not cultivable (due to topography) and therefore of no interest for our study. P-XRF analyses (see Section 2.3. for details) were carried out at soil surface after possibly removing plant cover and after homogenizing the first 2–3 cm. For each site at least 2 measurements have been carried out by moving the p-XRF to check that we were not dealing with an artifact.
For the highest concentrations in TEs, core sampling was carried out using a hand auger (a removable metal auger, 1 m long, with graduations every 10 cm) with measurements performed at different depths (up to 60 cm which corresponds to the maximum depth of rooting for most cultivated plants). At each depth, the soil was homogenized before analysis.
Our study is partly based on that of urban historical inventories [14] where soil analyses were preceded by field surveys of the activities of the studied sites.

2.3. Laboratory Methods

Soil Samples were analysed in situ using a portable X-ray fluorescence (p-XRF) spectrometer (Vanta M serie model, Evident Corporation under the Olympus/Evident Vanta brand, Nagano, Japan), with a miniature energy dispersive spectrometer (50-kV maximum X-ray tube), a rhodium (Rh) anode target excitation source, and sensitive large-area silicon drift detectors. p-XRF gives total TE concentrations. All TEs concentrations were corrected for soil moisture by drying in an oven at 40 °C to constant weight. Results were then expressed in mg of TEs per kg of dry soil (mg kg−1). The accuracy of the measurements was ensured by comparing the TEs concentrations obtained by p-XRF with 11 certified reference materials (CRMs 141, 143, 143, 144, 145, 277, 320, 1646a, 2711a, CP-1, SS-2), i.e., soil, sediment, sludge, compost in which TEs concentrations were measured after material mineralization and ICP measurements. To improve the accuracy and precision of the measurement, correction factors were applied for the measured elements, i.e., As, Cd, Cr, Cu, Ni, Pb, Zn, and absolute errors were determined.

2.4. Cartograms

2.4.1. Statistical Analysis of Outliers

We used the method of Tukey which was already applied to the detection of anomalous values of trace metal elements in soils [29,30,31]. This method did not rely on assumptions of normality but only on the inherent structure of the processed data. It has two advantages: (i) clear description of the extent and dissymmetry of the data (ii) objective identification of anomalous values (i.e., outliers). An outlier is therefore a statistically “anomalous” value in relation to a certain population and only in relation to the structure of this population. Thus, a value that proves to be outlier in a given pedogeochemical context is not necessarily outlier in another context.
In the case of our study, upper outliers are TE concentration values higher than the upper whisker, which is calculated using the following formula:
UW = Q3 + α IQD
LW = Q1 − α IQD
With UW: Upper whisker in (1); LW: Lower whisker in (2).
Q1: 1st quartile; Q3: 3rd quartile; IQD: Inter Quartile Distance (IQD = Q3 − Q1); α: whisker coefficient (where α = 1.5).
As the lower whisker is meaningless for determining any TEs contamination, only the upper whisker were calculated for this purpose using RStudio software.
The classification of soil TEs concentrations is based on 2 classes: (i) no anomaly for concentrations below the upper whisker, (ii) presence of anomaly for concentrations above the upper whisker.

2.4.2. Health Risk Assessment

Regional Health Agency (RHA) guidelines of Ile de France [32] proposes TEs concentration values to avoid overexposing site users and/or consumers in the case of food or ornamental crops. It has the advantage of considering the risk and not relying solely on a statistical approach while the geochemistry of soil can vary depending on the local geological context. The proposed reference values can under no circumstances be considered as regulatory thresholds, but as recommendations. Based on this methodology, 3 classes of contamination have been established based on 2 sets of ‘reference’ threshold values (Table 1):
-
Food Crops Reference Value (FCRV) corresponds to the maximum concentration of TEs for growing food plants in the open ground, without the need for in-depth investigation;
-
Ornamental Crop Reference Value (OCRV) corresponding to the maximum TEs concentration for growing food plants above ground with controlled input soil or in open ground for ornamental plants without the need for in-depth investigation. To maintain food use despite the FCRV being exceeded for at least one TEs, the RHA recommends an in-depth investigation;
-
Above the OCRV, an in-depth survey should be carried out to assess the compatibility of the site with the intended use.

2.4.3. Maps

Maps were produced using ArcGIS 10.8.

2.5. Statistical Analysis

After importing the data from Excel, a PCA of the studied sites in Dschang according to their composition in TE was produced using RStudio software version 2025.05.1+513. FactoMineR version 2.12 and Factoshiny version 2.7packages were used to produce PCA. The correlation matrix that gives significant values with a confidence level of 99.9% was generated with the packages corrplot and hmisc on RStudio. The ellipses corresponding to each group of individuals (i.e., the sites according to their activity) encompass the center of gravity of each group of individuals with a confidence level of 95%.
For the comparison of TE concentrations from the different sites, a normality test was carried out (Shapiro-Wilk test) then a non-parametric test (Kruskal Wallis test) because the data did not follow a normal distribution and finally a post-hoc test (Dunn test) to identify groups that differ with a confidence level of 95%. For Kruskal Wallis and Dunn tests, agricolae and dunn.test were used respectively.

3. Results and Discussion

3.1. Trace Elements (TEs) Concentrations According to Land Use Types

Concentrations of TEs at the surface soil samples according to land use types are given in Table 2.
Sites close to metal-related artisanal activities show on average the highest levels of contamination (statistically different from other activites), followed by uncontrolled landfill sites, then agricultural plots and agricultural lowland sites, which have similar levels of contamination. Between the most contaminated sites and control sites, the concentration ratios are 2.95 (Cr), 9.13 (Cu), 1.2 (Ni), 5.0 (Pb) and 20.8 (Zn). The trace metal most present in the surface horizon of metal-related activity sites is Zn, with an average concentration of 838 mg kg−1, followed by Cu (201.8 mg kg−1) and Cr (213.7 mg kg−1). Whatever land use (except for metal-related sites for Cu and Pb), the order of concentrations is as follows: Zn > Cr > Cu > Pb and Ni > As > Cd. It should be noted that for a given activity, the concentrations found vary greatly (e.g., 40.2 up to 3238.2 mg kg−1 for Zn measured in soils from uncontrolled dumps sites). These differences in concentrations are not surprising with both diffuse and punctual contaminations depending on whether the analyses were carried out at the level of the site of activities (direct soil contamination) or nearby (contamination by dust entrainment or runoff). On the contrary, the values for the control sites are little different.
The differences seem to be explained by anthropogenic activity and not by the soil geochemical background of control soils whose TE concentrations are (largely) lower than those of sites with human activities. It is worth noting that the geological origin of the soils is the same everywhere in Dschang. Anyway, as regards Ni, the concentrations are very close to those of the controls, whatever the use of the sites. This suggests that Ni is not used in human activities. This is also the case for Pb, except for sites used for metal-related activities. To strengthen this hypothesis of a soil contamination related to human activities, Zn/Pb ratio was determined as an indice of anthropogenic activities. The minimum and maximum values are respectively 1.4 and 8.6 for the control soil and the sites occupied by metal processing activities, and intermediate values (up to 3.9) for soils used for food, which is in agreement with the study of Douay et al. [33]. In the example of two former industries established in France, theses authors showed that the Umicore factory, specialized in zinc production, displayed a higher ratio than the Metaleurop smelter which used to be in the top rank of the largest producers of Pb.
A principal component analysis (PCA) was applied to concentrations of As, Cd, Cr, Cu, Ni, Pb, Zn, to identify pollution patterns (Figure 3). The first two PCA axes explain 64.3% of total variance. Axis 1 (43.1%) is strongly correlated with As, Cr, Cu, Pb, Zn, while Axis 2 (21.2%) is mainly associated with Ni. MRA sites are distinctly separated along Axis 1, indicating high trace metal concentrations, particularly Cu and Zn (cos2 > 0.8). Based on the nature and concentrations of TE, and taking into account the type of activities identified in the field, the heterogeneity of the MRA sites (Figure 3b) is explained by the diversity of activities related to metal working. In contrast, control and agricultural sites are clustered near the origin, suggesting minimal contamination. The UD sites are intermediate.
Soil profiles were studied to confirm the origin of TEs encountered in selected sites. In the case of soil contamination of anthropogenic origin, TEs concentrations are expected to decrease with depth until concentrations return to soil-geochemical background values [34]. Conversely, when the origin of TEs is essentially geogenic, a reversed concentration profile is observed—concentrations increase with depth [35]. Figure 4 shows the profile carried out at an uncontrolled dump of unsorted household waste. The concentrations of all TEs decrease with depth until they return to background values between 20 cm and 60 cm depending on the TE. Again, this leads to the conclusion that surface enrichment in TEs is anthropogenic. This decrease in TEs concentration with depth was already observed by Hodomihou et al. [36], in cultivated soils in Senegal (compared with uncultivated soils).
For profile shown in Figure 5 (landfill near the lake), only Zn concentration decreases with depth, returning to the geochemical background value at 60 cm. For the other TEs, the concentrations do not vary with depth and approach those of the pedogeochemical background, which would mean that only Zn is of anthropogenic origin.
The accumulation of particles from waste incineration on soil surface, or simply the decomposition of this TEs-enriched waste (accelerated in tropical climates), is accompanied by the production of TEs-enriched leachates. These leachates explain the increase in TEs concentrations with depth [37]. Although TEs concentrations higher than those of the controls are only observed down to around sixty centimeters (Figure 4 for all TE and Figure 5 only for Zn), there is reason to fear that some of the TEs will migrate into the deeper horizons (or even to the water table), as described by Ekenguele et al. [38]. Anthropogenic TEs have chemical forms that favour their mobility. For example Bouquet et al. [39] showed for soils of the same pedological origin that Pb of anthropogenic origin (from particles emitted by a Pb smelter) was potentially more mobile than Pb of geogenic origin, with respectively 48% and 82% present in the residual fraction (i.e., non-extractable). Thus based on these different analysis and data processing, the hypothesis of the anthropic origin of TE for metal-related activities and uncontrolled dumps is very likely, as it was shown in previous studies [40,41,42,43].
In our study, a variety of wastes have been identified in illegal dumps, mainly mobile phones, batteries, telephone and computer batteries, televisions, computers, forming WEEE containing TEs among other toxic substances [44]. The presence of TEs in the ash from the incineration of these wastes is thought to be the cause of the high concentrations of Zn (289.3 mg kg−1), Cr (123.6 mg kg−1) and Cu (57.9 mg kg−1). Zn present in large quantities in the soils of these dumps could come from TV cathode ray tubes, in which it is present in the form of zinc sulfide [34]. High levels of Cu and Cr could be attributed to the presence of computer monitors and DVD players in the landfills sampled. These metals are among the main components used in the manufacture of these devices, as mentioned by Oguchi et al. [45]. In another study, it was shown that concentrations of As, Cd, Cr, Cu, Hg, Pb and Zn in soils located near municipal solid waste incineration sites in eleven regions in China were twice as high as those in a control agricultural soil [46]. Our results corroborate those of this study, confirming the environmental impact associated with the incineration of waste at dumps, particularly WEEE. Higher TEs levels found in the vicinity of metal-related activities can also be explained by the prolonged accumulation of dust and debris from the processing of these metals, as shown by Ibrahim et al. [37] in Komabangou gold zone in Niger. This study concluded that TEs pollution in these areas was a function of the nature of metals that were transformed.
As far as the agricultural plots are concerned, only Cr (86.8 mg kg−1) and Zn (84.1 mg kg−1) exceeded the FCRV defined by the RHA Île-de-France, while for the metal-related activity sites, concentrations exceed not only the FCRV but also the ORCV. In the case of agricultural plots, these TEs could come from water used to irrigate these plots [47] and from the inputs used in these various plots, such as pesticides [48,49] and chemical fertilizers, mainly urea, which is commonly used by farmers in Dschang [50]. and which could be contaminated with Zn.

3.2. Spatial Distribution of TEs Based on Geostatistical Approach

Sites with TEs concentrations above the whisker level are considered anomalous (Table 3). This means that they have significantly higher values than neighboring points [29]. The advantage of this method is that it compares ‘anomalous’ values only to the other values from analyses in the study, without taking account of local soil geochemical background. In fact, the use of a categorization of concentration values proposed in other studies such as ASPITET program in France [51], would introduce a bias due to soil-geochemical backgrounds that may differ from that of Dschang (different geological substratum). In this case, there would be a risk of over- or under-estimating the enrichment of soils in TEs linked to anthropogenic activities.
The maps (Figure 6) show TEs content based on values of the upper whisker. All the TEs considered in this study are anomalous at several sites. The number of sites where TEs anomalies have been identified follows the following descending order (in brackets, % of sites with anomalous values): Cu (19.72%) > Zn (18.31%) > Pb (9.86%) > Cr (8.45%) > As (7.04%) = Ni (7.04%) > Cd (1.4%). The waste disposal sites and metal-working sites had the highest number of anomalies. Except for Cd, with a single anomaly in the city, sites showing anomalies are often the same, whatever TEs. For example, sites with Cu and Zn anomalies represent 38.03% of all sites. This can be explained by the fact that the activities carried out on these sites, in particular uncontrolled dumping of waste that has not been sorted at source and artisanal practices linked to metal working, generate these sources of contamination. For metal-related activity sites, Cu and Zn contamination is higher at metallurgy sites, while Cr and Pb contamination is higher at sites where various metal objects are warehoused and stored, particularly vehicle bodywork. In the case of uncontrolled waste dumps, Pb and Zn are mainly due to the presence of accumulators containing these elements, such as batteries and telephone batteries present in these dumps. On the other hand, Cu and Cr would come from the presence of metal objects such as drinks cans and kitchen utensils. Overall, anomalous values at various sites were correlated with their use, as shown by the study carried out in Nairobi by [52].
The main limitation of geostatistical methods is that, whatever the method used, it does not incorporate the notion of health risk, and the anomalies detected may therefore over- or under-estimate this risk. In the case of Dschang, the whisker values for Cr, Cu, Ni, Pb and Zn are higher than those recommended by the RHA Ile-de-France (France) guide [32] for the FCRV (Table 1), and values for Cr, Cu and Zn even exceed the ORCV (Table 1). Thus, if we consider only anomalous values as problematic, the health risk would be underestimated in our case. Yet, most maps showing the distribution of TEs concentrations in soils use geostatistical approaches [35,53,54,55,56], which can distort interpretation in terms of assessing risks to human health.

3.3. Spatial Distribution of TEs Based on Food Risk

To better assess the dietary risk of soils used for cultivation in Dschang, maps (Figure 7) were drawn up based on values recommended by the RHA Ile-de-France (France) guide [32]. It is worth noting that there is no consensus at the international level and therefore no universal reference values. Unlike the maps based on a statistical representation of TEs concentration data (Figure 6), the maps in Figure 7 provide an approach to dietary risk based on reference values proposed by RHA, which are based on data acquired on Ile-de-France soils (France) and almost on health recommendations based on international scientific studies. Using this reference framework allows for a quick first diagnosis in terms of risk. Three situations are distinguished: (i) TE concentrations below risk threshold for cultivation (green symbol); (ii) TE concentrations above the risk-free threshold for cultivation but below the threshold for ornamental crops (yellow symbol); (iii) TE concentration above threshold for ornamental crops where management measures must be taken (red symbol). It is in the case of the intermediate situation (yellow symbol) that the diagnosis could then be deepened by a comprehensive health risk assessment [57] based on hazard quotient or individual excess risk (depending on the type of reference toxicological value, i.e., with or without threshold effect). Such diagnosis considers: (i) dietary habits, both in terms of quantity and type of fruits and vegetables (ii) the type of consumers (men, women, children), (iii) exposure pathways (inhalation, soil ingestion, fruit and vegetable consumption), (iv) time spent on the sites considered, etc. Such a diagnosis—extremely lengthy to carry out and expensive—must be deployed in a second phase only at sites where pre-diagnosis cannot conclude accurately that there is a definite risk or no risk (i.e., sites with yellow symbol).
Regarding reference values, the authors of this guide from RHA Ile-de-France (France) state: ‘They should not be interpreted as health thresholds, but solely as reference values, compliance with which will prevent users from being overexposed to the practices in question. Levels higher than these values do not necessarily prohibit gardening, but a compatibility study should be carried out by a specialist consultancy in accordance with the national methodology for managing polluted sites and soils.
Based on the FCRV, the number of sites exceeding the FCRV is presented for each TEs in order (as a % of the total number of sites, each site can be contaminated by several TEs): Cr (87.32%) > Zn (49.30%) > Cu (47.89%) > Ni (22.53%) > Pb (16.9%) > As (5.63%) > Cd (1.40%). It should be noted that order of TEs has changed compared with that for the anomalous values and demonstrating that statistical approach led to an underestimation of the risk. In Dschang, some of the TEs measured are beneficial to humans and animals, but at levels that comply with certain thresholds prescribed by the World Health Organization (WHO), such as Cu and Zn [58]. However, these thresholds are most often exceeded.

4. Conclusions

The aim of this study was to analyze the spatial distribution of trace elements (TEs) in the soils of Dschang and to identify their sources by comparing a geostatistical method with a method that takes account of the risk to human health. To achieve this goal, several sites were sampled according to land use, to assess the impact of human activities on the accumulation of trace elements in soils. Analysis of the spatial distribution of TEs revealed areas of pollution in the urban center linked to various human activities. The most polluting activities are those associated with metal works. The city’s unsorted refuse dumps, where various types of waste are dumped, are also areas of high TEs accumulation. The levels of TEs present in soil at these sites make them most often unsuitable for any agricultural use, according to the recommendations in RHA guide for Ile-de-France region. The results of this study highlight the urgent need for action to reduce environmental contamination by TEs. While mapping the distribution of TEs in soils is generally based on geostatistical methods, we showed in this study that the risk to human health was underestimated, which is an important result to consider in further studies. Our study also highlighted that the use of portable X-ray fluorescence, which makes it possible to acquire data in situ, quickly and with sufficient precision, has made it possible to better consider the spatial heterogeneity of soil contamination (very common in urban areas). Associated with guide or threshold concentrations, areas where food use should be prohibited or the reverse is in no way risky can be determined. For other areas where it is necessary to more precisely assess the risks (sites with yellow symbols), in-depth risk assessment need to be implemented. When the risk is deemed too great to authorize food use, different management solutions exist [59]: (i) Excavating the contaminated soil and replacing it by uncontaminated top soil (called ex situ management), (ii) Excavating the contaminated soil and keeping it on site (called ‘on-site management’), (iii) Managing the contaminants in situ (i.e., ‘in situ management’). It is worth noting that only phytoextraction, that is, the use of plants capable of extracting from the soil, followed by transfer from roots to aerial parts can be applied for the case of TE. Finally, these data provide to the competent authorities, elements necessary to regulate human activities likely to contribute to the excessive accumulation of pollutants in the environment.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/urbansci9110467/s1, Figure S1: Matrix correlation from which PCA (Figure 3) was generated. In blue, significant correlation coefficients (confidence level of 99.9%).

Author Contributions

All authors contributed to the study. Material preparation, data collection and analysis were performed by D.L. and T.L. The first draft of the manuscript was written by D.L. and T.L.; É.T., I.A. and E.R.K. contributed to the writing of the discussion and H.N.T. to the production of the maps. P.G. contributed to resources and validation. All authors have read and agreed to the published version of the manuscript.

Funding

The work was funded by Nantes Metropole (Nantes, France) through the 2023–2025 agreement “Cooperation communities/universities: Quality of food waste compost in Dschang and Nantes Métropole”.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The database (Excel file) of analyses carried out by p-XRF is available for consultation (on request to the corresponding author).

Conflicts of Interest

The authors declare no conflicts of interest.

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Urbansci 09 00467 g001
Figure 1. Location of the city of Dschang (Cameroon).
Figure 1. Location of the city of Dschang (Cameroon).
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Figure 2. Location of sampling points in the study area.
Figure 2. Location of sampling points in the study area.
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Figure 3. Principal component analysis (PCA) of the studied sites in Dschang according to their composition in trace elements: Representation of (a) variables (circle of correlations) and (b) individuals, corresponding to samples sites with their respective number, projected on the factorial plan (Dim1, Dim2). Control, control soil; AP, agricultural plots; AL, agricultural lowlands; UD, uncontrolled dumps; MRA, Metal-related activities (correlation matrix is given in Supplementary Data Figure S1).
Figure 3. Principal component analysis (PCA) of the studied sites in Dschang according to their composition in trace elements: Representation of (a) variables (circle of correlations) and (b) individuals, corresponding to samples sites with their respective number, projected on the factorial plan (Dim1, Dim2). Control, control soil; AP, agricultural plots; AL, agricultural lowlands; UD, uncontrolled dumps; MRA, Metal-related activities (correlation matrix is given in Supplementary Data Figure S1).
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Figure 4. Changes in soil TEs concentrations as a function of depth at an uncontrolled household waste disposal site. The red vertical bar corresponds to the average concentration of the control sites for each TE. Error bars correspond to the measurement error with p-XRF (see Section 2.3 for details).
Figure 4. Changes in soil TEs concentrations as a function of depth at an uncontrolled household waste disposal site. The red vertical bar corresponds to the average concentration of the control sites for each TE. Error bars correspond to the measurement error with p-XRF (see Section 2.3 for details).
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Figure 5. Changes in soil TEs concentrations as a function of depth on a market-garden site located near an uncontrolled landfill site. The red vertical bar corresponds to the average concentration of the control sites for each TE. TEs error bars correspond to the measurement error with p-XRF (see Section 2.3 for details).
Figure 5. Changes in soil TEs concentrations as a function of depth on a market-garden site located near an uncontrolled landfill site. The red vertical bar corresponds to the average concentration of the control sites for each TE. TEs error bars correspond to the measurement error with p-XRF (see Section 2.3 for details).
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Figure 6. Trace elements mapping of surface soils in Dschang according to the ‘upper whisker’ method [30] (see Section 2.4.1 in ‘material and methods’ section for details): (1): As, (2): Cd, (3): Cr, (4): Cu, (5): Ni, (6): Pb, (7): Zn.
Figure 6. Trace elements mapping of surface soils in Dschang according to the ‘upper whisker’ method [30] (see Section 2.4.1 in ‘material and methods’ section for details): (1): As, (2): Cd, (3): Cr, (4): Cu, (5): Ni, (6): Pb, (7): Zn.
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Figure 7. Surface soil TEs maps for Dschang according to health risk approach based on reference values defined by the Regional Health Agency Ile-de-France (France) [32] (see Section 2.4.2. in ‘material and methods’ section for details). (1): As, (2): Cd, (3): Cr, (4): Cu, (5): Ni, (6): Pb, (7): Zn.
Figure 7. Surface soil TEs maps for Dschang according to health risk approach based on reference values defined by the Regional Health Agency Ile-de-France (France) [32] (see Section 2.4.2. in ‘material and methods’ section for details). (1): As, (2): Cd, (3): Cr, (4): Cu, (5): Ni, (6): Pb, (7): Zn.
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Table 1. Reference values defined by the Regional Health Agency, Ile-de-France [32]. FCRV, Food Crops Reference Value; OCRV, Ornamental Crop Reference Value.
Table 1. Reference values defined by the Regional Health Agency, Ile-de-France [32]. FCRV, Food Crops Reference Value; OCRV, Ornamental Crop Reference Value.
Trace ElementFCRVOCRV
mg kg−1 of Dry Soil
As1325
Cd0.52
Cr65128
Cu2867
Ni3167
Pb54100
Zn88195
Table 2. TEs concentrations in the surface soil samples by land use type. Control, control soil; AP, agricultural plots; AL, agricultural lowlands; UD, uncontrolled dumps; MRA, Metal-related activities. Letters stand for homogenous groups according to the Kruskal Wallis test followed by post-hoc Dunn test at the confidence level of 95%.
Table 2. TEs concentrations in the surface soil samples by land use type. Control, control soil; AP, agricultural plots; AL, agricultural lowlands; UD, uncontrolled dumps; MRA, Metal-related activities. Letters stand for homogenous groups according to the Kruskal Wallis test followed by post-hoc Dunn test at the confidence level of 95%.
Control (n = 2)AP (n = 14)AL (n = 15)UD (n = 29)MRA (n = 11)
mg kg−1 of Dry Soil
AsMin<LQ *0000
Mean<LQ *2.1 b2.9 b2.8 b8.2 a
Max<LQ *5.47.210.924.4
CdMin<LQ *0000
Mean<LQ *<LQ *<LQ *0.5<LQ *
Max<LQ *0013.60
CrMin63.322.59.232.7107.2
Mean72.5 b86.8 b109.3 b123.6 b213.7 a
Max81.7110.3256.3357.4576.0
CuMin16.812.47.18.825.6
Mean22.1 b28.3 b21.2 b57.9 b201.8 a
Max2.733.649.5328.9719.7
NiMin20.711.34.79.40
Mean22.5 a27.2 a25.4 a22.5 a26.3 a
Max24.434.642.341.360.1
PbMin25.79.35.18.20
Mean27.8 b21.7 b19.4 b34.3 b97.4 a
Max29.836.045.3137.8355.9
ZnMin35.931.734.240.2104.4
Mean40.2 b84.1 b68.8 b289.3 b838.0 a
Max44.5112.1173.83238.22319.8
Zn/Pb1.43.93.58.48.6
* LQ: Limit of Quantification.
Table 3. Upper whisker in TE (mg kg−1 of dry soil). For the calculation of values, see Section 2.4.1.
Table 3. Upper whisker in TE (mg kg−1 of dry soil). For the calculation of values, see Section 2.4.1.
Trace ElementUpper Whisker
As10.25
Cd0
Cr226.30
Cu72.88
Ni41.28
Pb74.87
Zn285.03
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Lekemo, D.; Lebeau, T.; Amani, I.; Kenne, E.R.; Tsafack, H.N.; Gaudin, P.; Temgoua, É. Geostatistical and Food Risk Assessment of Soils Contaminated by Trace Elements in the City of Dschang (Cameroon). Urban Sci. 2025, 9, 467. https://doi.org/10.3390/urbansci9110467

AMA Style

Lekemo D, Lebeau T, Amani I, Kenne ER, Tsafack HN, Gaudin P, Temgoua É. Geostatistical and Food Risk Assessment of Soils Contaminated by Trace Elements in the City of Dschang (Cameroon). Urban Science. 2025; 9(11):467. https://doi.org/10.3390/urbansci9110467

Chicago/Turabian Style

Lekemo, Denis, Thierry Lebeau, Innocent Amani, Emmanuel Rodrigue Kenne, Honorine Ntangmo Tsafack, Pierre Gaudin, and Émile Temgoua. 2025. "Geostatistical and Food Risk Assessment of Soils Contaminated by Trace Elements in the City of Dschang (Cameroon)" Urban Science 9, no. 11: 467. https://doi.org/10.3390/urbansci9110467

APA Style

Lekemo, D., Lebeau, T., Amani, I., Kenne, E. R., Tsafack, H. N., Gaudin, P., & Temgoua, É. (2025). Geostatistical and Food Risk Assessment of Soils Contaminated by Trace Elements in the City of Dschang (Cameroon). Urban Science, 9(11), 467. https://doi.org/10.3390/urbansci9110467

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