Influence of Natural and Anthropogenic Factors on the Spatial Distribution of Soil Trace Elements in South-Central Ganzhou District, Zhangye City, China

Abstract

The Qilian Mountains are an important ecological security barrier in the western part of China. The south-central part of Ganzhou District in Zhangye City is adjacent to the Qilian Mountains, which is an important battlefield for the construction of ecological environment protection in the Qilian Mountains. It is also a key site for studying the effects of natural and anthropogenic factors on soil geochemical characteristics. However, there is insufficient research on the spatial distribution pattern of soil trace elements and the influencing factors in some areas of the Qilian Mountains. In this work. The authors selected 35 sampling sites in the south-central part of Ganzhou District, Zhangye City, and divided them into three layers according to the depth. The authors completed geochemical elemental characterization and Pearson correlation analysis. This paper analyzed the effects of natural and anthropogenic factors on the spatial distribution of soil trace elements. The authors explored in depth the geochemical elemental characteristics of four typical profiles. The results of the study showed that the average values of Hg and Cr elements in the soil were more than twice the background values of the soil in Gansu Province. However, none of the levels exceeded the national screening values for soil contamination risks on agricultural and construction land in the Soil Environmental Quality Standards. Among them, the Profile2 and Profile4 were more intensely affected by anthropogenic influences. The Profile2 was mainly affected by tourism activities and the Profile4 was mainly affected by agricultural activities. The Profile1 and Profile3 were more influenced by natural factors, mainly by the alluvial flooding of the host rock. The elements Cr, Hg, and Mn were considered to be anthropogenic impact elements. As, Cd, Co, Cu, Ni, and Zn were considered natural influence elements. This study revealed the distribution patterns and influencing factors of 10 soil trace elements, which helped to further understand the influence of anthropogenic and natural factors on soil geochemical processes in the Qilian Mountains.

INTRODUCTION

The Qilian Mountains are an important ecological security barrier in the western part of China [58], and the Zhangye section of the Qilian Mountains National Nature Reserve accounts for 76.4% of the total area of the reserve, which is the main battlefield for the construction of ecological environmental protection in the Qilian Mountains, and a key site for studying the effects of natural and anthropogenic factors on soil geochemical characteristics [51].

The concentration and spatial distribution of elements in soil can be influenced by natural and anthropogenic factors [15]. Natural factors include the geological environment, the soil-forming parent material and weathering caused by climate change [1, 54, 65], while anthropogenic factors include agricultural activities, tourism, transportation and mineral development [19, 44]. Lower soil pH also increases the mobility of soil metal cations [2], and high concentrations of soil organic matter may also affect the distribution of elements [35]. Numerous studies have shown that elements that are more significantly affected by the natural environment include As, Cd, Co, Cu, Ni, Zn, etc., collectively referred to as “natural elements” [5, 20, 30, 46, 49, 50, 56]. Human activities can contribute to the enrichment of elements such as Cr, Hg, Mn, Pb, etc., which are naturally found in low concentrations in soils, except in the vicinity of mineral deposits, and are collectively referred to as “anthropogenic element” [4, 11, 16, 18, 21, 26, 31, 32, 36, 55]. Luo et al. [45] studied four typical profiles in the Tibetan Plateau region and found that human activities mainly affect the distribution of elements in surface soils, and the degree of elemental enrichment decreases significantly with the increase of soil depth, of which Mn, Pb, Cr are the elements that are more obviously affected by human activities. Some scholars have also found that the natural factors of soil-forming parent material is the main controlling factor affecting the distribution of elements, in which elements such as As, Co, Ni, Cu, Zn, etc. are more obviously affected by the soil-forming parent material [40, 41, 52]. Some scholars have studied the spatial distribution characteristics and pollution status of soil heavy metals in Gansu Province. They found that Ni and Zn are mainly derived from natural effects such as soil-forming matrices, while Hg is more affected by human activities [37, 43, 62].

Zhangye City is located in the middle reaches of the Black River Basin in the Hexi Corridor of the Qilian Mountains Protected Area. With the rapid development of economy and urbanization in the region, the enrichment of soil trace elements has become more and more obvious in some areas. However, the people have not studied enough the spatial distribution pattern of soil trace elements and the influencing factors in the south-central part of Ganzhou District, Zhangye City. In this work, the authors completed a soil geochemical analysis of the south-central part of Ganzhou District, Zhangye City. The aim is to investigate the effects of anthropogenic and natural factors on the distribution of 10 soil trace elements. This study contributed to further understanding of the influence of anthropogenic and natural factors on soil geochemical processes in the Qilian Mountains Protected Area.

OBJECTS AND METHODS

Study area. The study area is located in the south-central part of Ganzhou District, Zhang ye City, Gansu Province, with an average elevation of about 1421–1538 m above sea level, situated above two national nature reserves, the Qilian Mountains and the Hei he Wetland. Ganzhou District, Zhang ye City, belongs to two climate types: cold temperate arid and Qilian Mountain alpine semi-arid and semi-humid. The weather in the working area is mainly controlled by the westerly belt circulation in the middle and high latitudes and the influence of the polar cold air masses, with a dry climate, a long and colder winter, a shorter and warmer summer, and a low and concentrated precipitation, with many gales and sandy winds. The average annual temperature of the region is 7.3°C, the average annual precipitation is 130.4 mm, the average annual evaporation is 2002.5 mm, the average annual relative humidity is 52%, the average annual water pressure is 6.3 hPa, the average annual number of days of sandstorm is 3.9 days, the average annual wind speed is 2.0 m/s, and the dominant wind direction is south-southeast.

Zhang ye is located in the center of the Hexi Corridor, it is bordered by the Qilian Mountains to the south and the Badanjilin Desert to the north. It is an important node city on the Silk Road Economic Belt and an important comprehensive transportation hub city in northwest China. It provides valuable locations for human activities, agriculture and tourism to flourish. And the south-central part of Ganzhou District in Zhang ye City is next to the Qilian Mountains, which is an important ecological security barrier and highly vulnerable to human activities.

Long qu profile (38.82° N, 100.22° E) belongs to Long qu Township, Ganzhou District, Zhang ye City, adjacent to the Qilian Mountains at the headwaters of the middle reaches of the Hei he River; The Xin dun profile (38.96° N, 100.46° E) belongs to Xin dun Township, Ganzhou District, Zhang ye City, and is located near the Zhang ye National Wetland Park, surrounded by frequent tourist activities; Jingan profile (39.13° N, 100.55° E) belongs to Jingan Township, Ganzhou District, Zhang ye City, and is located on the side of the Gan ping Highway in the Long shou Mountain Canyon section; Hua zhai profile (38.73° N, 100.38° E) belongs to Hua zhai Township, Ganzhou District, Zhang ye City, located in the northern foothills of the Qilian Mountains. There is more agricultural activity here.

Samle Collection and Analysis. In this work, we selected 35 soil profile sampling sites in the south-central part of Ganzhou District, Zhang ye City. The soil samples were all from the Quaternary formation. We set the overall depth of sampling to 1 m and divided it into three layers: surface layer, middle layer and deep layer, representing the humus layer (0–0.2 m), the illuvial layer (0.4–0.5 m) and the bedrock layer (0.8–1.0 m), respectively. Soil description and sampling was carried out following guidelines for soil description (IUSS Working Group WRB, 2022). The locations of the sampling points are shown in Fig. 1a. Soil samples were collected at 0–0.2 m (surface layer), 0.4–0.5 m (middle layer) and 0.8–1.0 m (deep layer) at each sampling point and sealed in polyethylene bags. There were 105 samples in total. These include four typical profiles selected from four townships in the south-central part of Ganzhou District, located in Longqu Township, Xindun Township, Jing’an Township and Huazhai Township. We named Profile 1, Profile 2, Profile 3 and Profile 4, respectively. This is indicated in the pictures and tables by P1, P2, P3, and P4.

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Fig. 1.

(a) Location of the study area and distribution of sampling points; (b) Altitude of the study area.

The experimental tests were carried out at the Analysis and Testing Center of Langfang Comprehensive Natural Resources Investigation Center, China Geological Survey. All samples were dried at room temperature prior to testing and soil elemental content was determined after removing plant roots and gravel and grinding and passing through a 100-mesh sieve. Soil samples were dissolved with a mixture of concentrated nitric acid and hydrofluoric acid (1 : 1) until the solution became clear. The residue was transferred to a 25 mL test tube and diluted with deionized water. Inductively coupled plasma emission spectrometry (ICP-OES) was used for the determination of Cr, Mn, Zn, Cu, inductively coupled plasma mass spectrometry (ICP-MS) for the determination of Cd, Co, Ni, Pb, atomic fluorescence spectrometry (AFS) for the determination of the elements As, Hg, X-ray fluorescence spectrometry (XRF) for the determination of Al₂O₃, CaO, Na₂O, K₂O, Ba, Sr, Rb. Soil pH was measured using deionized water (1 : 1 soil : water). Total organic carbon (TOC) in the soil samples was analyzed using the dichromate oxidation method. The test results were calibrated by the Chinese national standard soil reference samples (GBW07401, GBW07402 and GBW07403), and the relative standard deviations of the repeated analyses for all elements were ≤5%.

In terms of data processing, we used Excel and IBM® SPSS®Statistics.2021 software for normal distribution test to ensure that all sample data conform to the law of normal distribution; we used Origin 2024 to draw the Pearson correlation evaluation map of the required elements and the analysis map of chemical weathering indexes; we used ArcGIS10.7 to draw the spatial distribution map of the required elements; and we used ArcGIS10.7 to draw the spatial distribution map of the required elements. We used ArcGIS 10.7 to draw the spatial distribution maps of the required elements.

Chemical weathering proxies. We estimated the chemical weathering intensity of the selected profiles by calculating the chemical alteration index (CIA), ln(Al₂O₃/Na₂O), Rb/Sr, and Ba/Sr. The CIA was calculated as follows:

1

Each oxide in Eq. (1) is presented as a molar content, and CaO* represents CaO in silicate minerals, excluding CaO content in carbonates and phosphates. We used the method of McLennan [57] to indirectly quantify CaO in silicate fractions by subtracting the Ca corresponding to the molar fraction of P₂O₅ (in apatite) from the molar fraction of total CaO. After subtraction, CaO* = Na₂O if CaO > Na₂O and CaO* = CaO if CaO < Na₂O. Higher CIA values indicate greater weathering intensity [8, 17, 34, 39, 61]. ln(Al₂O₃/Na₂O) has also been considered as a useful indicator of the intensity of chemical weathering [3, 6, 27, 28, 64]. Ba, Rb, and Sr exhibit different geochemical behaviors during chemical weathering of the Earth’s surface Ba, Rb, and Sr exhibit different geochemical behaviors during chemical weathering of the Earth’s surface [33, 47, 48, 59]. As the intensity of weathering increases, Sr readily precipitates out of the sediments, whereas the opposite is true for Rb and Ba. This difference can effectively separate Sr from Rb. Therefore, the Rb/Sr and Ba/Sr ratios can be used to indicate the weathering intensity.

RESULTS AND DISCUSSION

Characteristics of soil metal content. The test results of 10 metal elements and pH of soil samples are shown in Table 1. Combined with the background values of soil elements in China, it was found that the average contents of elements As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb and Zn in the A-layer soils were 1.02, 1.35, 1.09, 2.10, 1.18, 2.16, and 1.06 times higher than the background values of the surface layer soils in Gansu Province, respectively, 0.86, 1.13, 1.04 times, and the average content of As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Zn elements in the deep layer soil was 1.01, 1.23, 1.14, 2.25, 1.26, 3.17, 1.15, 0.87, 1.01, 1.04 times of the background value of the C-layer soil in Gansu Province, respectively. Although the content of all heavy metal elements did not exceed the national screening values for soil pollution risks on agricultural and construction land, the content of Cr and Hg elements in the soil of the A and C layers exceeded the background values by more than two times, and there may be a certain risk of pollution in the future [14]. The coefficients of variation (CVs) of the elements in soil layer A were Hg > Cr > Mn > Pb > Zn > Ni > Co > Cd > As > Cu, and those of soil layer C were Hg > Cr > Mn > Pb > Zn > Cu > Co > Cd > Ni > As. The coefficients of variation (CVs) of the elements of Hg, Cr, Pb, and Mn were above 30, which was larger than those of the other elements. This indicates that the spatial variability may be greater and the possibility of anthropogenic influence is also greater, which will be verified by further analysis later [25]. The mean pH values of surface and deep layer soils in the south-central part of Ganzhou district were ≥8.5. According to the soil acidity and alkalinity (pH) grading standard, the soils in the south-central part of Ganzhou district were strongly alkaline, which also affected the content and spatial distribution characteristics of soil metal elements to a certain extent.

Table 1. . Test results of soil elemental content in the south-central part of Ganzhou district

Layer-a (0~0.2 m)						Layer-C (0.8~1.0 m)
element	minimum	maximum	arithmetic mean	coefficient of variation	background value of A horizon soil in Gansu Province	minimum	maximum	arithmetic mean	coefficient of variation	background value of C horizon soil in Gansu Province
As	5.96	19.5	11.97	23.85	11.7	7.9	15.5	12.03	17.98	11.9
Cd	0.085	0.21	0.15	24.78	0.111	0.083	0.22	0.14	26.75	0.114
Co	5.75	20.5	13.54	25.34	12.4	4.99	24.8	14.21	27.66	12.5
Cr	47	235	145.21	45.78	69.3	64	224	141.76	39.30	63.1
Cu	14.1	35.7	27.65	21.46	23.4	12.4	52.7	28.45	28.28	22.5
Hg	0.006	0.074	0.035	65.07	0.016	0.006	0.05	0.02	58.33	0.0063
Mn	456	950	673.04	39.54	644	453	1035	692.50	30.85	600
Ni	13.3	43.7	29.69	29.18	34.4	11.2	43.8	30.73	26.24	35.4
Pb	11	36.5	20.19	36.19	17.9	11.9	24.9	19.58	30.41	19.3
Zn	33.5	110	69.83	29.94	67.0	27.7	126	69.47	28.54	66.9
pHa	7.7	9.7	8.5	5.83	8.5	7.69	9.85	8.59	7.21	8.5

a—pH dimensionless, other elements in mg/kg.

Characterization of the spatial distribution of soil metal elements. The spatial distribution of different elements in different soil layer heights was mapped by Kriging interpolation analysis of 10 trace elements using ArcGIS 10.7, as shown in Fig. 2. The distribution of metallic elements in the study area is characterized by patchy features, and the spatial variability of different elements is also significantly different. Combined with the location of the sampling points in Fig. 1, there are obvious aggregations in the northern part of Jing’an Township, Xindun Township, Huazhai Township and Longqu Township areas. The elements As, Co, Cu, Mn, Pb and Zn in the A-layer soil were aggregated near the Gan ping Highway in the northern part of Jing’an Township. The enrichment of Pb elements in the deep layer soil decreased significantly with increasing depth, while the changes of other elements were not obvious. As, Cd, Co, Cu, Hg, Mn, Ni, and Pb elements in the A-layer soil in the western part of Longqu Township have obvious aggregation. And the aggregation phenomenon was not weakened in the C-layer soil. Mn, Cr, Hg elements in the surface layer soil in the center area of Xindun Township showed aggregation phenomenon, and with the increase of depth, the aggregation phenomenon of Mn, Cr, Hg elements in the deep layer soil was obviously weakened, while the enrichment degree of As, Ni, Zn elements were obviously increased. As, Co, Cu, Hg, Mn, and Pb elements in the soil of Huazhai Township showed obvious aggregation in the soil species of the deep layer with the increase of the depth, and the enrichment of Cr elements from the surface layer to the deep layer was weakened. It has been shown that soil trace element concentrations generally influenced by natural factors such as soil-forming parent material or alluvial flooding increase with soil depth or the trend of change is not significant [10], whereas elements influenced by anthropogenic factors have a greater change in concentration in the vertical direction and generally decrease with depth [9]. Our results show that the northern part of Jing’an Township is in the Long shou Mountain canyon section, which is dominated by Haplic Cambisols (IUSS Working Group WRB, 2022) [23]. The degree of elemental enrichment of As, Co, Cu, Mn, and Zn did not decrease with the increase of the depth of the soil, and it is assumed to be caused by the alluvial and flooding effect of the soil-forming parent rock of the nearby mountains. The enrichment phenomenon of Pb element disappeared with the increase of soil depth. Since the northern part of Jing’an Township is in the section of Ganping Highway, which is seriously affected by human factors, the trialky lead in the exhaust of automobiles is not easy to be dissolved in the soil [12, 63], so it is deduced that the enrichment of Pb element is mainly caused by human factors. Xindun Township is located near Zhangye National Wetland Park, which is affected by tourism activities and frequent human activities [66]. The enrichment of Cr, Hg, and Mn elements in the C-layer soil decreased significantly with the increase of depth, which may be due to the surface enrichment caused by the influence of anthropogenic factors. The soil types here are mainly Histic Gleysols [23]. Cr(III) in the soil is usually formed in the form of hydroxides and oxides [13], which are easily adsorbed on clay particles, leading to impeded migration, and the high humidity of the soil is highly likely to cause surface enrichment of the elements [7]. As the depth increases, the anthropogenic influence gradually decreases, so the phenomenon of elemental enrichment gradually diminishes. Longqu Township is close to the Qilian Mountains and is less affected by human activities, mainly distributing Haplic Cambisols [23]. The enrichment of As, Cd, Co, Cu, Hg, Mn, Ni, and Pb has not weakened with the increase of depth, so these elements are more affected by the soil-forming parent rock. Huazhai Township is located in villages immediately adjacent to the Qilian Mountains and is dominated by Haplic Cambisols. The enrichment of Cr elements decreases with increasing soil depth and may be influenced mainly by agricultural activities. It may be consumed during crop production and sowing [53]. Taken together, the enrichment of As, Co, Cu, Hg, Mn, and Pb elements did not change significantly with increasing soil depth, which may be mainly influenced by the soil-forming parent rocks. Mn, Cr and Hg are considered as “anthropogenic elements”, and their distribution patterns are closely related to human activities. Combined with the spatial distribution characteristics of the elements, the enrichment phenomenon of Mn, Cr and Hg gradually decrease or even disappears with the increase of soil depth, which is in line with the distribution pattern of “anthropogenic elements”. Therefore, we believe that the distribution of Mn, Cr and Hg is mainly affected by human activities.

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Fig. 2.

Characteristics of spatial distribution of soil micronutrient content in the south-central part of Ganzhou District.

Correlation analysis of soil metal elements. Pearson correlation analysis was done by taking the arithmetic mean of the elemental contents at different depths of each sampling point. The results showed that Cr showed negative or poor correlation with all other elements. Mn and correlations with the elements Zn, As, Cr, and Hg were poor. The elements As, Pb, Zn, Co, and Cu showed significant positive correlation with each other. The elements Ni, Co, and Cu were significantly positively correlated with each other. Hg is positively correlated with Ni but weakly correlated with other elements. pb is weakly correlated with Hg and Ni. It has been shown that the correlation between “anthropogenic” and “natural” elements is poor [29]. Combined with the spatial distribution characteristics of soil trace elements in Fig. 2, the elements As, Pb, Zn, Co, Cu, Ni have a strong correlation, and the reason for their enrichment may be mainly caused by the alluvial flooding of soil-forming parent rocks, while the elements Cr, Mn, Hg may be mainly caused by human activities.

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Fig. 3.

Pearson correlation analysis of soil trace elements in the south-central part of Ganzhou district.

Chemical weathering intensity. Soil texture, pH and TOC are important factors influencing the distribution of soil elements. In order to further explore the factors influencing the spatial distribution of soil elements, we selected four typical profiles in the areas with obvious elemental enrichment for analysis. As can be seen in Table 2, there were significant differences in soil texture types among the sampling sites. P1 is Sandy Cambisols. P2 has Sandy Gleysols in the surface layer and Clayey Gleysols in the middle and deep layer. Sandy soils are more porous and permeable, which facilitates the rapid migration of water and solutes. It may result in a higher rate of migration of some soluble elements in sandy soils, thus affecting their distribution in the soil profile. In contrast, clayey soils are less porous and less permeable, acting as a barrier to elemental transport. This makes it easier for some elements to accumulate in clayey soils. Different textured soils have different capacities to adsorb elements. In general, soils with higher clay mineral content have a larger specific surface area and more active adsorption sites, which provide a stronger adsorption capacity for metal elements and other elements. The middle layer of P2 is Clayey Gleysols, and some easily adsorbed trace elements (e.g., Mn, Zn) may be enriched in this layer, while the content of these elements in Sandy Gleysols is relatively low, which affects the spatial distribution of soil elements to some extent. The pH of the three profiles P1, P2 and P4 did not change much with depth, and the pH of P3 changed from alkaline to strongly alkaline with depth, which may have some effect on the elemental distribution. Soil pH reflects the acid-base balance of the soil and affects the concentration of micronutrients in the soil. It has been shown that pH significantly affects the distribution pattern of elements at pH < 6.5 [22], while all our test results show that pH is greater than 6.5, so the effect of pH on the distribution of elements may not be significant. As soil depth increases, the TOC of the soil at P1 decreased from 14.9 to 12.5 g kg^–1. The TOC of the soil at P2 increased from 33.7 to 34.6 g kg^–1. The TOC of the soil at P3 increased from 6.8 to 19.5 g kg^–1. The TOC of the soil at P4 increased from 19.0 to 10.0 g kg^–1. Soil organic matter plays a vital role in the transformation of soil elemental transport, and a high capacity of soil organic matter carries metal elements and affects their activity [38]. Meanwhile, by calculating the correlation of elements in the four profiles, it was found (Fig. 4) that there was no obvious correlation between soil trace elements and TOC and pH, which suggests that TOC and pH may not be the main factors affecting the distribution of soil elements.

Table 2. . Soil pH and TOC of different profiles in the south-central part of Ganzhou district 613 Classification of soil properties according to WRB 2022 for four soil profiles: Soil textural group: SL—Sandy 614 loam, L—loam, SC—sandy clay, CL—Clay loam

Sample site	Depth, m	Textural group	Diagnostic			pH	TOC, g kg–1	Notes
			horizons	properties	materials
P1	0–0.2	SL	Cambic	–	Solimovic	8.56	14.9	Close to the Qilian Mountains, located in the headwaters of the middle reaches of the Heihe River
	0.4–0.5	SL	Cambic	–	–	8.56	13.8
	0.8–1.0	SL	Cambic	Gleyic	–	8.57	12.5
P2	0–0.2	SC	Histic	Gleyic	–	7.70	33.7	Located near Zhangye National Wetland Park
	0.4–0.5	CL	Histic	Gleyic	–	7.69	34.2
	0.8–1.0	CL	Histic	Gleyic	Limnic	7.69	34.6
	0–0.2	SL	Cambic	–	–	8.41	16.8
P3	0.4–0.5	SL	Cambic	Salic	–	8.93	17.6	Longshoushan Gorge on Ganping Highway
	0.8–1.0	L	Cambic	–	Calcaric	9.85	19.5
	0–0.2	SL	Cambic	–	Solimovic	8.60	19.0
	0.4–0.5	L	Cambic	Salic	–	8.61	16.2	Located in a village adjacent to the Qilian Mountains
P4	0.8–1.0	L	Cambic	Salic	Calcaric	8.74	10.0

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Fig. 4.

Pearson correlation analysis of different profile elements in south-central Ganzhou district.

Pearson analysis revealed that the strength of elemental correlation coefficients varied among the four soil profiles. The order of the number of elements with significant correlation is: P1 > P3 > P4 > P2. There is no obvious positive or even negative correlation between Hg and other elements in the P2 and P4. There is a significant correlation between Cr and Mn in the P2, but there is no significant positive correlation between Cr and Mn and any other element. There was no significant positive correlation between Pb and other elements in the P3. There was also no significant positive correlation between Cr and other elements in the P4. According to the results of our field survey and the distribution pattern of anthropogenic elements, the Zhangye National Wetland Park near the P2 is characterized by frequent tourism activities and high anthropogenic impacts. Combined with the spatial distribution characteristics of the elements, the enrichment degree of Cr and Mn elements decreased significantly with the increase of soil depth, so it is inferred that the enrichment of Cr and Mn elements in the surface layer is mainly affected by anthropogenic factors. There are more agricultural activities in the vicinity of the P4, and the villagers are mainly engaged in maize and vegetable cultivation. Combined with the results of the previous study, the surface enrichment of Cr elements may be mainly influenced by human activities. The P3 is on the side of the highway and is affected by vehicle exhaust, which also causes enrichment of Pb in the surface soil, which disappears with increasing soil depth.

Chemical weathering intensity. Weathering soil-forming processes can significantly affect the distribution of soil elements, which may exhibit enrichment due to complex biochemical interactions. For this we performed a calculation, as shown in Fig. 5. The range of CIA values for all profiles is in the 60–71 range, with a mean value of 68, which is slightly higher than the Upper Crustal Abundance (UCC) value, suggesting that it is currently in a stage of weak to moderate chemical weathering. The highest CIA values were found in the P2 and P4, while the CIA values in the P1 and P3 did not vary significantly with depth. The range of ln (Al₂O₃/Na₂O) values for all profiles is between 2 and 10, with a greater variation in ln (Al₂O₃/Na₂O) values with depth for the P4. The maximum value of ln (Al₂O₃/Na₂O) is found in the P2. There are no significant changes in the P1 and P3. Rb/Sr ratios range from 0.1 to 0.5. Ba/Sr ratios range from 1.5 to 4.0. The Rb/Sr and Ba/Sr ratios of the P2 and P4 are higher than those of the other two profiles. Looking at the different chemical weathering indicators of the four profiles together, the P2 and P4 have higher weathering intensity. A variety of factors influence the intensity of chemical weathering of soils, including climate, parent rock, and human activity [24, 42, 60]. Four soil profiles are located on stable terraces that Mineralogical and geochemical characteristics are relatively uniform, physical and chemical properties such as pH and soil color are similar. Among them, the fluctuation of each chemical weathering index in the P1 and P3 is small, and the change trend is not obvious. This suggests that weathering of the P1 and P3 may be primarily influenced by climate change. In contrast, the CIA values of the P2 and P4 show significant fluctuations and small peaks. We hypothesize that they are more significantly affected by human activities.

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Fig. 5.

Chemical weathering indexes of different profiles in the south-central part of Ganzhou.

CONCLUSIONS

In this work, we systematically analyzed the spatial distribution patterns of 10 soil trace elements and their influencing factors in the south-central part of Ganzhou District, Zhang ye City. The results of the study showed that the average values of Hg and Cr elements in the soil exceeded more than twice the background values of the soil in Gansu Province, but none of the contents exceeded the national screening values for soil pollution risks in agricultural and construction land in the Soil Environmental Quality Standards; The relative high values of each element of soil were mainly distributed in four areas, Long qu Township, Xin dun Township, Jing’an Township and Hua zhai Township in Ganzhou District. Pearson correlation analysis combined with chemical weathering indicators can infer the main factors affecting the enrichment of each element. Through the analysis of four typical profiles in four regions, it is found that the P2 and P4 are more strongly affected by human influence. The P2 was mainly influenced by tourism activities. The P4 was mainly influenced by agricultural activities. The P1 and P3 were more influenced by natural factors, mainly by the alluvial flooding of the host rock; Among them, the elements Cr, Hg, and Mn were considered anthropogenic influences, and As, Cd, Co, Cu, Ni, and Zn were considered natural influences. Elemental Pb in the P3 was mainly influenced by anthropogenic factors, while that in the remaining three profiles was influenced by natural factors. This study revealed the distribution patterns and influencing factors of 10 soil trace elements, emphasizing the interactive effects of natural and anthropogenic factors on trace element enrichment. It helps to further understand the soil geochemical processes in the Qilian Mountains and provides theoretical basis for the ecological protection and construction in the Qilian Mountains.

ACKNOWLEDGMENTS

Writing-original draft Yuze Bai; Writing–review & editing Yi Liu; Investigation and Mapping Ning Zhang; Investigation and Validation Kairan Xu; Project administration Miao Liu; Data curation Jiaxing Sun, Manman Lin and Furong Zhai.

FUNDING

The work was supported by the Open Project Program of Hebei Center for Ecological and Environmental Geology Research, project no. JSYF-202406 and by the Geological Survey Project of Ecological Protection and Restoration in the Middle Reach of the Black River Region, project no. DD20242705.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

We did not use Artificial Intelligence tools in writing this article.

CONFLICT OF INTEREST

The authors of this work declare that they have no conflicts of interest.

Publisher’s Note.

Pleiades Publishing remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

AI tools may have been used in the translation or editing of this article.

REFERENCES

1 Adamu, M.; Haile, M.; Teka, K. Variation in soil physico-chemical properties driven by land use change in acidic soils of Southern Ethiopia. Eurasian Soil Sci.; 2025; 58, 33. [DOI: https://dx.doi.org/10.1134/s1064229324602452] 1:CAS:528:DC%2BB2MXmvFSitb8%3D

2 Nyman, A.; Boman, A.; Johnson, A.; Dopson, M.; Åström, M. E. Easily mobilized metals and acidity in acid sulfate soils across the Swedish coastal plains. Eur. J. Soil Sci.; 2024; 75, e70013. [DOI: https://dx.doi.org/10.1111/ejss.70013] 1:CAS:528:DC%2BB2cXislOitLzM

3 Algeo, T. J.; Hong, H.; Wang, Ch. The chemical index of alteration (CIA) and interpretation of ACNK diagrams. Chem. Geol.; 2025; 671, 122474. [DOI: https://dx.doi.org/10.1016/j.chemgeo.2024.122474] 1:CAS:528:DC%2BB2cXisFWns7rK

4 Asare, P.; Sarpong, K.; Gyamfi, O.; Ankapong, E.; Agyei, V.; Amissah-Reynolds, P. K.; Dartey, E. Contamination and health risk assessment of potentially toxic elements in rice (Oryza sativa) and soil from Ashanti Region. Environ. Monit. Assess.; 2024; 196, 16. [DOI: https://dx.doi.org/10.1007/s10661-024-13340-4] 1:CAS:528:DC%2BB2cXitlygs7vI

5 Aung, P. P.; Mao, Ya.; Hu, T.; Qi, Sh.; Tian, Q.; Chen, Zh.; Xing, X. Metal concentrations and pollution assessment in bottom sediments from Inle Lake, Myanmar. J. Geochem. Explor.; 2019; 207, 106357. [DOI: https://dx.doi.org/10.1016/j.gexplo.2019.106357] 1:CAS:528:DC%2BC1MXhslKht7nM

6 Babeesh, C.; Achyuthan, H.; Sajeesh, T. P. Geochemical signatures of Karlad Lake sediments, North Kerala: Source area weathering and provenance. J. Geol. Soc. India; 2018; 92, pp. 177-186. [DOI: https://dx.doi.org/10.1007/s12594-018-0979-6] 1:CAS:528:DC%2BC1cXhsFChsb%2FO

7 Bagdasarov, I. E.; Konyushkova, M. V.; Kryukova, Yu. A.; Ladonin, D. V.; Tseits, M. A.; Krasilnikov, P. V. Trace elements in marsh soils of the pomor coast of the White Sea. Eurasian Soil Sci.; 2024; 57, pp. 1321-1328. [DOI: https://dx.doi.org/10.1134/s1064229324600817] 1:CAS:528:DC%2BB2cXhs1egtrrM

8 Bao, J.; Song, Ch.; Yang, Yi.; Fang, X.; Meng, Q.; Feng, Yi.; He, P. Reduced chemical weathering intensity in the Qaidam Basin (NE Tibetan Plateau) during the Late Cenozoic. J. Asian Earth Sci.; 2019; 170, pp. 155-165. [DOI: https://dx.doi.org/10.1016/j.jseaes.2018.10.018]

9 Bao, J.; Chang, Ya.; Cheng, N.; Li, Yi.; Chang, X.; Feng, J.; Nan, X.; Ren, H. Vertical distribution and migration of heavy metals in soil of green stormwater infrastructure receiving roof runoff. Sci. Total Environ.; 2024; 954, 176511. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2024.176511] 1:CAS:528:DC%2BB2cXitFWgt7zM

10 Bernhard, N.; Moskwa, L.M.; Schmidt, K.; Oeser, R. A.; Aburto, F.; Bader, M. Y.; Baumann, K.; von Blanckenburg, F.; Boy, J.; van den Brink, L.; Brucker, E.; Büdel, B.; Canessa, R.; Dippold, M. A.; Ehlers, T. A.; Fuentes, J. P.; Godoy, R.; Jung, P.; Karsten, U.; Köster, M.; Kuzyakov, Ya.; Leinweber, P.; Neidhardt, H.; Matus, F.; Mueller, C. W.; Oelmann, Yv.; Oses, R.; Osses, P.; Paulino, L.; Samolov, E.; Schaller, M.; Schmid, M.; Spielvogel, S.; Spohn, M.; Stock, S.; Stroncik, N.; Tielbörger, K.; Übernickel, K.; Scholten, T.; Seguel, O.; Wagner, D.; Kühn, P. Pedogenic and microbial interrelations to regional climate and local topography: New insights from a climate gradient (arid to humid) along the Coastal Cordillera of Chile. Catena; 2018; 170, pp. 335-355. [DOI: https://dx.doi.org/10.1016/j.catena.2018.06.018] 1:CAS:528:DC%2BC1cXht1GmtrvF

11 Bhat, M. A.; Fan, D.; Nisa, F. U.; Dar, T.; Kumar, A.; Sun, Q.; Li, S.-L.; Mir, R. R. Trace elements in the Upper Indus River Basin (UIRB) of Western Himalayas: Quantification, sources modeling, and impacts. J. Hazard. Mater.; 2024; 476, 135073. [DOI: https://dx.doi.org/10.1016/j.jhazmat.2024.135073] 1:CAS:528:DC%2BB2cXhsVyhtL7N

12 Burachevskaya, M. V.; Minkina, T. M.; Mandzhieva, S. S.; Bauer, T. V.; Kirichkov, M. V.; Nevidomskaya, D. G.; Zamulina, I. V. Effect of Soil Buffer Capacity on the Transformation of Lead and Cadmium Compounds. Eurasian Soil Sci.; 2024; 57, pp. 1110-1121. [DOI: https://dx.doi.org/10.1134/s1064229324600441] 1:CAS:528:DC%2BB2cXhsFCls7%2FI

13 Burton, E. D.; Choppala, G.; Vithana, Ch. L.; Karimian, N.; Hockmann, K.; Johnston, S. G. Chromium (VI) formation via heating of Cr(III)-Fe(III)-(oxy)hydroxides: A pathway for fire-induced soil pollution. Chemosphere; 2019; 222, pp. 440-444. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2019.01.172] 1:CAS:528:DC%2BC1MXitlOksL8%3D

14 Cai, N.; Wang, X.; Wang, W.; Wang, L.; Tian, Sh.; Zhu, H.; Zhang, X. Accumulation, ecological health risks, and source identification of potentially toxic elements in river sediments of the Qinghai-Tibet Plateau, China. Process Saf. Environ. Prot.; 2024; 182, pp. 703-718. [DOI: https://dx.doi.org/10.1016/j.psep.2023.12.026] 1:CAS:528:DC%2BB3sXis1aru7vI

15 Cao, W.; Sheng, Yu.; Wu, J.; Peng, E.; Gao, R.; Zhou, M. Spatial variability and source analysis of typical soil trace elements at permafrost section along national highway 214 in the eastern Qinghai–Tibet Plateau. Environ. Geochem. Health; 2023; 45, pp. 1819-1840. [DOI: https://dx.doi.org/10.1007/s10653-022-01299-5] 1:CAS:528:DC%2BB38XhsFGqtr7E

16 Duman, M.; Eronat, A. H.; Talas, E. Interplay of natural and anthropogenic factors in sediment dynamics and trace element distribution in Güllük Gulf, western Türkiye: A comprehensive geochemical and hydrodynamic analysis. Cont. Shelf Res.; 2024; 282, 105332. [DOI: https://dx.doi.org/10.1016/j.csr.2024.105332]

17 Dzombak, R. M.; Sheldon, N. D. Terrestrial records of weathering indicate three billion years of dynamic equilibrium. Gondwana Res.; 2022; 109, pp. 376-393. [DOI: https://dx.doi.org/10.1016/j.gr.2022.05.009] 1:CAS:528:DC%2BB38Xhslymt7%2FJ

18 Espinoza-Guillen, J. A.; Alderete-Malpartida, M. B.; Escobar-Mendoza, J. E.; Navarro-Abarca, U. F.; Silva-Castro, K. A.; Martinez-Mercado, P. L. Identifying contamination of heavy metals in soils of Peruvian Amazon plain: Use of multivariate statistical techniques. Environ. Monit. Assess.; 2022; 194, 27. [DOI: https://dx.doi.org/10.1007/s10661-022-10494-x] 1:CAS:528:DC%2BB38XisVOitL3M

19 Feng, Z. W.; Chen, W. D.; Meng, Y. C.; Lu, H. X.; Shi, X. Y.; Zhang, J. J. Spatial variability and source analysis of soil heavy metals: A case study of the key planting area of special agricultural products in Cangxi County, China. PLoS One; 2024; 19, 24. [DOI: https://dx.doi.org/10.1371/journal.pone.0303387] 1:CAS:528:DC%2BB2cXht1Kju77J

20 Fernández-Ayuso, A.; Kohfahl, C.; Aguilera, H.; Rodríguez-Rodríguez, M.; Ruiz-Bermudo, F.; Serrano-Hidalgo, C.; Romero-Álvarez, C. Control of trace metal distribution and variability in an interdunal wetland. Sci. Total Environ.; 2023; 857, 159409. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2022.159409] 1:CAS:528:DC%2BB38XislWhsrbI

21 Florez-Vargas, O.; Vilanova, E.; Alcaide, C.; Henao, J. A.; Villarreal-Jaimes, C. A.; Medina-Pérez, O. M.; Rodriguez-Villamizar, L. A.; Idrovo, A. J.; Sánchez-Rodríguez, L. H. Geological context and human exposures to element mixtures in mining and agricultural settings in Colombia. Sci. Total Environ.; 2023; 898, 165632. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2023.165632] 1:CAS:528:DC%2BB3sXhsFGjsrjE

22 Fraser, T. D.; Duddigan, S.; Diaz, A.; Green, I.; Tibbett, M. Optimizing pH for soil enzyme assays reveals important biochemical functions in low pH soil. J. Soil Sci. Plant Nutr.; 2024; 24, pp. 6236-6247. [DOI: https://dx.doi.org/10.1007/s42729-024-01866-y] 1:CAS:528:DC%2BB2cXhvFSltbrI

23 Gerasimova, M. I.; Smirnova, M. A. Qualifiers in the international soil classification system WRB-2022: Composition, connotation, functions. Eurasian Soil Sci.; 2025; 58, 6. [DOI: https://dx.doi.org/10.1134/s1064229324601902] 1:CAS:528:DC%2BB2MXks1GitLo%3D

24 Ghasera, Kh. M.; Rashid, Sh. A. Geochemical characteristics of two contrasting weathering profiles developed at high altitude, NE Lesser Himalaya, India: Implications for controlling factors and mobility of elements. J. Earth Syst. Sci.; 2022; 131, 25. [DOI: https://dx.doi.org/10.1007/s12040-021-01742-8] 1:CAS:528:DC%2BB38XjvFOis7Y%3D

25 Gökmen, V.; Sürücü, A.; Budak, M.; Bilgili, A. V. “Modeling and mapping the spatial variability of soil micronutrients in the Tigris basin,” J. King Saud Univ. –. Sci.; 2023; 35, 102724. [DOI: https://dx.doi.org/10.1016/j.jksus.2023.102724]

26 Guo, Q. E.; Cao, S. Y.; Nan, L. L.; Dong, B.; Zhan, Z. B.; Wang, Z. Ecological risk assessment of Cu, Ni, Cd, Hg, Zn, Pb and As in typical farmland gray-brown desert soil in China. Eurasian Soil Sci.; 2024; 57, pp. 1759-1766. [DOI: https://dx.doi.org/10.1134/s1064229324601306] 1:CAS:528:DC%2BB2cXhs1Kqtb7E

27 Hadji, F.; Marok, A.; Samet, A. M.; Reolid, M.; Bensefia, K. E. Inorganic geochemistry of Miocene sediments from the Lower Chelif Basin (NW Algeria) for approaching weathering and palaeoclimatic conditions. J. Iberian Geol.; 2024; 50, pp. 137-156. [DOI: https://dx.doi.org/10.1007/s41513-024-00236-y]

28 Hatano, N.; Yoshida, K.; Sasao, E. Effects of grain size on the chemical weathering index: A case study of Neogene fluvial sediments in southwest Japan. Sedimentary Geology; 2019; 386, pp. 1-8. [DOI: https://dx.doi.org/10.1016/j.sedgeo.2019.03.017] 1:CAS:528:DC%2BC1MXmvFehsrk%3D

29 Hidouri, N.; Moussaoui, Z.; Sleimi, N.; Hamed, Y.; Hamzaoui-Azzaza, F. Soil contamination by trace elements and radioelements and related environmental risks in agricultural soils of the M’Dhilla Basin (southwestern Tunisia). Environ. Monit. Assess.; 2024; 196, 17. [DOI: https://dx.doi.org/10.1007/s10661-024-13202-z] 1:CAS:528:DC%2BB2cXitFGmurrJ

30 Huang, K.; Ma, L.; Abuduwaili, J.; Liu, W.; Issanova, G.; Saparov, G.; Lin, L. Human-induced enrichment of potentially toxic elements in a sediment core of lake Balkhash, the largest lake in Central Asia. Sustainability; 2020; 12, 4717. [DOI: https://dx.doi.org/10.3390/su12114717]

31 Ilić, P.; Ilić, S.; Mushtaq, Z.; Rashid, A.; Bjelić, L. S.; Markić, D. N.; Kurilić, S. M.; Farooqi, Z. U. R.; Baloch, M. Y. J.; Mehmood, T.; Ullah, Z.; Riaz, S. Assessing the ecological risks and spatial distribution of heavy metal contamination at solid waste dumpsites. Eurasian Soil Sci.; 2024; 57, pp. 1277-1296. [DOI: https://dx.doi.org/10.1134/s1064229324700303] 1:CAS:528:DC%2BB2cXht1Wgtb3I

32 Islam, M. S.; Al Bakky, A.; Ahmed, S.; Islam, M. T.; Antu, U. B.; Saikat, M. S. M.; Akter, R.; Roy, T. K.; Jolly, Ye. N.; Islam, K. A.; Sarkar, A.; Ismail, Z.; Idris, A. M. Toxicity assessment of heavy metals translocation in maize grown in the Ganges delta floodplain soils around the Payra power plant in Bangladesh. Food Chem. Toxicol.; 2024; 193, 115005. [DOI: https://dx.doi.org/10.1016/j.fct.2024.115005] 1:CAS:528:DC%2BB2cXitVersbrI

33 Jin, Zh.; Wang, S.; Shen, J.; Zhang, E.; Li, F.; Ji, J.; Lu, X. Chemical weathering since the Little Ice Age recorded in lake sediments: A high-resolution proxy of past climate. Earth Surf. Processes Landforms; 2001; 26, pp. 775-782. [DOI: https://dx.doi.org/10.1002/esp.224] 1:CAS:528:DC%2BD3MXmtF2itb0%3D

34 Kanzari, A.; Gérard, M.; Boekhout, F.; Galoisy, L.; Calas, G.; Descostes, M. Impact of incipient weathering on uranium migration in granitic waste rock piles from former U mines (Limousin, France). J. Geochem. Explor.; 2017; 183, pp. 114-126. [DOI: https://dx.doi.org/10.1016/j.gexplo.2017.08.010] 1:CAS:528:DC%2BC2sXhs12ksrbM

35 Kebonye, N. M.; Eze, P. N.; Ahado, S. K.; John, K. Structural equation modeling of the interactions between trace elements and soil organic matter in semiarid soils. Int. J. Environ. Sci. Technol.; 2020; 17, pp. 2205-2214. [DOI: https://dx.doi.org/10.1007/s13762-019-02610-1] 1:CAS:528:DC%2BB3cXivVehtQ%3D%3D

36 Krasavtseva, E. A.; Soshina, A. S.; Ivanova, T. K.; Mosendz, I. A.; Maksimova, V. V.; Korneykova, M. V.; Fokina, N. V.; Chaporgina, A. A.; Latyuk, E. S.; Elizarova, I. R.; Shirokaya, A. A.; Dolgikh, A. V.; Slukovskaya, M. V. Chemical and microbiological characteristics of soils formed during overgrowing the wastes from rare metal ores enrichment in the Subarctic. Eurasian Soil Sci.; 2025; 58, 25. [DOI: https://dx.doi.org/10.1134/s1064229324603536] 1:CAS:528:DC%2BB2MXltFWht7w%3D

37 Li, Q.; Cao, Yi.; Meng, T.; He, L.; Zhang, S. Biogeochemical behavior, health risk assessment and source identification of antimony and arsenic in soil from a legacy antimony smelter in Gansu, Northwest China. Environ. Sci. Eur.; 2023; 35, 13. [DOI: https://dx.doi.org/10.1186/s12302-023-00821-5] 1:CAS:528:DC%2BB3sXis1GmtL3P

38 Li, Q.; Wang, L.; Fu, Yu.; Lin, D.; Hou, M.; Li, X.; Hu, D.; Wang, Zh. Transformation of soil organic matter subjected to environmental disturbance and preservation of organic matter bound to soil minerals: A review. J. Soils Sediments; 2023; 23, pp. 1485-1500. [DOI: https://dx.doi.org/10.1007/s11368-022-03381-y] 1:CAS:528:DC%2BB38XjtVClsLrJ

39 Li, S.; Gaschnig, R. M.; Rudnick, R. L. Insights into chemical weathering of the upper continental crust from the geochemistry of ancient glacial diamictites. Geochim. Cosmochim. Acta; 2016; 176, pp. 96-117. [DOI: https://dx.doi.org/10.1016/j.gca.2015.12.012] 1:CAS:528:DC%2BC2MXitVyqu7zP

40 Li, T.; Li, Yo.; Liu, H.; Li, S.; Ouyang, Yu.; Li, Ch.; Zhang, K.; Li, J.; Zhang, J.; Zhang, T.; Huang, Yo.; Wu, J. Chemical weathering intensity and geochemical characteristics of Cretaceous terrigenous clastic rock-purple soil profiles in the Pushi area, Xichang. Geol. J.; 2022; 57, pp. 3587-3600. [DOI: https://dx.doi.org/10.1002/gj.4489] 1:CAS:528:DC%2BB38XhvVWku7%2FE

41 Liao, J.; Wang, T.; Gui, J.; Zhang, H.; Huang, C.; Song, X.; Zhang, Sh. Ecological risk assessment and source identification of heavy metals in soils from Shiyang river watershed in Northwest China. Toxics; 2023; 11, 825. [DOI: https://dx.doi.org/10.3390/toxics11100825] 1:CAS:528:DC%2BB3sXit12qtbnP

42 Liu, F.; Wang, S.; Wang, J.; Guo, F.; Yu, Sh.; Sun, P. The hydrochemistry characteristics and chemical weathering intensity of an anthropogenically involved catchment, South China. Water; 2024; 16, 2444. [DOI: https://dx.doi.org/10.3390/w16172444] 1:CAS:528:DC%2BB2cXivVehtbvP

43 Liu, L.; Lu, Ya.; Shan, Yu.; Mi, J.; Zhang, Z.; Ni, F.; Zhang, J.; Shao, W. Pollution characteristics of soil heavy metals around two typical copper mining and beneficiation enterprises in Northwest China. Environ. Monit. Assess.; 2022; 194, 16. [DOI: https://dx.doi.org/10.1007/s10661-022-10416-x]

44 Lukin, S. V. Ecological assessment of concentrations of heavy metals and arsenic in soils and crops of the Central Chernozemic region. Eurasian Soil Sci.; 2024; 57, pp. 1709-1717. [DOI: https://dx.doi.org/10.1134/s106422932460146x] 1:CAS:528:DC%2BB2cXitlSitbbL

45 Luo, Yu.; Yang, Sh.; Wen, Ch.; Xu, X.; Xiao, X.; Zhou, J.; Yang, X.; Li, R.; Zhang, J.; Fang, X. Anthropogenic effects on soils in the eastern Tibetan Plateau revealed by geochemical elemental characteristics. Environ. Res.; 2024; 252, 118794. [DOI: https://dx.doi.org/10.1016/j.envres.2024.118794] 1:CAS:528:DC%2BB2cXnsFClt7k%3D

46 Memoli, V.; Eymar, E.; García-Delgado, C.; Esposito, F.; Santorufo, L.; De Marco, A.; Barile, R.; Maisto, G. Total and fraction content of elements in volcanic soil: Natural or anthropogenic derivation. Sci. Total Environ.; 2018; 625, pp. 16-26. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2017.12.223] 1:CAS:528:DC%2BC2sXitVCktrrJ

47 Papazotos, P.; Liakopoulos, A.; Kontodimos, K.; Koukoulis, A. Integrated geochemical analysis of urban and peri-urban soils: A case study of Lamia City, Greece. Environ. Monit. Assess.; 2024; 196, 31. [DOI: https://dx.doi.org/10.1007/s10661-024-13223-8] 1:CAS:528:DC%2BB2cXit1ChsrjF

48 Patino, L. C.; Carr, M. J.; Feigenson, M. D. Local and regional variations in Central American arc lavas controlled by variations in subducted sediment input. Contrib. Mineral. Petrol.; 2000; 138, pp. 265-283. [DOI: https://dx.doi.org/10.1007/s004100050562] 1:CAS:528:DC%2BD3cXhslyrt74%3D

49 Pinskii, D. L.; Shary, P. A. Evaluation of the buffer capacity of soils for copper and statistical assessment of the contributions of its components. Eurasian Soil Sci.; 2024; 57, pp. 1590-1600. [DOI: https://dx.doi.org/10.1134/s1064229324601537] 1:CAS:528:DC%2BB2cXitlSitbbP

50 Penteado, P. B.; Nogarotto, D. C.; Baltazar, J. P.; Pozza, S. A.; Canteras, F. B. Inorganic pollution in urban topsoils of Latin American cities: A systematic review and future research direction. Catena; 2021; 105946, pp. 46-53. [DOI: https://dx.doi.org/10.1016/j.catena.2021.105946] 1:CAS:528:DC%2BB3MXivVCjsbvN

51 Qin, Ya.; Feng, Q.; Holden, N. M.; Cao, J. Variation in soil organic carbon by slope aspect in the middle of the Qilian Mountains in the upper Heihe River Basin, China. Catena; 2016; 147, pp. 308-314. [DOI: https://dx.doi.org/10.1016/j.catena.2016.07.025] 1:CAS:528:DC%2BC28Xht1GhsbzK

52 Rodrigues, W. F.; de Oliveira, F. S.; Schaefer, C. E. G. R.; Gauzzi, T.; Leite, M. G. P. Geochemistry of Antarctic periglacial soils from Harmony Point, Nelson Island. Environ. Earth Sci.; 2021; 80, 16. [DOI: https://dx.doi.org/10.1007/s12665-021-09713-4] 1:CAS:528:DC%2BB3MXhvVOltbbJ

53 Saha, D.; Chatterjee, D.; Chakravarty, S.; Roychowdhury, T. Investigation of environmental-concern trace elements in coal and their combustion residues from thermal power plants in Eastern India. Nat. Resour. Res.; 2019; 28, pp. 1505-1520. [DOI: https://dx.doi.org/10.1007/s11053-019-09451-2] 1:CAS:528:DC%2BC1MXmslGkurg%3D

54 Sang, P. N.; Liu, Zh.; Zhao, Yu.; Hieu, P. T.; Thav, S.; Den, S. Chemical weathering in the Mekong River Basin: Clay mineralogy and element geochemistry of lower-reach river sediments. Appl. Geochem.; 2024; 175, 106179. [DOI: https://dx.doi.org/10.1016/j.apgeochem.2024.106179] 1:CAS:528:DC%2BB2cXitVKgu7rM

55 Siromlya, T. I.; Burachevskaya, M. V.; Mandzhieva, S. S.; Minkina, T. M.; Chernikova, N. P.; Barakhov, A. V.; Chaplygin, V. A. Fractional and group composition of Cr, Ni, and Mn compounds in the main types of soils in background and contaminated areas in the Forest-Steppe zone in Novosibirsk oblast. Eurasian Soil Sci.; 2025; 58, 27. [DOI: https://dx.doi.org/10.1134/s1064229324603688] 1:CAS:528:DC%2BB2MXltFWhtrk%3D

56 Poznanović Spahić, M.; Gulan, A.; Sakan, S.; Tančić, P.; Spahić, D.; Glavaš-Trbić, B. The origin of toxic elements, environmental risk and new methods on prediction of weathering processes: Case study of roadside soils (highway E75, Vojvodina, Serbia). Int. J. Environ. Sci. Technol.; 2024; 22, pp. 5263-5288. [DOI: https://dx.doi.org/10.1007/s13762-024-05978-x] 1:CAS:528:DC%2BB2cXhvFKmtLnI

57 von Blanckenburg, F.; Bouchez, J.; Willenbring, J. K.; Ibarra, D. E.; Rugenstein, J. K. C. There is no Neogene denudation conundrum. Proc. Natl. Acad. Sci. U. S. A.; 2022; 119, e2202387119. [DOI: https://dx.doi.org/10.1073/pnas.2202387119] 1:CAS:528:DC%2BB38XisVCiu7nM

58 Xue, J.; Li, Z.; Feng, Q.; Li, Z.; Gui, J.; Li, Yu. Ecological conservation pattern based on ecosystem services in the Qilian Mountains, northwest China. Environmental Development; 2023; 46, 100834. [DOI: https://dx.doi.org/10.1016/j.envdev.2023.100834]

59 Yang, J.-H.; Du, Y.-S. Weathering geochemistry and palaeoclimate implication of the Early Permian mudstones from eastern Henan Province, North China. Journal of Palaeogeography; 2017; 6, pp. 370-380. [DOI: https://dx.doi.org/10.1016/j.jop.2017.08.003]

60 Yang, M.; Li, G.; Zhu, X.; Ma, Yi.; Liu, Zh. Evaluation of multiple weathering indices of fine-grained river sediments as climate proxies in subtropical and tropical South China. Catena; 2024; 246, 108408. [DOI: https://dx.doi.org/10.1016/j.catena.2024.108408]

61 Yao, Ye.; Liu, X.; Zhang, Zh.; Li, Zh.; Hu, Ya. Spatiotemporal variations of chemical weathering intensity in large drainage basin and its potential climatic implications: A case study from the Yangtze River Valley. J. Geochem. Explor.; 2022; 243, 107093. [DOI: https://dx.doi.org/10.1016/j.gexplo.2022.107093] 1:CAS:528:DC%2BB38XisFOmsLfL

62 Zhang, L.; Wang, B.; Zhang, S. Risk assessment and attribution analysis of potentially toxic elements in soil of Dongdagou, Baiyin, Gansu province, China. Sustainability; 2024; 16, 1689. [DOI: https://dx.doi.org/10.3390/su16041689] 1:CAS:528:DC%2BB2cXltVynsL0%3D

63 Zhang, T.; Tian, G.; Hu, X.; Xie, Yi.; Zhang, L.; Bian, B. Intensity analysis of chromium cycling in south Jiangsu region of China. Chemosphere; 2021; 263, 128138. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2020.128138] 1:CAS:528:DC%2BB3cXhsl2ktr7O

64 Zhang, W.; Ming, Q.; Shi, Zh.; Niu, J.; Su, H. Climate change and drought events in the geochemical records of the lacustrine deposits in the Southeastern Tibetan Plateau. PLoS One; 2016; 11, e0168928. [DOI: https://dx.doi.org/10.1371/journal.pone.0168928] 1:CAS:528:DC%2BC2sXhsFChtLrE

65 Zhangurov, E. V.; Lebedeva, M. P.; Shamrikova, E. V.; Korolev, M. A.; Panyukov, A. N. Soils on carbonate rocks of the Polar Urals: Genesis, properties, and classification. Eurasian Soil Sci.; 2024; 57, pp. 2024-2041. [DOI: https://dx.doi.org/10.1134/s1064229324602099] 1:CAS:528:DC%2BB2MXhs12h

66 Zhou, Y.; Zhao, R.; Zhao, H.; Zhang, L.; Zhang, M.; Zou, J. Effects of different fallow and wetting methods on soil and vegetation properties in the middle reaches of the Heihe River: A case study of Zhangye National Wetland Park. Acta Ecol. Sin.; 2019; 39, pp. 3333-3343. [DOI: https://dx.doi.org/10.5846/stxb201806291437] 1:CAS:528:DC%2BB38XitVGmu7%2FJ