Heavy metal concentrations in soil and ecological risk assessment in the vicinity of Tianzhu Industrial Park, Qinghai-Tibet Plateau

Study area

The study area is located near the Tianzhu Industrial Park (N 36°31′–37°55′, E 102°07′–103°46′) in the eastern Qilian Mountains, on the northeastern edge of the Qinghai-Tibet Plateau. The elevation of the area ranges from 2,040 m to 4,874 m. The distribution of monthly total precipitation and mean temperature is shown in Fig. 1. Mean monthly temperatures range from −11.6 °C in January to 14.4 °C in July, with an average annual temperature of 1.6 °C. Monthly precipitation varies from 2.1 mm in December to 176 mm in June, with most rainfall occurring during the plant growing season (June to September). There is no absolute frost-free period. The primary vegetation consists of alpine species, which are ecologically fragile and highly susceptible to environmental stress. The region experiences a typical mountain plateau climate, characterized by intense sunshine and significant seasonal variations in rainfall and humidity. The predominant soil type is mountain chestnut soil, with a pH range of 7.0 to 8.2.

Sampling sites

In August 2021, soil samples were collected from three depth intervals (0–10 cm, 10–20 cm, and 20–30 cm) at 12 sites distributed across four cardinal directions (east, south, west, and north). These sites were located at distances of 500 m, 1000 m, and 1500 m from the industrial park, as shown in Fig. 2. The 500 m mark was defined as the boundary of the last manufacturer in each direction. All sampling locations were accurately identified and recorded using a Trimble Geo XH 6000 handheld GPS, produced by Beijing Mingtu Technology Co., Ltd., Beijing, China.

Sampling

At each sampling site, three replicate sampling points were selected, spaced approximately 20 m apart, allowing for triplicate samples to be collected at each location. Using a stainless-steel shovel, approximately 1 kg of soil from each depth interval was collected at each sampling point. After collection, the soil samples were thoroughly mixed and packed in zipper-sealed plastic bags. The samples were then transported to the laboratory and air-dried at room temperature for two weeks. Once dried, any visible gravel and plant roots were removed, and the soil was ground and passed through a one mm sieve for elemental content analysis.

Chemical analysis

Precisely 0.5 g of soil was weighed and transferred into a 100 ml pressure-resistant polytetrafluoroethylene (PTFE) vessel for acid digestion using a TOP Wave Microwave Digester (Jena, Germany). The digestion process involved a mixture of HNO₃, HF, and HClO₄ (all HPLC grade) in a 3:1:1 ratio at 120 °C until the solution became clear. Metal analysis was conducted in duplicate for each clarified digested sample. The concentrations of As, Se, Hg, Cd, and Pb were determined using an atomic fluorescence photometer (PF51, Beijing), while Cu, Cr, Mn, Ni, and Zn concentrations were measured using a flame atomic absorption spectrometer (ATS-990) (Kiazai et al., 2019; Lu, 2021).

Evaluation of heavy metal pollution in soil

In this study, soil quality was evaluated using background values for metal elements from the Qinghai-Tibet Plateau (Cheng & Tian, 1993). The ecological risk assessment was performed using the Hakanson potential ecological hazard index (Hakanson, 1980), a widely used method to assess the degree of heavy metal pollution in soil (Lv et al., 2014). The index is calculated as follows: ${\displaystyle C_f^i=C_s^i/C_n^i}$ ${\displaystyle E_r^i=T_r^i\times C_f^i.}$

where $C_f^i$ represents the contamination factor of individual heavy metals, $C_s^i$ is the concentration of metal i in the soil, and $C_n^i$ is the reference concentration of metal i. The potential ecological hazard coefficient for each heavy metal, $E_r^i$, is calculated using the toxic response factor $T_r^i$, which is set at specific values for different metals: 10 for As, 30 for Cd, 2 for Cr, 5 for Cu, Pb, and Ni, 15 for Se, 40 for Hg, and 1 for Zn and Mn (Hakanson, 1980; Han & Xu, 2022).

The potential ecological risk factor ($E_r^i$) is classified into 5 levels: low potential ecological risk ($E_r^i<40$), moderate potential ecological risk ($40\le E_r^i\le 80$), considerable potential ecological risk ($80\le E_r^i\le 160$), high potential ecological risk ($160\le E_r^i\le 320$), and very high ecological risk ($E_r^i>320$) (MacDonald, Ingersoll & Berger, 2000; Keshavarzi & Kumar, 2019).

Data processing and analysis

This study employed a 3 (soil depth) × 3 (distance away from the park boundary) × 4 (direction) factorial design. A general ANOVA model, including all interactions, was used to evaluate the effects of these factors on metal concentrations in the soil. Tukey’s Honest Significant Difference test was applied to identify statistically significant differences between means, with P < 0.05 considered as the threshold for significance. Data were analyzed using SPSS Statistics 22.0 (IBM Corp., Armonk, NY, USA). The analysis indicated significant interactions between metal concentrations and the combined factors of soil depth, distance, and direction (P < 0.05). Further examination revealed that the variation among distances was relatively small compared to the variation due to soil depth and direction. Therefore, metal concentration data for the different distances were presented in a table, while the effects of soil depth and direction were illustrated in graphs created using ArcGIS 10.6 (Esri Inc., Redlands, CA, USA). Pearson correlation analysis was also performed to assess the relationships between metal concentrations.

Heavy metal concentrations in soil

The concentrations of 10 heavy metals: As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Se, and Zn in the soil are summarized in Table 1. As concentrations ranged from 9.8 mg/kg to 56.4 mg/kg, with a mean value of 20.1 mg/kg, slightly higher than the reference value from the Qinghai-Tibet Plateau, suggesting potential As accumulation in the study area. The mean concentrations of Cd and Hg were significantly elevated compared to the reference values for the Qinghai-Tibet Plateau, indicating moderate Cd pollution and elevated Hg levels. Cr and Cu concentrations were also higher than the reference values, reflecting increased levels of these metals in the soil. Mn concentrations ranged from 593 mg/kg to 831 mg/kg, with a mean value of 711 mg/kg, which was close to the reference level. In contrast, the mean Ni concentration was more than double the reference value, suggesting substantial Ni accumulation. Pb concentrations were comparable to the reference, indicating low levels of lead contamination. No data for Se were available for comparison with the Qinghai-Tibet Plateau. Zn concentrations, however, were higher than the reference value, indicating some level of Zn accumulation.

Heavy metal concentrations in soil at three distances from the boundary

The metal concentrations in the soil, along with the standard error of the mean (SEM) and p-values for each metal at three distances (500 m, 1000 m, and 1500 m) from the park boundary, are presented in Table 2. The effect of distance was significant for most metals (P < 0.01, except for Se). However, the variation in metal concentrations across the three distances was smaller compared to the variation observed with soil depth and direction.

The concentrations of Cu, Mn, and Ni increased with distance from the park, while Pb concentrations decreased. Other metals did not exhibit a consistent trend relative to distance from the industrial park. These findings indicate that proximity to the industrial park had a measurable impact on soil contamination, particularly for metals such as Mn, Ni, Zn, and Pb.

Spatial distribution of heavy metals in soil

The heavy metal concentrations at three soil depths (0–10 cm, 10–20 cm, and 20–30 cm) in the eastern, southern, western, and northern directions are presented in Fig. 3. Significant interactions were observed between soil depth and direction (P < 0.05). The concentrations of As (Fig. 3A), Cd (Fig. 3B), Hg (Fig. 3E), Pb (Fig. 3G), Se (Fig. 3I), and Zn (Fig. 3J) generally decreased with increasing soil depth (P < 0.05), although this trend varied by direction. For Cr (Fig. 3C), Cu (Fig. 3D), Mn (Fig. 3F), and Ni (Fig. 3H), the changes in concentration with soil depth significantly interacted with direction (P < 0.05). In the western direction, Cr, Cu, and Mn concentrations increased with soil depth (P < 0.05). Similarly, Cu and Ni concentrations increased with depth in the southern direction (P < 0.05) but decreased toward the eastern side (P < 0.05). In contrast, no significant changes in metal concentrations were observed with depth in the northern direction (P > 0.05).

Potential ecological risk indexes for heavy metals in soil

The potential ecological risk indices for 10 metals (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Se, Zn) across four directions (east, south, west, north) and three distances (500 m, 1000 m, 1500 m) are presented in Table 3. Cd consistently exhibited a high ecological risk across all directions and distances, with particularly elevated risk at 500 m and 1000 m. As showed varying risk levels across distances but remained a major concern, especially in the northern and western directions. Zn posed a high ecological risk in the western and northern directions, with relatively stable risk levels across distances. Hg and Se generally presented lower risk compared to Cd and As, though Hg exhibited significant fluctuations, particularly in the southern direction. For most metals, the ecological risk tended to decrease with increasing distance from the source. However, metals such as Cd and As continued to present significant risks even at greater distances.

Correlations between the soil concentrations of 10 metals

The Pearson correlation coefficients between the soil concentrations of the 10 metals are presented in Table 4. Significant positive correlations (P < 0.05) were observed between the following pairs: As and Hg, Mn, Pb, Se, Zn; Cd and Hg, Pb, Se, Zn; Cr and Cu, Ni; Cu and Pb, Zn; Hg and Mn, Se, Zn; Mn and Se; Ni and Se; Pb and Se, Zn; and Se and Zn. Significant negative correlations (P < 0.05) were found between As and Cr; Cd and Cr; Cr and Hg; Cu and Hg; and Mn and Pb. Notably, strong positive correlations were found between As and Hg, as well as Zn and Cd. In contrast, certain metals, such as Cr and Hg, or Zn and Ni, exhibited weaker or negative correlations.