Characteristics, spatiotemporal distribution, and risk assessment of Cu and Ni pollution in a farmland soil-corn system of arid oasis city in Northwest China

doi:10.21203/rs.3.rs-4956526/v1

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Research Article

Characteristics, spatiotemporal distribution, and risk assessment of Cu and Ni pollution in a farmland soil-corn system of arid oasis city in Northwest China

https://doi.org/10.21203/rs.3.rs-4956526/v1

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The rapid development of mining resources in the northwest oasis industrial and mining cities has brought many environmental problems. Previous research on heavy metals in cities in the Northwest Oasis mainly focused on the soil-wheat system, lacking research on the soil-corn system. As one of the main crops grown in the Northwest region, the pollution of heavy metals in corn grains is closely related to the physical health of the people in the Northwest region. The results show that the average content of Cu and Ni in the soil of the study area were 124.00 mg kg^− 1 and 136.80 mg kg^− 1, respectively, which are both higher than the background value of the area. The content of various heavy metals varies among the various organs of corn, The contents of Cu and Ni were the highest in tassel. The spatial distribution characteristics of heavy metals show that Cu and Ni have similarities in spatial distribution and may have the same source. The average Bio-concentration and translocation factors of corn plants are Cu > Ni. The hazard quotient (HQ) value of both children and adults are less than 1, indicating that Cu and Ni have no significant health risks for both adults and children.

soil-corn system

spatiotemporal distribution

heavy metals

risk assessment

Non-ferrous metals are the dominant mineral resources in northwest China. The development of non-ferrous metals deposits, smelting and processing industries in arid oasis cities has greatly promoted the growth of local economy. However, these industrial activities have also brought serious environmental pollution problems, which have caused a non-negligible impact on the local ecological environment^[1][2][3][4]. JinChang City is a typical resource-based industrial and mining city, as well as a dry oasis city, with rich production of metals such as Cu and Ni, which is known as "Nickel City". Mining, metal smelting, and tailings accumulation are the main factors leading to heavy metal pollution in the soil and rivers of Jinchang City. The accumulation of heavy metals in soil not only affects the yield and quality safety of crops, but also affects the health of local residents through the food chain or direct ingestion^[5][6]. Soil heavy metal pollution is hidden, persistent and irreversible^[7]. The communique on the State of China's ecological Environment in 2022 pointed out that "the main pollutants affecting the environmental quality of agricultural land soil are heavy metals"^[8].

Grain crops constitute one of the primary sources of human exposure to heavy metals, accounting for about 90% of the total intake of heavy metals^[9]. It is very important to understand the current situation of heavy metal pollution in soil and crops around Jinchang City and its impact on food security. Prolonged exposure to Ni can cause symptoms such as vomiting, diarrhea, gastrointestinal bleeding, liver and kidney failure, and death in severe cases^[10]. Prolonged exposure to Ni can cause symptoms such as allergic disease, kidney, lung and nose cancers^[11][9]. It is estimated that about 79.6% of the total annual Cu input into agricultural soils is attributable to agricultural activities^[12]. Land use mainly affected the distribution of heavy metals through different agricultural activities, and the pollution degree increased with the increase of farming intensity^[6]. 67.5% of total Ni per year is attributed to air deposition associated with industrial processes^[13].

In recent years, many scholars have conducted a large number of studies on the accumulation of heavy metals and the health risks of residents in areas polluted by heavy metals. For example, XiaoHu Li et al found that Cu and Ni contents in cultivated soil around the nickel copper mine in Jinchang City were 135.27 mg kg^− 1 and 132.05 mg kg^− 1, respectively, which was 4–6 times the environmental background value of soil in Gansu province^[14]. Gao Jing found that the average content of heavy metals such as Cu, Zn, Ni, Co, Pb and Mn in the soil samples of Jinchang City exceeded the soil background value in the region, and Cu and Ni were the most seriously polluted^[15]. Zhang Chuanhua et al. found that the soil in the cultivated area of Baolong Town, Wushan County, Chongqing was mainly heavily polluted, accounting for 63.89% ^[16]. Bailin Liu et al. found that the pollution in Dongdagou River basin was the most serious, and the pollution in the northeast side away from the river was the lightest. Dongdagou irrigation water was the main source of Cd, Zn, Pb and Cu^[6]. Yifang Zhao et al. conducted a random sampling of corn crops in Guizhou Province in 2021 and found that Ni presents a high risk, and exposure to corn may cause a probabilistic carcinogenic risk for children and adults^[17]. Dun Wu et al. found that the soil Cu and Ni in Wanjiang Economic Zone exceeded the standard to varying degrees, and the soil was moderately polluted. The combined hazard coefficient (HI) of 8 heavy metals in corn for adults and children was greater than 1. Compared with adults, the non-carcinogenic risk of children ingestion of crops was more serious^[18]. Manual zinc smelting in Hezhang area has caused serious environmental heavy metal pollution, and the Pb and Cd contents in the soil and corn seeds of the smelting plant have all or part exceeded the national food limit standard^[5].

Previous studies on heavy metals in oasis cities in Northwest China mainly focused on soil-wheat system, while studies on soil-corn system were lacking. As one of the main cultivated grains in Northwest China, Heavy metal contamination in corn kernels is intimately linked to the health of individuals in the northwest region. In addition, conventional research papers generally divide corn plants into four parts: roots, stalks, leaves, and grains, while there is less research on husks, corncobs, and tassels. The above-ground part of corn is used locally (Dongdagou and Xidagou in Baiyin) as mixed feed for poultry and pigs^[19], so it is necessary to understand the heavy metal pollution in these parts. The purpose of this study is to explore the retention of heavy metals in agricultural soil in Jinchang, an arid oasis city in northwest China, and focus on the soil-corn system to explore the related effects of soil heavy metal pollution on corn crops, so as to provide a relevant basis for the remediation and management of heavy metals in agricultural soil in Jinchang in the future.

The major objectives of this paper were: (1) To explore the contents of Cu and Ni in farmland soil and corn organs in the study area. (2) Reveal the extent of soil pollution in the study area and assess the potential health risks of corn grains. (3) Analyzing the law of heavy metal pollution from the perspective of space; (4) To explore the Bio-concentration and translocation factors of heavy metals in maize.

2.1. Study area overview

Jinchang is one of the major cities in Hexi Corridor. located in 37°47 '10 "-39°00' 30"N, 101°04 '35 "-102°43' 40"E, on the northern slopes of the Qilian Mountain, running from northwest to southeast and is 99 km long from east to west. The climate type of the study area belongs to the temperate arid climate of the mainland. Sufficient light, dry climate, northwest wind throughout the year, day and night, four seasons temperature difference is large, average annual temperature 9.2℃, average annual rainfall 139.80 mm. The Jinchang City has 122,690.59 hectares (1,80,400 mu) of cultivated land, of which 122,686.57 hectares (1,80,300 mu) of irrigated land, accounting for 100%; 4.02 hectares (0.01 mu) of dry land^[20]. The main soil types of cultivated land include irrigated soil, gray brown soil, etc., and the food crops cultivated are mainly wheat, barley, corn and potato^[21].

Since the mining of Jinchuan Nickel Mine, 55 years of development have resulted in a large amount of wastewater, exhaust gas, and solid waste being discharged into the atmosphere, rivers, and other places, leading to increasingly severe environmental problems in the region. According to statistics, Jinchang City will produce 17.9 million tons of general industrial solid waste in 2022, of which tailings, other wastes, smelting waste, phosphogypsum and fly ash account for 97.74% of the city's total industrial solid waste^[22]. The arid climate in the research area has led local residents to prefer using industrial wastewater or domestic sewage to irrigate farmland^[23]. And because the research area is close to the Gobi Desert and desert, and is located in an area with a high incidence of sandstorms, and the occurrence of sandstorms will aggravate the pollution of heavy metals in the environment^[24].

2.2. Sample collection and preprocessing

Use GPS to accurately locate coordinate points and select sampling points based on the location of the beneficiation plant, tailings pond, sewage irrigation area, and wind conditions. In 2021, stainless steel shovels were used to sample corn plants at 15 locations in the study area agricultural land, and soil samples were taken from the surface 15 cm of the sampling points. Sampling points are denoted by 1 to 15. The details of the research area and the distribution of sampling points are shown in Fig. 1. Soil and corn samples are sealed and stored in PE bags. The soil sample is air-dried at 30°C to achieve a constant weight, then ground and sieved through a 10-mesh sieve. After screening, it is stored in PE bags. The corn sample was divided into eight parts as shown in Fig. 2: root, stalk 1, corncobs, grains, husks, stalk 2, leaves, and tassel^[19], Each part is first rinsed repeatedly with deionized water, then placed in a constant temperature drying oven at 70 ° C to a constant weight, and then the dried sample is crushed using a grinder. Then ground and sieved through a 10-mesh sieve. After screening, it is stored in PE bags.

2.3 Chemical analysis of soil and corn

Weigh 2 grams of soil sample and place it in a 55 mL digestion tank. Wet it with a small amount of water and sequentially add 4.00 mL of HF, 6.00 mL of HNO₃, and 2.00 mL of H₂O₂ solution. Let the mixed solution stand for thirty minutes, then use a microwave digestion device to digest it. Transfer the entire amount to a 25ml volumetric flask, dilute with nitric acid solution, and store the diluted solution in a PE bottle. Analysis was performed using a flame atomic absorption spectrometer^[25].

Weigh 2 grams of corn sample and place it in a 55 mL digestion tank. Wet it with a small amount of water and sequentially add 10 mL of HNO₃, and 3.00 mL of H₂O₂ solution. Let the mixed solution stand for thirty minutes, then use a microwave digestion device to digest it. Transfer the entire amount to a 25ml volumetric flask, dilute with nitric acid solution, and store the diluted solution in a PE bottle. Analysis was performed using a flame atomic absorption spectrometer^[25].

Soil agricultural chemical analysis method is used for testing and analysis of soil physical and chemical properties^[26].

2.4. Quality control

To ensure the accuracy of the test results, each soil and corn sample will be analyzed in triplicate relative to the control group. Quality control uses GBW07386 (GSS-30) and GBW10012 (GSB-3). The standard deviation was < 5% for all elements. All containers used during the experiment were immersed in nitric acid solution for more than 1 day and rinsed with deionized water before use. All chemical reagents were guarantee reagent.

2.5 Evaluation method of soil heavy metal pollution

The geo-accumulation index method is a quantitative evaluation method to determine the degree of heavy metal pollution in sediment that has been widely used in the evaluation of heavy metal pollution in soil and dust^[27]. The geo-accumulation index method comprehensively considers the impact of human and natural activities^[28]. Compared with other one-sided evaluation methods, The geo-accumulation index method can more accurately reflect the actual situation of soil heavy metal pollution, and this evaluation result is more authentic. The calculation formula is

$$\:{I}_{geo}={log}_{2}\left(\frac{{C}_{i}}{K\times\:{B}_{i}}\right)$$

where $\:{C}_{i}$(mg kg^–1) is the measured value of heavy metal element $\:i$ in the study area; $\:{B}_{i}$ (mg kg^–1) is the local soil background value of heavy metal element $\:i$ in the study area, and $\:K$ is a coefficient (usually taken as 1.5) that takes into account the possible changes in background values caused by differences in rocks across different regions. The corresponding relationship between soil heavy metal pollution level and $\:{I}_{geo}$ values is shown in Table 1.

Table 1

Grading standard of the geo-accumulation index method
$\:{I}_{geo}$	< 0	0–1	1–2	2–3	3–4	> 4
Graded	0	1	2	3	4	5
pollution degree	unpolluted	Slightly polluted	Moderately polluted	Biased polluted	Heavily polluted	Severely polluted

2.6 Health risk assessment model for heavy metals in grains

Human health risk assessment is commonly used to quantify the potential human health risks associated with exposure to certain heavy metals^[18]. A Referring to the health risk model specified by United States Environmental Protection Agency^[29] and combined it with the Technical Guidelines for Soil Pollution Risk Assessment of Construction Land in China^[30], conduct a health risk assessment of residents in the study area.

The exposure calculation formula is as follows:

$$\:ADI=\frac{{C}_{i}\times\:IngR\times\:EF\times\:ED}{BW\times\:AT}$$

where $\:ADI$ is the average daily intake(mgkg^− 1d^− 1), $\:{C}_{i}$ is the concentration of heavy metals in corn grain (mg kg^− 1), The meanings and values of other parameters in the formula are shown in Table 2^[24][27].

Table 2

Parameters of health risk assessment of heavy metals in corn grains.
Factor	Meaning	Unit	Value
Factor	Meaning	Unit	Adults	Children
$\:IR$	ingestion rate	Kg/d	0.15	0.1
$\:ED$	exposure duration	a	30	10
$\:EF$	exposure frequency	d/a	365	365
$\:BW$	body weight of the exposed individual	kg	70	16
$\:AT$	average time	d	365$\:\times\:ED$

The health risk of agricultural products intake is typically characterized by the hazard quotient (HQ)^[4]. The HQ is the ratio of the ADI of heavy metal to its reference dose (RfD)^[24]. and its calculation formula is as follows:

$$\:HQ=\frac{ADI}{RfD}$$

where RfD is the exposure reference dose for heavy metal(mg kg^− 1 d^− 1). Usually, when HQ ≤ 1, it indicates that there is low or no health risk; When HQ > 1, it indicates the presence of non-carcinogenic health risks.

2.7 Bio-concentration and translocation factors

Bio-concentration factor (BCF) and translocation factor (TF) are important coefficients for studying the ability of plants to absorb heavy metals and the transfer of heavy metals within plants. The Bio-concentration factor is an indicator that measures the difficulty of plants accumulating heavy metals in soil. The larger the value, the easier it is for plants to absorb the heavy metal^[1]. The translocation factor reflects the ability of heavy metals to migrate from roots to other aboveground parts, and its value reflects the ability of heavy metals to transfer from roots to aboveground parts^[1]. The calculation formula for BCF is$\:BCF=\frac{{C}_{w}}{{C}_{s}}$

where $\:{C}_{w}$ (mg kg^–1) is the heavy metal content in crop organs; and $\:{C}_{s}$ (mg kg^–1) is the heavy metal content in crop soil.

The calculation formula for TF is$\:TF=\frac{{C}_{w}}{{C}_{r}}$

where $\:{C}_{w}$(mg kg^− 1) is the heavy metal content in crop organs; and $\:{C}_{r}$ (mg kg^− 1) is the heavy metal content in crop roots.

2.8 Statistical analysis

Perform statistical analysis on chemical analysis data of plants and soil using Microsoft Excel 2016. And use Origin 2022 Pro (Origin Lab, USA) for image rendering. Use Pearson correlation matrix to analyze the correlation between heavy metals and soil properties, as well as heavy metals in corn kernels. Operate on the inverse distance weighting method based on ArcGis (10.8) to depict the spatial distribution map of heavy metals.

3.1 Heavy metal content in soil

The analysis results of heavy metal element content in soil samples are shown in Table 3. The range of Cu content in soil is between 24.10-682.00mg kg^− 1, with a mean value of 124.00mg kg^− 1 and a large variation range. The range of Ni content is between 21.65-916.10mg kg^− 1, with a mean value of 136.8mg kg^− 1. The mean content of the two elements exceeds the soil background values of Jinchang City (GB62/T 4524 − 2022), which is 3.32 and 4.47 times the background value, respectively, indicating that the soil at the sampling points in the study area has been contaminated with heavy metals Cu and Ni, and the degree of pollution is relatively high. Moreover, the average value of Cu has exceeded the risk screening values for soil contamination of agricultural land (GB15618-2018), with 73.33% of the data exceeding the soil background values of Jinchang City and 26.67% exceeding the Risk screening values for soil contamination of agricultural land. The Ni content at 53.33% of the sampling points exceeds the soil background values of Jinchang City, and the Ni content at 20% of the sampling points exceeds the Risk screening values for soil contamination of agricultural land. This indicates that there is a risk of soil pollution in agricultural land in these areas.

Table 3

Descriptive statistics of soil properties and heavy metal concentrations in agricultural soils and related soil quality standards (mg kg^–1)
Statistical values	Cu	Ni	Ph	EC(µScm^− 1)	OM(g kg^− 1)	DOC(mg l^− 1)	CEC(cmol⁺ kg^− 1)
Minimum	24.1	21.65	7.92	143	14.26	20.78	0.12
Maximum	682.0	916.1	8.23	324	38.87	58.65	8.97
Mean	124.0	136.8	8.14	186.23	28.11	37.39	3.82
Standard deviation	173.36	224.21
Coefficient of variation (%)	139.81	163.95
Over standard rate(%)	26.67	20
Risk screening values for soil contamination of agricultural land	100	190
Soil background values of jinchang city	37.3	30.6

The coefficient of variation (CV) of heavy metal pollution is a statistic that measures the uniformity and variability of heavy metal elements in the study area^[31]. The larger the CV value of pollutants, the greater the impact of human activities^[32]. The CV values of Cu and Ni are 139.81% and 163.95%, respectively, indicating strong variability, indicating that the spatial distribution of Cu and Ni is uneven, and the content of heavy metals in soil is not only affected by geological background, but also by human activities^[37]. Large spatial differences indicate that industrial activities may be a potential source of heavy metal pollution^[34].

3.2 Assessment of soil heavy metal pollution

The spatial distribution of heavy metals can be used to evaluate the possible sources of soil heavy metal pollution. The distribution of heavy metals in the soil is shown in Fig. 3, where different concentrations of different heavy metals are displayed in different colors, with green indicating low concentrations and red indicating high concentrations. The distribution of Cu and Ni in the soil is similar, with high concentration areas concentrated near sampling points 1, 2, and 3, and the concentration of heavy metals in the soil decreasing as the distance from the sampling points increases. This indicates that the pollution of heavy metals Cu and Ni in the soil may have the same source. Sampling point 2 is near the Jinchuan Group Metallurgical Plant, tailings pond, Jinchuan Group Copper Slag Mining, and residential areas. The high concentration of heavy metals in this area may be due to long-term irrigation with sewage and the emission of waste gases from the metallurgical plant, causing heavy metals to settle in the soil through the atmosphere^[14].

As can be seen from Fig. 4, pollution is mainly concentrated in sampling points 1, 2, 3 and 14. Sampling point 9, 13, and 15 have mild Cu pollution, accounting for 20%; sampling point 3 has moderate Cu pollution, accounting for 6.67%; sampling point 1 and 14 have moderate Cu pollution, accounting for 13.33%; sampling point 2 has severe pollution, accounting for 6.67%; the remaining sampling points are not polluted, accounting for 53.33%. Sampling point 9, 11, 12, and 15 have mild Ni pollution, accounting for 26.67%; sampling point 1, 3, and 14 have moderate pollution, accounting for 20%; sampling point 2 has severe pollution, accounting for 6.67%. The remaining locations are uncontaminated, accounting for 46.67%. These data indicate that only sites 1, 2, 3, and 14 are severely contaminated with Cu and Ni, Other locations have less or no pollution.

3.3. Distribution characteristics of Cu and Ni in different plant parts

The content of heavy metals in each component of corn is shown in Fig. 5. The average content in the roots of corn samples is Ni(12.99mg/kg) > Cu(9.20mg/kg); the average content in the stalk1 of corn is Cu(1.89mg/kg) > Ni(0.79mg/kg); the average content in the stalk2 of corn is Cu(3.55mg/kg) > Ni(1.39mg/kg); the average content in the leaves of corn is Cu(23.43mg/kg) > Ni(13.84mg/kg); the average content in the corncobs is Cu(3.04mg/kg) > Ni (0.1mg/kg); the average content in the husks is Cu(4.68mg/kg) > Ni(2.47mg/kg); the average content in the grains of corn is Cu(0.64mg/kg) > Ni(0.37mg/kg); the average content in the tassel of corn is Cu(23.62mg/kg) > Ni(21.67mg/kg).

Different heavy metals are distributed differently in corn, with Cu showing the following distribution in corn organs: tassel > leaves > roots > husks > stalk 2 > corncobs > stalk 1 > grains, which is consistent with the results of Su Chun-tian et al^[33]. Ni shows the following distribution in corn organs: tassel > leaves > roots > husks > stalk 2 > stalk 1 > grains > corncobs; it can be seen that heavy metals are mainly concentrated in the anther and leaves, which is consistent with the results of Li Ye-pu et al^[19]. The reason why the heavy metals in the corn anther are higher than those in other parts (except root and leaf) may be that the corn anther growth period is shorter (10–15 d), and it needs a large amount of nutrients in a short time. Meanwhile, pollutants can enter the anther along with nutrients. Pollutants enter the leaves through the soil-root-leaf and atmospheric-leaf routes. Xiao-Hu Li found that the heavy metal content in the dust on the surface of the slag pile was relatively high. The maximum concentrations of Cu and Ni were 4698.70 and 2310.86 mg kg^− 1, respectively, with an average of 1744.87 and 1172.14 mg kg^− 1[14]. This can explain why the pollutant content in the leaves is higher than that in other organs^[19]. It can be seen that although the distribution of Cu and Ni in corn plants is different, the general trend of distribution is consistent, and both heavy metals are easily accumulated in the tassel of corn.

Corn is the main food for local residents and livestock feed, and the quality of food safety affects the health of local residents. The Cu content in corn grains ranges from 0 to 1.38 mg kg^− 1, with an average of 0.64 mg kg^− 1. Because there is no specific limit for Cu in corn in the latest national standard for food safety (GB 2762 − 2022), we refer to the food copper limit standard of 10 mg kg^− 1 for grain as a reference value. All 15 sampling points had corn grain copper content that did not exceed this limit. The Ni content in corn grains ranges from 0 to 1.52 mg kg^− 1, with an average of 0.37 mg kg^− 1. We refer to the food safety standard for Ni limit of 1 mg kg^− 1 for oils and fats as a reference value. Only sampling points 1 (1.09 mg kg^− 1) and 2 (1.52 mg kg^− 1) exceeded the limit, and the rest were less than 1 mg kg^− 1. The non-compliance rate was 13.33%. This shows that soil pollution does not necessarily mean that corn crops are polluted, but sampling points 1 and 2 have corn grain Ni pollution, and sampling points 1 and 2 have heavy soil Cu and Ni pollution and pollution. This area is not suitable for growing corn crops.

3.4 Spatial distribution characteristics of heavy metals in various organs of corn

The spatial distribution characteristics of heavy metals can be used to evaluate the possible sources of soil heavy metal pollution. The distribution of heavy metals in various organs of maize is shown in Fig. 6, where different concentrations of heavy metals are displayed in different colors, with green indicating low concentrations and red indicating high concentrations.

The distribution of Ni concentration in corn kernels is similar to that in soil, with high concentrations concentrated in sampling points 1 and 2. The distribution of Ni content in soil and corn kernels is highly similar, indicating that soil Ni pollution can predict Ni pollution in corn kernels. The distribution of Cu content in corn kernels is different from that in soil, with high concentrations of Cu in corn kernels located at sampling point 14. This spatial difference between soil and corn kernels may be due to differences in soil physicochemical properties and bioavailability of heavy metals in soil^[4].

The Cu content in roots, leaves, and seed coats is similar to the distribution of Cu and Ni in the soil, with two high-concentration areas in the roots. The distribution of Cu and Ni in stem 1 is similar to that in the soil, but there are differences between them. The high-concentration areas are mainly concentrated at point 15. The distribution of Cu in stem 2 is similar to that in the soil, with high concentrations at points 1, 2, 12, and 13. The high-concentration areas of Ni in stem 2 are concentrated at points 2. The high-concentration areas of Cu in corn cob are at points 14 and 15, and the high-concentration areas of Ni are at point 10. The high-concentration areas of Cu and Ni in male inflorescences are located at points 7. Such differences may be due to long-term agricultural cultivation, as the agricultural soil in Jinchuan District, Jinchang City has been affected by human activities^[4]. The distribution pattern of metals may be affected by various pollution sources, such as sewage irrigation containing heavy metals^[38], long-term fertilization on soil^[39], and the emission of heavy metals from coal and industrial waste gases that are transported to the soil through atmospheric dust^[40].

To further understand the relationship between heavy metal content in corn kernels and soil, a correlation analysis was conducted between heavy metal content in rice kernels and soil (Fig. 7), and the Pearson correlation coefficient was used to analyze the impact of soil on heavy metal content in corn kernels. The results showed that soil Ni and soil Cu showed a highly significant positive correlation (P < 0.01), and grain Cu and grain Ni also showed a highly significant level (P < 0.01). These correlations suggest that heavy metals may have homology; There is a highly significant correlation (P < 0.01) between soil Ni and soil Ni. This result indicates that an increase in soil Ni heavy metal concentration will significantly increase the Ni content in seeds, which is consistent with the previous conclusion. Zhou Yan et al. also obtained similar results^[41]; There is a highly significant correlation between soil Cu and grain Ni, indicating that the size of grain Ni content is related to the size of soil Cu content, which may be because copper is an essential nutrient element for crops^[42]. The correlation between soil Cu and grain Cu is not significant, indicating that the Cu content in the soil has not reached the toxic range. In the absence of Cu element, plant roots can resist the transportation of Cu to the aboveground part of the plant. The absorption of heavy metals by plants depends on their activity, and is also greatly influenced by soil pH and organic matter content^[43].

3.5. BCFs and TFs of Cu and Ni

The average enrichment coefficients of heavy metals Cu and Ni in different organs of corn are shown in Table 4. From Table 4, it can be seen that the average enrichment coefficients of Cu in the organs of corn are as follows: tassel > leaves > roots > stalk 2 > corncobs > husks > stalk 1 > grains; the average enrichment coefficients of Ni in the organs of corn are as follows: tassel > roots > leaves > stalk 2 > stalk 1 > husks > grains > corncobs. The organs of corn with the strongest ability to enrich Cu and Ni are tassel, with enrichment coefficients of 0.6106 and 0.5282, respectively. There are also differences among the elements, such as the strong enrichment of Cu in leaves and tassel, and the weak enrichment in corn grains. The enrichment of Ni in roots and tassel is strong, while it is weak in corn cores. The order of enrichment of the heavy metal elements in the roots is Ni > Cu, while in other organs it is Cu > Ni. This may be because the aboveground parts except the roots are also polluted by Cu in atmospheric deposition^[14]. The average enrichment coefficients of corn plants are in the order of Cu > Ni, which is consistent with the study of Jiangyun Liu et al^[34].

Studies have shown that different plant organs have different biological utilization rates of heavy metals, and the root system has the highest absorption and bioaccumulation rate of heavy metals^[35]. Based on this study, it can be inferred that in the corn-soil system of the arid oasis city in northwest China, the tassel of corn have a stronger ability to enrich Cu and Ni than other organs. The migration coefficients of Cu and Ni in different organs of maize are shown in Table 5, from which we can see that: the migration coefficients are similar to the accumulation coefficients, and both Cu and Ni elements show strong migration ability in the anther and leaves. This indicates that it is easier for Cu and Ni elements to migrate from the underground parts to the leaves and tassel. The migration coefficients of Cu and Ni in corn kernels are 0.1255 and 0.0337, respectively, indicating that heavy metals are difficult to migrate from the roots to the corn grains. This may be because the roots are the first barrier for heavy metals to transfer to the edible parts of the plant^[36]. The migration coefficients of Cu and Ni in maize organs are all expressed as: Cu > Ni.

Table 4

Bio-concentration factors (BCFs) in different organs of corn crops
		roots	stalk 1	corncobs	grains	husks	stalk 2	leaves	tassel
Cu	Maximum	0.1642	0.2105	0.1237	0.0281	0.1203	0.2315	0.6192	4.3154
	Minimum	0.0468	0.0022	0.0055	-	0.0103	0.0103	0.1262	0.0107
	Mean	0.0929	0.0305	0.0605	0.0114	0.0543	0.0543	0.2902	0.6106
Ni	Maximum	1.1224	0.0430	0.0279	0.0314	0.0538	0.0763	0.2143	3.9412
	Minimum	0.0280	-	-	-	-	-	0.0771	0.0053
	Mean	0.1803	0.0141	0.0020	0.0048	0.0111	0.0212	0.1250	0.5282

Table 5

Translocation factors (TFs) in different organs of corn crops
		stalk 1	corncobs	grains	husks	stalk 2	leaves	tassel
Cu	Maximum	3.3735	1.2735	0.3878	1.9277	2.6786	6.1224	44.4444
	Minimum	0.0387	0.0984	-	0.1014	0.1483	1.2440	0.1908
	Mean	0.3970	0.6394	0.1255	0.6345	0.7322	3.2109	6.6992
Ni	Maximum	0.4817	0.1810	0.1606	0.6057	0.6534	2.7500	33.7423
	Minimum	-	-	-	-	-	0.1872	0.0808
	Mean	0.1098	0.0130	0.0337	0.1191	0.1685	1.1796	4.8011

3.6 Health risk assessment of corn grains

The health risk assessment of residents in the study area was conducted using the US Environmental Protection Agency (USEPA) recommended health risk model^[29], with Ni RfD set at 0.02 and Cu RfD set at 0.037mg (kg · d). The health risk assessment results of heavy metal exposure in corn kernels in the study area are shown in Fig. 8. The average HQ values of children in Jinchuan District, Jinchang City through ingestion of Cu and Ni are 0.10731982 and 0.114583333, respectively, while the average HQ values of adults through ingestion of Cu and Ni are 0.036795367 and 0.039285714. The non carcinogenic risk index Ni for children and adults is slightly higher than Cu, indicating that Ni has a slightly higher non carcinogenic risk than Cu. It was found that the risk index of children is generally higher than that of adults, which is consistent with previous research results^[18]. This may be due to the underdeveloped metabolic organs such as liver and kidney in children, which have weaker detoxification and excretion functions for toxic and harmful substances, making them more sensitive to environmental pollution^[41]. The HQ values of heavy metals for both adults and children are less than 1, indicating that although there are multiple sampling points in the study area with moderate to severe soil pollution, there is no significant health risk for adults and children.

The average content of Cu and Ni heavy metals in the soil within the study area exceeded the soil background values of Jinchang City, and 26.67% of the Cu data exceeds the risk screening values for soil contamination of agricultural land. The Ni content in 20% of the sampling points exceeds the risk screening values for soil contamination of agricultural land, indicating that there is a risk of soil pollution in agricultural land in these areas. Among the 15 sampling points in the study area, the proportion of Cu pollution above mild pollution was 46.67%, and the proportion of Ni was 53.33%. The spatial distribution of heavy metals in soil and corn shows that the Ni content in soil and corn kernels is similar, indicating that soil Ni pollution can be used to predict corn kernel Ni pollution. It was found that the Ni content in corn kernels at sampling points 1 and 2 has exceeded the relevant limits in the National Food Safety Standard (GB 2762 − 2022), so the farmland at sampling points 1 and 2 is no longer suitable for planting corn crops. However, there is no such relationship between soil Cu and corn kernel Cu. Heavy metal pollution varies among different organs of corn, with Cu showing the following pattern in corn organs: tassel > leaves > roots > husks > stalk 2 > corncobs > stalk 1 > grains, while Ni shows the following pattern in corn organs: tassel > leaves > roots > husks > stalk 2 > stalk 1 > grains > corncobs. Both Cu and Ni elements show strong enrichment and migration abilities in tassel and leaves, with Cu > Ni, indicating that Cu exhibits higher activity in corn. The health risk assessment results showed that the HQ values for both adults and children are less than 1, indicating that eating corn has no significant adverse effects on the health of children and adults.

Author Contributions All authors contributed to the study conception and design. Conceptualization, S.X. and C.J.; formal analysis, A.W.; investigation, S.X., A.W., G.G., K.L. and Y.S.; resources, S.X., G.G. and K.L.; data curation, S.X.; writing—original draft preparation, A.W.; writing—review and editing, S.X., C.J. and J.L.; funding acquisition, S.X. All authors read and approved the final manuscript.

Data Availability Statement The raw data supporting the conclusions of this article will be made available by the authors on request.

Funding This study was supported by the National Natural Science Foundation of China (Grants No. 42261134537). J.J. Liu was funded by Inner Mongolia Agricultural University commissioned project (Grant No. 2024JBGS0019)

Acknowledgements: S.H. Xu was funded by Lanzhou University of Technology commissioned project.

Conflict of interest The authors declare no competing interests.

Consent to participate Consent for publication was obtained from all participants.

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Characteristics, spatiotemporal distribution, and risk assessment of Cu and Ni pollution in a farmland soil-corn system of arid oasis city in Northwest China

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Abstract

Figures

1. Introduction

2. Materials and methods

2.1. Study area overview

2.2. Sample collection and preprocessing

2.3 Chemical analysis of soil and corn

2.4. Quality control

2.5 Evaluation method of soil heavy metal pollution

2.6 Health risk assessment model for heavy metals in grains

2.7 Bio-concentration and translocation factors

2.8 Statistical analysis

3. Results and discussion

3.1 Heavy metal content in soil

3.2 Assessment of soil heavy metal pollution

3.3. Distribution characteristics of Cu and Ni in different plant parts

3.4 Spatial distribution characteristics of heavy metals in various organs of corn

3.5. BCFs and TFs of Cu and Ni

3.6 Health risk assessment of corn grains

4. Conclusions

Declarations

References

Additional Declarations

Supplementary Files

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