Pollution Evaluation in Soils and Health Risk in Vegetables of Heavy Metals in Surrounding Lanzhou City in Gansu Province, China

Pollution Evaluation in Soils and Health Risk in Vegetables of Heavy Metals in Surrounding Lanzhou City in Gansu Province, China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Pollution Evaluation in Soils and Health Risk in Vegetables of Heavy Metals in Surrounding Lanzhou City in Gansu Province, China Han-ru Ren, Jun Ren, Ling Tao, Xue-chang Ren This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5021647/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Heavy metal (HMs) contamination in soil causes secondary pollution of vegetables and poses a great threat to health. Soil and vegetable samples were collected from eight different districts in the vegetable base of Lanzhou city in Gansu province. The heavy metal (Zn, Cd, Cr, Cu, and Pb) contents were determined using inductively coupled plasma atomic emission spectroscopy. The results suggest that the Cr and Zn contents of soils in the eight plantation bases were much higher than those of the other three metal contents. The metal concentrations showed significant differences among plantation bases and vegetable species, and the mean HM concentrations of vegetable bases exceeded background levels by 1.1~3.0 times. The accumulation of Cu in vegetables was significantly higher than that of other metals. Remarkable differences were found among the vegetables in the uptake abilities of Zn, Cd, Cr, and Cu. From the linear model regression analysis, significant positive relationships were found between the accumulation of HMs in vegetables and soil content. The information found in this work may be used to provide referential strategies and methods to minimize the impact of HMs on human health through the consumption and cultivation of vegetables. Heavy metals Vegetable Soil Bioconcentration Health risk Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 1. Introduction The main sources of heavy metals in the atmosphere, hydrosphere, and biota are soil (Ahmad & Goni 2010; Minhaz et al. 2018 ; Alturiqi et al. 2020 ), and HM pollution and accumulation in the ecosystem pose serious problems worldwide. Heavy metal (HM) contamination of water, soil, and crops is a severe environmental problem that has attracted worldwide attention. Agricultural soils are prone to contamination with HMs from atmospheric deposition and various anthropogenic activities such as uncontrolled discharge from industrial and urban waste materials, sewage sludge, wastewater irrigation, and excessive chemical fertilizers and pesticides (Chen et al. 2019 ; Jalali & Meyari 2020 ). Excessive HMs in soil always cause potential threats to the environment and food safety, and have damaging effects on human and animal health (Osma et al. 2013 ; Swartjes et al. 2013 ; Zeng et al. 2018 ; Gebeyehu & Bayissa 2020 ; Lai et al. 2022 ; Moghaddam et al. 2022 ; Nolos et al. 2022 ). Recently, the pollution problem in agricultural soils has begun to draw the attention of many scientists and countries. Thus, studying HM contamination of soil, conducting risk assessments, and identifying pollution sources can provide evidence for relevant departments to develop approaches to control pollution. Most HMs do not undergo microbial or chemical degradation, which poses a significant threat to the environment and food safety. HMs can be harmful because of their potential to accumulate in different body parts of human beings and have adverse health effects, even at low concentrations (Khan et al. 2023a , 2023b ; Li et al. 2024 ). Vegetables are important edible crops and an essential part of the human diet. They are rich in nutrients required for human health and are an important source of carbohydrates, vitamins, minerals, and fiber. HMs in soils can be readily taken up by vegetable roots and can accumulate at high levels in the edible parts of vegetables, even at low levels in soil (Gaurav et al. 2018 ). The uptake and bioaccumulation of HMs in vegetables are influenced by a number of factors, such as climate, atmospheric deposition, the concentrations of HMs in soil, the physicochemical properties of the soil on which the vegetables are grown, and the degree of maturity of the plants at the time of harvest (Zhou et al. 2016 ; Leblebici et al, 2020 ; Gupta et al. 2021 ; Wang et al. 2021 ). Many phosphate rocks contain HMs such as Pb and Cd, and high application rates of phosphorus (P) fertilizer may not only increase soil P but also lead to the accumulation of metals above the maximum limited values (Ogbonna et al. 2013 ; Xu et al. 2022 ). The vegetable planting bases are on the outskirts of Lanzhou city, which is the principal vegetable production site for people living in Lanzhou and nearby. However, HMs accumulate in soils and vegetables because of the excessive use of chemical and organic fertilizers, pesticides, and growth-regulating agents. To date, the HM content of agricultural soil in the vegetable plots of Lanzhou and its pollution problem have been studied very little, and there has been no systematic investigation of HMs in soil and vegetables, as well as the accumulation and transfer characteristics of HMs in these districts (Khan et al. 2023 ; Khan et al. 2023 ). As HMs in soil have a long residence time and are potentially dangerous, it is very important to study the condition of HMs accumulation in soil and vegetables (Agbenin et al. 2009 ; Fang et al. 2011 ; Wang et al. 2012 ; Eliku & Leta 2017 ; Chen et al. 2018 ; Deng et al. 2021 ). It is also vital to pay attention to food safety, which will bring about potential adverse effects on human beings through vegetables polluted by HMs (Sawut et al. 2018 ; Alfaro et al. 2022 ). In this study, field investigation and systematic sampling were carried out for HMs, including Zn, Cd, Cr, Cu, and Pb, in soil and vegetables in the vicinity of Lanzhou. The aims of this study were: 1) to detect the contents of five metals in soil and six main species of vegetables, and to examine the relationship between them; 2) to assess the bioaccumulation factor of heavy metals from soil to vegetables; 3) to investigate the relationship and difference between the metals and the species of vegetables; and 4) to assess the risk of HMs in vegetables and soils in eight planting bases surrounding Lanzhou City in Gansu Province, China. The results can provide a scientific basis for harmless cultivation and a more scientific method for the risk assessment of HM hazards in vegetables by using a comprehensive risk index to jointly evaluate the impact of HMs in soil and vegetables on human health. 2. Materials and methods 2.1. Study area Eight vegetable planting bases are located in the vicinity of Lanzhou city in Gansu province, China, at longitudes of 103°35ʹ–103°55ʹ east and latitudes of 36°00ʹ–36°08ʹ north. These planting bases are situated in the upper reaches of the Yellow River and are named Anning, Xigu, Chengguan, Heping, Dingyuan, Zhonghe, Pingan, and Huazhuang (Fig. 1 ). The climate is subtropical monsoon, with an average annual temperature of 10.3°C, average annual precipitation of 327.8 mm and inadequate rainfall. The farmland is irrigated with the Yellow River water. The four distinct seasons and superior water heat conditions were conducive to crop growth. 2.2. Vegetables and soils sampling Eight sampling sites were randomly selected in the vicinity of Lanzhou city, each sampling site was recorded by using global position system (GPS) (Fig. 1 ), six vegetables and corresponding soil samples in each site were collected from April to October 2021, each sampling was carried out with six replicates. Soil samples were collected from the surface layer (0–20 cm), air-dried and disaggregated. The identifiable stones and plant debris were removed and the samples were passed through 2 mm mesh sieve. To determine HM contents, a representative subsample of every soil sample was finely ground with a porcelain mortar, passed through 0.15 mm mesh sieve, and stored in closed plastic containers. The most common vegetables from the soil sampling sites were selected for the analysis. These included six different vegetable samples locally grown and consumed by the population: lettuce ( Lactuca sativa L.), rape ( Brassica campestris L.), leek ( Allium tuberosum Rottl. ex Spreng), scallion ( Allium fistulosum L.) cucumber ( Cucumis sativus L.) and zucchini ( Cucurbita maxima Duch. ex Lam.). The edible parts of the vegetable samples were first lightly washed with tap water to remove surface dust, then washed with deionized water, dried with filter paper, weighed, dehydrated in an oven at 105°C for 2 h, and finally stored at 75°C for 48 h. 2.3. Analysis of samples The pH and electrical conductivity (EC) of the soil samples were determined using a soil/water slurry (1:5 w/v). The organic matter (OM) of the soil was measured using the K 2 Cr 2 O 7 volumetric method in an oil bath. Soil samples were digested with concentrated nitric acid (HNO 3 ), hydrofluoric acid (HF), hydrochloric acid (HCl), and perchloric acid (HClO 4 ). The plant samples were digested with concentrated HNO 3 . All containers were soaked at least 24h with 2% nitric acid before use. To ensure the accuracy of the analysis, each sample was subjected to &, and the mean was used as the final determination of the metal concentration. The Zn, Cd, Cr, Cu, and Pb contents were determined using inductively coupled plasma atomic emission spectroscopy (ICP-AES). 2.4. Evaluation of heavy metal pollution in soil The pollution levels of single and comprehensive HMs in soil were assessed using single-factor (P i ) and Nemerow’s synthetic pollution index (P n ). These indices were computed using the following equations (Sawut et al. 2018 ; Yu et al., 2021 ). Where P i is the single-factor index, C i is the concentration of each HM, and S i is the standard value for each HM (Table 1 ). P imax is the maximum of single-factor index, and P n is classified as safety (P n ≤0.7, Class I), precaution (0.7 < P n ≤1.0, Class II), slightly polluted (1.0 < P n ≤2.0, Class III), moderately polluted (2.0 3.0, Class V). $$\:{\text{P}}_{\text{i}}={\text{C}}_{\text{i}}/{\text{S}}_{\text{i}}$$ $$\:{\text{P}}_{\text{n}}=\sqrt{({\text{P}}_{\text{i}\text{m}\text{a}\text{x}}^{2}+{\stackrel{-}{\text{P}}}^{2})/2}$$ The ecological risk index (RI), which comprehensively considers HMs content, environmental influence, and biotoxicity (Hakanson 1980 ), was used to evaluate the risk of multiple HMs from soils to assess HM pollution levels. The RI is computed by following equations, where \(\:{\text{E}}_{\text{r}}^{\text{i}}\) represents the potential ecological risk index of each HM, \(\:{\text{C}}_{\text{s}}^{\text{i}}\) is the concentration of each HM in soil, \(\:{\text{C}}_{\text{b}}^{\text{i}}\:\) is the background value of HM in soil in this region, \(\:{\text{T}}_{\text{r}}^{\text{i}}\) is the toxic response coefficients and the values of Cu, Cr, Pb, Cd, and Zn are 5, 2, 5, 30 and 1, respectively. The RI classifications were low risk (RI < 150), moderate risk (150 ≤ RI < 300), considerable risk (300 ≤ RI < 600), and high risk (RI ≥ 600). The risk degree of single HM ( \(\:{\text{E}}_{\text{r}}^{\text{i}}\) ) is low ecological risk ( \(\:{\text{E}}_{\text{r}}^{\text{i}}\) <40), moderate ecological risk (40≤ \(\:{\text{E}}_{\text{r}}^{\text{i}}\) <80), considerable ecological risk (80≤ \(\:{\text{E}}_{\text{r}}^{\text{i}}\) <160), high ecological risk (160≤ \(\:{\text{E}}_{\text{r}}^{\text{i}}\) <320), and very high ecological risk ( \(\:{\text{E}}_{\text{r}}^{\text{i}}\) ≥320). The geo-accumulation index (I geo ) is usually applied to assess the pollution level of HMs in soil and is calculated using the following equation (Wang et al., 2012 ), where K is introduced as a constant 1.5 to minimize the possible influence of background values due to geogenic variation. The pollution degrees of I geo was classified as unpolluted (I geo ≤0), slightly to moderately polluted (0 < I geo ≤1), moderately polluted (1 < I geo ≤2), moderately to heavily polluted (2 < I geo ≤3), heavily polluted (3 < I geo ≤4), heavily to extremely polluted (4 5). $$\:{\text{I}}_{\text{g}\text{e}\text{o}}={\text{l}\text{o}\text{g}}_{2}({\text{C}}_{\text{s}}^{\text{i}}/{(\text{K}\times\:\text{C}}_{\text{b}}^{\text{i}}))$$ 2.5. Health risk assessment of heavy metals for vegetable The health risk of HMs in vegetables can be assessed by the target hazard quotients (THQ) and hazard index (HI), which were proposed by the US Environmental Protection Agency (USEPA 2000). The THQ ij was calculated using Eq. 6 to assess the non-carcinogenic risks of vegetable i HM and j, and HI i was computed to estimate the potential risk of i HMs for all vegetables using Eq. 7 (Alfaro et al. 2022 ). Where C ij is the concentration of HM in j vegetables (mg/kg, fresh weight), IR is the ratio of vegetable ingestion (kg/day) for lettuce (0.09), rape (0.08), leek (0.06), scallion (0.03), cucumber (0.12), and zucchini (0.09) (Swartjes et al. 2013 ); EF is exposure frequency (365 d/a); ED is exposure duration (76.4 years, life expectancy in China according to World Health Statistics 2018); BW represents the average of body weight (70 kg); AT represents the average exposure time for non-carcinogenic effects (assuming 76.4 years, 365 days a year); RfD is the daily reference dose of HMs (mg/kg·d), the values of RfD for Cu, Cr, Cd, Zn and Pb were 0.04, 0.003, 0.001, 0.3 and 0.0035, respectively (Wang et al., 2021 ). If the value of THQ or HI is ≤ 1.0, there is no obvious health risk to residents; on the contrary, non-carcinogenic risks are likely to occur when THQ or HI is > 1.0, and the health risk increases with an increase in THQ or HI. 2.6. Bioconcentration factors for heavy metals (BCF) The bioconcentration factor (BCF) was used to evaluate the potential for HM accumulation in vegetables related to HM concentrations in soils. BCF was calculated using the following equation (Alfaro et al., 2022 ), Where C vegetable is the HM content in vegetables and C soil is the HM concentration in the soil. BCF \(\:=\frac{{\text{C}}_{\text{v}\text{e}\text{g}\text{e}\text{t}\text{a}\text{b}\text{l}\text{e}}}{{\text{C}}_{\text{s}\text{o}\text{i}\text{l}}}\) 2.7. Data processing and analyses Statistical analyses were performed using STATISTICA 7.0. Summary statistics such as mean, standard deviation, minimum and maximum concentrations, median, and skewness were obtained to characterize soil properties and HM contents. To assess contamination status, Government Standards or guidelines from the China State Environmental Protection Administration (CSEPA) for HMs in soils (GB15618-2018) and vegetables (GB 2762 − 2017) were consulted as appropriate standards. The data were analyzed using two-way and one-way analysis of variance (ANOVA) to determine the effect of plantation base and species. Duncan’s multiple comparison tests were performed to determine the statistical significance of the differences between vegetable species. 3. Results 3.1. Levels of heavy metals in soil The accumulation of five HM elements in the soil and six vegetables from eight planting bases surrounding Lanzhou City occurred in varying degrees, and the ecological risk of HMs in the Chengguan and Huazhuang regions was always at lower levels, where the Dingyuan and Xigu regions were significantly higher than other regions, which were the largest recipients of industrial wastewater, urban sewage, domestic waste, and solid waste soil in the city and an important source of HM pollution. The soils in the eight vegetable bases were all alkalic because the soil pH values were higher than 8.0, with a mean of 8.35 and ranged from 8.10 to 8.66. The electrical conductivities of the soils in the eight planting-based treatments were low, range from 0.26 0.57. The mean HM concentrations (i.e., Zn, Cr, Pb, Cd and Cu) in the soils of eight different vegetable bases exceeded the natural background levels. In comparison, for soils, the HM levels were 1.1 to 3.0 times higher than the natural background levels. The concentrations of Zn, Cd, Cr, Cu, and Pb exceeded natural background levels by 1.05-, 3.00-, 1.17-, 1.18 and 1.32 times, respectively. The coefficient of variation (VC) indicated the degree of variation in the sampling sites, and the VC values for Zn, Cd, Cr, Cu, and Pb were 13.18%, 25.01%, 11.03%, 17.04, and 9.04, respectively. The mean HM content in soils followed the order: Cr > Zn ˃ Cu > Pb ˃ Cd. The Cr and Zn contents of soils in the eight planting bases were much higher than those of the other three metals. The Zn content was high in Chengguan district with 78.66 mg/kg while low in Anning district with 54.10 mg/kg. The Cr content was high in Dingyuan District, with a value of 78.43 mg/kg while low in Chengguan (55.03 mg/kg (Table 1 ). Table 1 The pH, EC (dS/m), organic matter (OM, %) 1.28–1.69 and the content (mg/kg) of HMs in farmland soils in eight planting bases surrounding the Lanzhou city in Gansu province, China Site pH EC OM Zn Cd Cr Cu Pb Anning 8.7 ± 1.2 0.31 ± 0.06 1.43 ± 0.08 54.10 ± 4.32 0.37 ± 0.07 60.80 ± 6.58 29.24 ± 3.22 22.27 ± 1.65 Xigu 8.2 ± 0.8 0.27 ± 0.04 1.38 ± 0.06 61.37 ± 5.39 0.43 ± 0.08 68.40 ± 8.35 40.46 ± 5.29 25.23 ± 3.26 Chengguan 8.4 ± 1.5 0.57 ± 0.09 1.95 ± 0.21 78.66 ± 6.84 0.25 ± 0.06 55.03 ± 6.39 27.90 ± 3.27 24.40 ± 1.55 Heping 8.6 ± 0.6 0.37 ± 0.03 1.42 ± 0.10 55.31 ± 4.37 0.35 ± 0.03 61.98 ± 5.29 33.14 ± 2.33 22.53 ± 1.68 Dingyuan 8.2 ± 1.3 0.26 ± 0.02 1.28 ± 0.09 67.48 ± 7.85 0.52 ± 0.04 78.43 ± 9.64 30.71 ± 2.45 25.57 ± 1.79 Zhonghe 8.1 ± 0.7 0.49 ± 0.06 1.87 ± 0.08 60.88 ± 8.24 0.34 ± 0.02 68.73 ± 8.78 29.75 ± 2.36 29.03 ± 2.04 Pingan 8.3 ± 0.5 0.41 ± 0.05 1.76 ± 0.15 60.28 ± 6.55 0.34 ± 0.02 66.68 ± 6.25 27.38 ± 3.15 24.87 ± 2.16 Huazhuang 8.5 ± 0.4 0.56 ± 0.06 1.96 ± 0.12 55.86 ± 4.35 0.25 ± 0.01 60.02 ± 5.34 22.69 ± 1.98 22.66 ± 1.22 Mean 8.36 0.41 1.63 61.74 0.36 65.01 30.16 24.57 Background value of heavy metal in soil a 58.74 0.12 55.66 25.68 18.56 Risk standard of heavy metal for soil (S i ) b 300.00 0.60 250.00 100.00 170.00 a Soil background values in Gansu province (Soil background values of Chinese elements 1990); b Soil environment quality: Risk control standard for soil contamination of agricultural land (GB15618-2018, Ministry of Environment Protection) The contents of Cr, Zn, Cu, Pb, and Cd in the soils of the eight sites were lower than the risk control standard for soil contamination of agricultural land (GB15618-2018), indicating that these heavy metals in the soils were safe. The Cd, Cr, and Pb contents were higher than the soil background values. For Cd, the accumulation of lettuce at the Dingyuan site exceeded the grade II national standard of China. The application of fertilizers and livestock manure can also lead to the accumulation of heavy metals in the soil and vegetables of agricultural bases in cities. Relevant research has also confirmed that the large and long-term application of organic fertilizers and phosphorus-containing fertilizers from livestock and poultry manure has led to a serious accumulation of HMs (Cupara et al. 2022 ). Greenhouse vegetables are commonly cultivated with heavy metal-containing pesticides, and films are added during the planting process, which may also contribute to the accumulation of HMs (Henry et al. 2018 ; Fan et al. 2017 ). At the same time, some studies have shown that vegetable plots are transformed from farmlands with a history of frequent use, which can leave a large amount of HM contaminants. In this study, we found that the HMs (Zn, Cr, Pb, Hg, and Cd) in the soil of the Anning region were greater than the background levels in the soil, and only Cd exceeded the grade II national standard of China. Except for the Anning, Heping, and Huazhuang sites, the Zn content in the other sites was higher than the soil background value, and the Cu content was higher than the soil background value, except for the Huazhuang site (Table 1 ). 3.2. Pollution assessment of heavy metals in soil The P n indexes of the eight vegetable bases showed lesser variations, and only the Xigu site exceeded the safety line (Class I); specifically, The P n indexes of the Dingyuan site were higher than 0.7 and lower than 1 (Class II), which resulted in slight pollution. The P n values ranged from 0.48 to 0.94, exposing two ranges from precaution to slight pollution, the P n of eight vegetable bases decreased in the following order: Dingyuan > Xigu > Anning > Heping > Zhonghe = Pingan > Chengguan > Huazhuang. The soil pollution levels in these vegetable bases indicate a certain degree of heavy metal pollution. Consequently, we assume that this might be due to unreasonable agricultural activities, such as the overuse of pesticides and chemical fertilizers, as well as the influence of the petrochemical industry located near these vegetable bases (Wang et al. 2021 ). The potential ecological risk indexes ( \(\:{\text{E}}_{\text{r}}^{\text{i}})\) of each HM (Zn, Cd, Cr, Cu, Pb) in the soils of eight vegetable bases and the comprehensive potential ecological risk index (RI) of multiple HMs were calculated, and the results indicated that Cd contributed to the majority of the ecological risk (Table 2 ). In Chengguan and Huazhuang sites, the \(\:{\text{E}}_{\text{r}}^{\text{i}}\) values for Cd both were 62.50, suggesting a moderate ecological risk, and in other six sites, the \(\:{\text{E}}_{\text{r}}^{\text{i}}\) values for Cd were 80≤ \(\:{\text{E}}_{\text{r}}^{\text{i}}\) <160, posing the considerable ecological risk. The \(\:{\text{E}}_{\text{r}}^{\text{i}}\) of Zn, Cr, Cu and Pb in all vegetable bases were much less than 40, all belonged to low ecological risk. For the five tested HMs, the single contributions to the total potential ecological risk (RI) followed the order of Cd > Pb > Cu > Cr > Zn. The RI of the total samples was low, based on the ecological risk index for multiple HMs (Table 2 ). Table 2 Ecological risk index ( \(\:{\text{E}}_{\text{r}}^{\text{i}})\) for single HM and RI for multiple HMs from farmland soils in eight planting bases surrounding the Lanzhou city in Gansu province, China Site \(\:{\text{E}}_{\text{r}}^{\text{i}}\) RI Zn Cd Cr Cu Pb Anning 0.92 ± 0.01 92.50 ± 9.65 2.18 ± 0.12 5.69 ± 0.46 6.00 ± 0.51 107.30 Xigu 1.04 ± 0.02 107.50 ± 13.45 2.46 ± 0.16 7.88 ± 0.51 6.80 ± 0.52 125.68 Chengguan 1.34 ± 0.03 62.50 ± 6.35 1.98 ± 0.15 5.43 ± 0.42 6.57 ± 0.60 77.82 Heping 0.94 ± 0.01 87.50 ± 5.26 2.23 ± 0.24 6.45 ± 0.41 6.07 ± 0.56 103.19 Dingyuan 1.15 ± 0.02 130.00 ± 12.24 2.82 ± 0.10 5.98 ± 0.48 6.89 ± 0.58 146.83 Zhonghe 1.04 ± 0.02 85.00 ± 8.25 2.47 ± 0.14 5.79 ± 0.50 7.82 ± 0.62 102.12 Pingan 1.03 ± 0.01 85.00 ± 7.29 2.40 ± 0.07 5.33 ± 0.56 6.70 ± 0.71 100.45 Huazhuang 0.95 ± 0.01 62.50 ± 7.11 2.16 ± 0.11 4.42 ± 0.61 6.10 ± 0.66 76.13 The negative I geo values of Zn and Cr indicated that the eight vegetable bases were free from Zn and Cr contamination. The I geo -Cu in all vegetable bases, except for the Xigu site, and I geo -Pb in all vegetable bases, except for the Zhonghe site, were less than zero. Additionally, the I geo -Cu at the Xigu site and I geo -Pb at the Zhonghe site were within the range of 0 < I geo ≤1, suggesting that the degrees of Cu and Pb pollution at these two sites were slightly to moderately polluted. The I geo -Cd performed larger spatial variation, the I geo -Cd values in Chengguan, Heping, Zhonghe, Pingan and Huazhuang sites were in 0 < I geo ≤1, indicating that the pollution degrees of Cd in these five sites were slightly to moderately polluted, and the I geo -Cd values in Anning, Xigu and Dingyuan sites were in 1 < I geo ≤2, indicating these two sites existed moderately polluted for Cd (Fig. 3 ). 3.3. Levels of heavy metals in vegetables Two-way ANOVA showed that the contents of Zn, Cd, Cr, and Cu were significantly affected by sites and vegetable species, and the interactions between sites and vegetables were not significant (Table 3 ). The Zn content of the vegetables varied significantly within species in each vegetable base (one-way ANOVA: F 5,25 =3.16, P < 0.05 for Anning; F 5,25 =3.34, P < 0.05 for Xigu; F 5,25 =2.95, P < 0.05, Chengguan; F 5,25 =7.58, P < 0.001 for Heping; F 5,25 =3.23, P < 0.05 for Dingyuan; F 5,25 =3.54, P < 0.05, Zhonghe; F 5,25 =6.65, P < 0.001 for Pinganu; F 5,25 =3.76, P < 0.05 for Huazhuang). At the Anning and Heping sites, the Zn content in lettuce was significantly higher than that in other vegetables, and the Zn content did not exhibit significant differences among the other five vegetables. At the Xigu site, the Zn contents in rape, scallion, and cucumber were not significantly different, and they were significantly higher than those in leek and lower than those in lettuce. At the Chengguan site, the Zn content in scallions was significantly higher than that in other vegetables, and the other five vegetables did not show significant differences. At the Dingyuan site, no significant differences were observed among rape, scallion, cucumber, and zucchini, which were significantly higher than lettuce and lower than leek. At the Zhonghe site, the highest Zn content was observed in cucumbers, and zucchini showed the lowest accumulation capacity. At the Pingan site, the Zn contents of lettuce, rapeseed, and leek did not show significant differences, and were significantly higher than those of the other three vegetables, with no significant differences observed. Among the scallions, cucumber and zucchini. In Huazhuang, the Zn content in cucumber was significantly higher than that in the other vegetables, and there was no significant difference among the other five vegetables (Fig. 4 ). Table 3 The analysis of variance for the effects of different site, vegetable and their interaction on HM accumulation in vegetables Metal Source of variation df F-value P Zn site 7 12.98 < 0.001 vegetable 5 7.98 < 0.001 site × vegetable 35 0.76 0.8346 Cd site 7 5.27 < 0.001 vegetable 5 4.66 < 0.001 site × vegetable 35 1.42 0.0663 Cr site 7 12.12 < 0.001 vegetable 5 5.20 < 0.001 site × vegetable 35 1.40 0.0748 Cu site 7 17.25 < 0.001 vegetable 5 6.72 < 0.001 site × vegetable 35 0.78 0.8073 Pb site 7 30.29 < 0.001 vegetable 5 0.50 0.7751 site × vegetable 35 1.70 < 0.05 The Cd content of vegetables was significantly different among vegetables on eight bases (One-way ANOVA: F 5,25 =4.47, P < 0.05 for Anning; F 5,25 =4.13, P < 0.05 for Xigu; F 5,25 =9.39, P < 0.001 for Chengguan; F 5,25 =4.03, P < 0.05 for Heping; F 5,25 =4.89, P < 0.05 for Dingyuan; F 5,25 =5.59, P < 0.001 for Zhonghe; F 5,25 =3.98, P < 0.05 for Pingan; F 5,25 =4.36, P < 0.05 for Huazhuang). In the Xigu and Heping sites, the Cd content in rape was significantly higher than that in other vegetables and did not differ significantly among the other five vegetables, whereas in the Pingan and Huazhuang sites, the opposite performance was observed. At the Anning site, the Cd contents of lettuce, leek, and cucumber were not significantly different, but were significantly higher than those of scallion and zucchini and lower than that of rape. At the Chengguan site, lettuce, leek, cucumber, and zucchini consistently showed lower Cd contents, and the Cd contents of rape and scallion were significantly higher than those of the other four vegetables. Only in Dingyuan site, the Cd content of lettuce exceeded the government standards from the China for HMs in vegetables (GB 2762 − 2017), and significantly higher than other five vegetables, there were significant difference among these five vegetables. At the Zhonghe site, the Cd contents of lettuce, rape, leek, scallion, and zucchini were not significantly different, but were significantly lower than those of cucumber (Fig. 5 ). There was a significant difference in Cr content among the eight vegetables at the Dingyuan site (One-way ANOVA: F 5,25 =4.59, P < 0.01), and no significant differences were observed among the other seven sites. The Cr contents of rape and scallion at the Xigu site, lettuce and scallion at the Zhonghe site, and rape in Pingan slightly exceeded the National Food Safety Standards for contaminant Limits in China (GB 2762 − 2017). More serious Cr pollution was found at the Dingyuan site; the Cr contents of lettuce, rape, scallion, and zucchini exceeded the standard, and leek and cucumber were relatively safe (Fig. 6 ). The Cu contents of the six vegetables in the eight vegetable bases did not show significant differences; lettuce and cucumber always accumulated Cu at most sites, and scallion always showed less Cu uptake (Fig. 7 ). There were significant difference for Pb contents among vegetables in seven bases (One-way ANOVA: F 5,25 =3.45, P < 0.05 for Anning; F 5,25 =4.56, P < 0.05 for Xigu; F 5,25 =3.29, P < 0.05 for Chengguan; F 5,25 =3.03, P < 0.05 for Dingyuan; F 5,25 =4.24, P < 0.01 for Zhonghe; F 5,25 =3.23, P < 0.05 for Pingan; F 5,25 =3.26, P < 0.05 for Huazhuang). At the Anning site, the Pb content in rape was significantly higher than that in other vegetables and did not show significant differences among the other five vegetables. At the Xigu site, the Pb content of rape, scallion, and cucumber was significantly higher than that of rape and lower than that of lettuce. At the Chengguan site, scallions showed the highest Pb content, and no significant difference was observed among the other five vegetables. There was a significant difference in the Pb content among the six vegetables at the Heping site. In Dingyuan site, the Pb content of leek exceeded the government standards from the China for HMs in vegetables (GB 2762 − 2017), and was significantly higher than other five vegetables, there were significant difference among these five vegetables. At the Zhonghe site, the Pb contents of scallions, cucumbers, and zucchini were not significantly different but were significantly higher than those of lettuce, rape, and leek. At the Huazhuang and Pingan sites, the Pb content of leek was significantly higher than that of the other five vegetables and slightly exceeded the standards (Fig. 8 ). HM contents in soils of the vegetable base in Lanzhou followed the order Cr > Zn > Cu > Pb > Cd. The detected sequences of the five metals were significantly affected by plantation base and species. From the linear model regression analysis, the remarkable significant positive relationships were concluded between metal accumulation of vegetables and soils for Zn in Allium tuberosum, Cucumis sativus, Cucurbita maxima , Cd in Lactuca sativa, Allium tuberosum, Cucumis sativus , Cr in Allium fistulosum, Cucurbita maxima , Cu in all vegetables except Cucurbita maxima , Pb in Lactuca sativa, Allium fistulosum . The concentrations of all HMs in the soil in this study were higher than the background values and accumulated significantly, but the contents of the vegetables were relatively low; only one leafy vegetable sample had a Cd content exceeding the national standard, indicating that the accumulation of HMs in vegetables was influenced by conditions other than the total amount of HMs in the soil. Studies have shown that many factors affect the uptake of HMs in vegetables, such as soil physicochemical characteristics, speciation distribution of HM in soil, biological effectiveness, vegetable varieties, planting management conditions, and spatial differences (Fan et al. 2017 ; Idrees et al. 2017 ; Shama et al. 2017; Henry et al. 2018 ). Therefore, when investigating HM accumulation in vegetables, more attention should be paid to the possible effects of factors other than HM in the soil. 3.4. The health risks of heavy metals in vegetables The target hazard quotients (THQ) and hazard index (HI) were applied to assess the human health risk of HMs from vegetable growth in the vegetable bases surrounding Lanzhou City, Gansu Province, China. There were some differences in the THQs because the HMs that contaminated the soils were different for the eight vegetable bases. The THQs of HMs for each vegetable from the Xigu, Dingyuan, Heping, and Zhonghe sites were always higher. All THQ values of HMs for the eight vegetable bases were less than 1, indicating no obvious health risk to the surrounding residents who took up HMs via an individual vegetable (Fig. 9 ). The HI values of Cu in all vegetable bases and Cr in Zhonghe, Dingyuan, and Xigu sites were more than 1, suggesting that all sites were likely to pose health risks for Cu and Cr from these three sites (Fig. 10 ). The hazard index (HI) has been approved as an important index for health risk assessment and is used to assess the health risks associated with the uptake of HM in food crops. In this study areas, it was as follows: Cu > Cr > Cd > Zn > Pb. The HIs of all of the HMs investigated in this study were < 1, except for Cu at all sites and Cr at the Zhonghe, Dingyuan, and Xigu sites. In the present study, we investigated the THQ indexes of not only non-essential metals but also essential metals. Different vegetable species always have different HM accumulation ability to HMs. It has been reported that Cd uptake in leafy vegetables is higher than that in non-leafy vegetables. In this study, no significant differences were found in the HM content of the edible parts of different vegetable types. Cucumber had higher concentrations and THQs of HMs, and may be classed as “high accumulators” for Cd. Lower THQs of HMs were found in scallions, which were classed as “low accumulators” (Lai et al. 2022 ). This suggests that the low accumulators were suitable for planting on heavy metal-polluted soil, whereas the high accumulators were unsuitable. The high concentration and the strong accumulation ability of HMs in leafy vegetables were possibly due to the leaves being the main parts of the vegetables used for photosynthesis and more metals flowing to the leaves by strong transpiration. However, Fruit vegetables accumulate more HMs in the edible part, which may be due to the longer growth period and longer accumulation time of HMs (Leblebici et al. 2020 ). Furthermore, atmospheric deposition may be one of the reasons for the metal uptake of leafy vegetables through leaf stomata (Chen et al. 2018 ). Both Cu and Zn are important nutrient elements for humans and are considered to pose much lower health risks than Pb, Cd, Hg, As, and Cr (Zhou et al. 2016 ; Deng et al. 2021 ; Nolos et al. 2022 ). Poor health can be caused by a lack of these required metal elements; however, excessive ingestion can also pose health risks. Currently, there are several methods for estimating the potential health risks of HMs from carcinogenic and non-carcinogenic effects. Non-cancer risk assessment is typically based on the THQ method, which is the ratio of the determined pollutant dose to the reference oral dose (Li et al. 2016 ). THQ values were associated with HM intake, exposure period, body weight, and reference oral dose. Vegetables are only a part of human diets, and in addition to vegetable consumption, consumption of rice, meat, fish, and tobacco also leads to the intake of large amounts of HMs (Qureshi et al. 2016 ; Rehman et al. 2018 ). Table 4 Bioconcentration factors (BCFs) of HMs for vegetables from eight vegetable bases surrounding Lanzhou city in Gansu province, China. Values with the same lowercase letters indicate no significant difference among vegetables for each HM, and values with capital letters indicate no significant difference among HMs for each vegetable at the 5% level of probability by Duncan’s multiple comparison test. Vegetable Zn Cd Cr Cu Pb F-value lettuce 0.0755Aa 0.0840Aa 0.0070A 0.2844B 0.0058A 79.8301*** rape 0.0726Aa 0.1081Aa 0.0073B 0.2733C 0.0063B 41.2892*** leek 0.0478Ab 0.0496Ac 0.0061B 0.2763C 0.0065B 249.7786*** scallion 0.0442Ab 0.0665Ab 0.0078B 0.2329C 0.0058B 141.0772*** cucumber 0.0715Aa 0.0699Ab 0.0060B 0.3035C 0.0068B 335.2488*** zucchini 0.0494Ab 0.0336Ac 0.0068B 0.2402C 0.0063B 273.8285*** F-value 5.1880** 13.3202*** 2.0736 1.7582 0.0952 3.5. The bioconcentration factor of heavy metals The BCF of each vegetable showed significant differences among the five HMs and among the six vegetables for Zn and Cd. All six vegetables showed consistent Cr, Cu, and Pb uptake capacities. The BCFs of Zn in lettuce, rape, and cucumber were significantly higher than those in the other three vegetables, and there were no significant differences in the BCFs of Zn among lettuce, rape, and cucumber. Leek, scallion, and zucchini were not significantly different for Zn levels. The BCFs of scallion and cucumber for Cd were significantly higher than those of leek and zucchini and lower than those of lettuce and rape. The BCFs of different HMs responded differently to the various vegetables. The BCFs of Cu in all vegetables were much higher than those of the other four HMs, and lettuce did not show significant differences in Zn, Cd, Cr, and Pb. The BCFs of rape, leek, scallion, cucumber and zucchini for Zn and Cd were higher than lower than Cr and Pb, there were significant differences between Zn and Cd, between Cr and Pb (Table 4 ). 3.6. Correlation analysis The physicochemical parameters EC and OM of soils from the eight vegetable bases showed a strong positive correlation (r = 0.96). There were extremely significant correlation at P < 0.001 between pH and Cr (r=-0.91), and Pb (r=-0.90), and a relatively significant correlation at P < 0.01 between pH and Cr (r=-0.70), and Pb (r=-0.72), and between EC and Cr (r=-0.84), and Cu (r=-0.89), and Cu (r=-0.88), and a significant correlation at P < 0.05 between OM and Cd (r=-0.78) and Cu (r = 0.69). RI and P n both showed significant correlations with EC, OM, and Cr and Cd contents (Fig. 11 ). A significant correlation between HM content in the soil and edible parts of the vegetables was observed according to the correlation analysis (P < 0.05) for five HMs and eight vegetables (Fig. 12 ). It was speculated that the HMs in vegetables may come from the soil, which may indicate that HMs in vegetables tend to accumulate in the edible parts but not in the roots or other parts. 5. Conclusions Cr and Zn in soils from eight vegetable bases were much higher than Cd, Pb, and Cu; there were different levels of heavy metal pollution, and the soils of the Dingyuan and Xigu sites exhibited higher levels of heavy metal pollution and were moderately polluted by Cd. The ecological risk followed the order of Cd > Pb > Cu > Cr > Zn for all vegetable bases. Cu and Zn in six vegetables from all eight plantation bases did not exceed the Chinese government standards for heavy metals in vegetables (GB 2762 − 2017). In the Xigu, Dingyuan, and Zhonghe sites, the contents of Cd, Pb, and Cu in vegetables exceeded this standard, and there were certain food safety risks. None of the vegetables from the Xigu, Dingyuan, Heping, or Zhonghe sites presented obvious health risks. It is likely to pose health risks for Cu and Cr from the Zhonghe, Dingyuan, and Xigu sites because of the excessive hazard index. The vegetables always exhibited different accumulation abilities for different heavy metals, and Cu and Cd were more easily accumulated in the edible parts of vegetables. The EC and OM of soils usually promote the uptake of heavy metals, and there are significant correlations between the content of heavy metals in soil and vegetables. The main heavy metal sources in vegetable bases are human activities and natural sources. Referential strategies and methods should be adopted to minimize the impacts of heavy metals on human health through the consumption and cultivation of vegetables in the surrounding vegetable bases of the city. Meanwhile, the calculation of the risk assessment model was based on the sampling data, which could lead to uncertainties owing to the lack of comprehensive data for soil and local vegetables in this research. Uncertainties may be caused by factors related to regional vegetable planting methods and land use modes, which would inevitably increase the uncertainty of the results. The parameters published in this research may also need to be updated to represent the current condition more accurately (Ullah et al., 2022 ). Although the abovementioned factors may bring some uncertainties, this investigation can still provide valuable information for better control of environmental risk and adjustment of vegetable planting modes by local governments and farmers. Declarations Supplementary Materials: No supplementary material is available Author Contributions: Hanru Ren: Visualization, Methodology, Resources, Supervision, Data processing. Jun Ren: Methodology, Resources, Formal analysis, Laboratory analyses. Ling Tao: Conceptualization, Investigation, Data processing, Formal analysis, Visualization, Supervision, Funding acquisition. Xuechang Ren: Conceptualization, Investigation. Funding: Gansu Provincial Education Department Industry Support Plan Project (2021CYZC-31); Science and Technology Plan Project of Gansu Provincial Science and Technology Department (22CX3GA076); Special Project of Gansu Science and Technology Commissioner (23CXGA0082); Gansu Key Research and Development programs (22YF7GA139)；the Innovation Fund Project of higher education in Gansu Province (2023A-036). Institutional Review Board Statement: Exclude this statement. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: All relevant data are within the paper. Acknowledgements: This research was funded by the Foundation of Key Laboratory of Yellow River Environment of Gansu Province (20JR2RA002, 21YRWEK007, 21YRWEG003), Industrial Support Program of Education Department of Gansu Province (2021CYZC-31), the Lanzhou Talent Innovation and Entrepreneurship Project (2021-RC-41), the National Training Programs of Innovation and Entrepreneurship for Undergraduates (202210753012). The “Innovative Star” Project for Outstanding Graduate Students in Gansu Province (2022CXZX-514). Conflicts of Interest: The authors declare no conflict of interest. References Agbenin, J.O.; Danko, M.; Welp, G. Soil and vegetable compositional relationships of eight potentially toxic metals in urban garden fields from northern Nigeria. J. Sci. Food Agric. 2009 , 89 , 49-54. Ahmad, J.U.;·Goni, M.A. Heavy metal contamination in water, soil, and vegetables of the industrial areas in Dhaka, Bangladesh. Environ. Monit. Assess. 2010 , 166 , 347-357. Alfaro, M.R.; Ugarte, O.M.; Lima, L.H.V.; Silva, J.R.; Silva, F.B.V.; Lins, S.A.S.; Nascimento, C.W.A. Risk assessment of heavy metals in soils and edible parts of vegetables grown on sites contaminated by an abandoned steel plant in Havana. Environ. Geochem. Health , 2022 , 44 , 43-56. Alturiqi, A.S.; Albedair, L.A.; Ali M.H.H. Health risk assessment of heavy metals in irrigation water, soil and vegetables from different farms in Riyadh district, Saudi Arabia. J. Elem. 2020 , 25(4) , 1269-1289. Chen, M.; Li, F.G.; Hu, L.W.; Yang, T.; Yang, Q.; Tao, M.X.; Deng, Y.W. Heavy metal pollution in topsoil and vegetables in the typical mining area near Gannan, Jiangxi Province, China. Enviro. Eng. Sci . 2019 , 36(10) , 1307-1314. Chen, Y.C.; Yuan, L.; Xu, C. The accumulation characteristics and potential health risks of heavy metals in vegetables from reclaimed area of China. Human Ecol. Risk Assess. 2018 , 4 , 949-960. Cupara, N., Nikolic, R.; Durovic, D.; Milasevic; I.; Medin, D.; Krivokapic, S. Heavy metal assessment in agricultural soils and vegetables in the vicinity of industrial pollutants in the Pljevlja municipality (Montenegro): ecological and health risk approach. Environ. Monit. Assess. 2022 , 194 , 819 Deng, B.; Li, W.Y.; Xu, W.H.; He, Z.M.; Tan, X. Correlation and the concentrations of Pb, Cd, Hg and As in vegetables and soils of Chongqing, China. Environ. Geochem. Health 2021 43 , 2357-2376. Eliku, T.; Leta, S. Heavy metals bioconcentration from soil to vegetables and appraisal of health risk in Koka and Wonji farms, Ethiopia. Environ. Sci. Pollut. Res. 2017 , 24 , 11807-11815. Fan, Y.; Li, H.; Xue, Z.J.; Zhang, Q.; Cheng, F.Q. Accumulation characteristics and potential risk of heavy metals in soil-vegetable system under greenhouse cultivation condition in Northern China. Ecol. Eng. 2017 , 102 , 367-373. Fang, S.B.; Hu, H.; Sun, W.C.; Pan, J. J. Spatial variations of heavy metals in the soils of vegetable-growing land along urban-rural gradient of Nanjing, China. Int. J. Environ. Res. Public Health 2011 , 8 , 1805-1816. Gaurav, V.K.; Kumar, D.; Sharma, C. Assessment of metal accumulation in the vegetables and associated health risk in the upper-most Ganga-Yamuna Doab Region, India. Am. J. Plant Sci. 2018 , 9 , 2347-2358. Gebeyehu, H.R.; Bayissa, L.D. Levels of heavy metals in soil and vegetables and associated health risks in Mojoarea, Ethiopia. PLoSONE , 2020 , 15(1) : e0227883 Gupta, N.; Yadav, K.K.; Kumar, V.; Krishnan, S. Kumar, S.; Nejad, Z.D.;Khan, M.A.M.; Alam, J. Evaluating heavy metals contamination in soil and vegetables in the region of North India: Levels, transfer and potential human health risk analysis Environmental Toxicology and Pharmacology , 2021 , 82 , 103563 Hakanson, L. An ecological risk index for aquatic pollution control. A sedimentological approach. Water Res. 1980 , 14 , 975-1001. Henry, M.U.; Ogenyi, R.A.; Henry, U.I.; Dogun, O. Assessment of heavy metal concentration in water, soil and vegetable in ex-mining pond, Jos South L.G.A Plateau State, Nigeria. Int. J. of Sci. Res. Public. 2018 , 8(8) , 840-845. Idrees, M.; Rehman, Z.U.; Bibi, S.; Shan, F.; Gulab, H.; Ali, L.; Mabood, F.; Multivariate analysis of the heavy metal concentrations in the vegetable and soil samples-acase study from district Ｃharsadda and district Mardan. Pak. J. Bot. 2017 , 49(3) , 1167-1171. Jalali, M.; Meyari, J.M. Assessment of the health risks of heavy metals in soils and vegetables from greenhouse production systems in Iran. Int. J. Phytoremediat. 2020 , 22(8) , 834-848. Khan, M.N.; Aslam, M.A.; Muhsinah, A.B.; Uddin, J. Heavy metals in vegetables: screening health risks of irrigation with wastewater in Peri-Urban areas of Bhakkar, Pakistan. Toxics 2023a , 11(5) , 460. Khan, M.N.; Aslam, M.A.; Zada, I.; Albekairi, T.H. Statistical analysis and health risk assessment: vegetables irrigated with wastewater in Kirri Shamozai, Pakistan. Toxics 2023b , 11(11) , 899 Lai, L.; Li, B.; Li, Z.R.; He, Y.M.; Hu, W.Y.; Zu, Y.Q.; Zhan, F.D. Pollution and health risk assessment of heavy metals in farmlands and vegetables surrounding a lead-zinc mine in Yunnan province, China. Soil Sediment Contam. 2022 , 31 , 483-497. Leblebici, Z.; Kar, M.; Basaran, L. Assessment of the heavy metal accumulation of various green vegetables grown in Nevsehir and their risks human health. Environ. Monit. Assess. 2020 , 192 , 483. Li, B.; Wang, Y.H.; Jiang, Y.; Li, G.C.; Cui, J.H.; Wang, Y.; Zhang, H.; Wang, S.C.; Xu, S.; Wang, R.Z. The accumulation and health risk of heavy metals in vegetables around a zinc smelter in northeastern China. Environ. Sci. Pollut. Res. 2016 , 23 , 25114-25126. Li, H.X.; Rehman, A.; Rahman, S.; Li, K.D.; Yang, T.R.; Akuetteh, P.; Khalid, M. Biosynthesized zinc oxide nanoparticles modulate the phytoremediation potential of Pennisetum giganteum and its rhizocompartments associated microbial community structure. J. Clean. Prod. 2024 , 434 , 140346. Minhaz, A.; Masaru, M.; Kiyoshi, K. Heavy metal contamination of irrigation water, soil, and vegetable in a multi-industry district of Bangladesh. Int. J. Environ. Res. 2018 , 12 , 531-542. Moghaddam, V.K.; Latifi, P.; Darrudi, R.; Askari, S.G.; Mohammadi, A.A.; Marufi, N.; Javan, S. Heavy metal contaminated soil, water, and vegetables in northeastern Iran: potential health risk factors. J. Environ. Health Sci . 2022 , 20 , 65-77. Nolos, R.C.; Agarin, C.J.M.; Domino, M.Y.R.; Bonifacio, P.B.; Chan, E.B.; Mascarenas, D.R.; Senoro, D.B. Health risks due to metal concentrations in soil and vegetables from the six municipalities of the Island province in the Philippines. Int. J. Environ. Res. Public. Health. 2022 , 19 , 1578. Ogbonna, P.C.; Odukaesieme, C.; Silva, J.A.T. Distribution of heavy metals in soil and accumulation in plants at an agricultural area of Umudike, Nigeria. Chem. Ecol . 2013 , 7 , 595-603. Osma, E.; Serin, M.; Leblebici, Z.; Aksoy, A. Assessment of heavy metal accumulations (Cd, Cr, Cu, Ni, Pb, and Zn) in vegetables and soils. Pol. J. Environ. Stud. 2013 , 22(5) , 1449-1455. Qureshi, A.S.; Hussain, M.I.; Ismall, S.; Khan, Q.M. Evaluating heavy metal accumulation and potential health risks in vegetables irrigated with treated wastewater. Chemosphere , 2016 , 163 , 54-61. Rehman, Z.U.; Khan, S.; Shah, M.T.; Brusseau, M.L., Khan, S.A.; Mainhagu, J. Transfer of heavy metals from soils to vegetables and associated human health risks at selected sites in Pakistan. Pedosphere 2018 , 28(4) , 666-679. Sawut, R.; Kasim, N.; Maihemuti, B.; Hu, L.; Abliz, A.; Abdujappar, A.; Kurban, M. Pollution characteristics and health risk assessment of heavy metals in the vegetable bases of northwest China. Sci. Total Environ. 2018 , 642 , 864-878. Swartjes, F.A.; Versluijs, K.W., Otte, P.F. A tiered approach for the human health risk assessment for consumption of vegetables from with cadmium-contaminated land in urban areas. Environ. Res. , 2013 , 126 , 223-231. Ullah, H.; Khaliq, M.; Ullah, N.; Iqbal, A.; Fozia; Ullah, I. Health risk assessment and multivariate statistical analysis of heavy metals in vegetables of Khyber Pakhtunkhwa region, Pakistan. Biol. Trace Elem. Res. 2022 , 200 , 3023-3038. Wang, Y.H.; Zhan,M.G.; Zhu, H.X.; Guo, S.J.; Wang, W.S. Xue, B.M. Distribution and accumulation of metals in soils and plant from a lead-zinc mine land in Guangxi, South China. Bull. Environ. Contam. Toxicol. 2012 , 88 , 198-203. Wang, Z.; Bao, J.G.; Wang, T.; Moryani, H.T.; Kang, W., Zheng, J., Zhan, C.L. & Xiao, W.S. Hazardous heavy metals accumulation and health risk assessment of different vegetable species in contaminated soils from a typical mining city, central China. Int. J. Environ. Res. Public Health. 2021 , 18 , 2617 Xu, X.; Shi, M.Y.; Yu, X.M., Liu, M.D. Heavy metal pollution and health risk assessment of vegetable-soil systems of facilities irrigated with wastewater in Northern China. Int. J. Environ. Res. Public Health. 2022 , 19 , 9835. Yu, H.L., Shen, X.F., Chen, H.Y., Dong, H.R., Zhang, L.J., Yuan, T., Zhang, D., Shang, X.D., Tan, Q., Liu, J.Y., Lv, B.B. & Li, Y. Analysis of heavy metal content in Lentinula edodes and the main influencing factors. Food Control 2021 , 130 , 108198 Zeng, L.P.; Zhou, F.; Zhang, X.C.; Qin, J.H.; Li, H.S. Distribution of heavy metals in soils and vegetables and health risk assessment in the vicinity of three contaminated sites in Guangdong Province, China. Human Ecol. Risk Assess. 2018 , 7 , 1901-1915. Zhou, H., Yang, W.T., Zhou, X., Liu, L., Gu, J.F., Wang, W.L., Zou, J.L., Tian, T., Peng, P.Q., Liao, B.H. Accumulation of heavy metals in vegetable species planted in contaminated soils and the health risk assessment. Int. J. Environ. Res. Public Health. 2016 , 13 , 289. Khan, M.N., Aslam, M.A., Muhsinah, A.B., Uddin, J. Heavy metals in vegetables: Screening health risks of irrigation with wastewater in Peri-Urban areas of Bhakkar, Pakistan. Toxics. 2023 , 11 , 460. Khan, M.N., Aslam, M.A., Zada, I., Albekairi, T.H. Statistical analysis and health risk assessment: vegetables irrigated with wastewater in Kirri Shamozai, Pakistan. Toxics. 2023 , 11 , 899. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 05 Sep, 2024 Submission checks completed at journal 03 Sep, 2024 First submitted to journal 02 Sep, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5021647","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":350212555,"identity":"e113f945-a826-4225-b07b-5bd1b07975ea","order_by":0,"name":"Han-ru Ren","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsklEQVRIiWNgGAWjYHACNjDJz8x8+AFpWiTb2dIMSNNicJ5HQYIo9ebtvcce/NxxL3HzYR4GA4Yam2iCWmTOnEs37D1TnLjtMO+BBwzH0nIbCGmRkMgxk+BtSwBq4UswYGw4TIQW+Tdmkn+BWjY38xhIEKdFgsdMGmTLBmaitfDkmEnLtiUYzzgMDOQEovzCfsZM8m1bgmx//+HDDz7U2BDWggoSSFM+CkbBKBgFowAXAAA90jnkMgcB4QAAAABJRU5ErkJggg==","orcid":"","institution":"Gansu Hanxing Environmental Protection Co., Ltd","correspondingAuthor":true,"prefix":"","firstName":"Han-ru","middleName":"","lastName":"Ren","suffix":""},{"id":350212556,"identity":"08b21541-e84b-4e05-b8a1-36f6210ad10e","order_by":1,"name":"Jun Ren","email":"","orcid":"","institution":"Gansu Hanxing Environmental Protection Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Ren","suffix":""},{"id":350212557,"identity":"84a72771-15dd-4c95-988d-c12fb08ac6ba","order_by":2,"name":"Ling Tao","email":"","orcid":"","institution":"Gansu Hanxing Environmental Protection Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Ling","middleName":"","lastName":"Tao","suffix":""},{"id":350212559,"identity":"a5437822-932a-4247-a5ee-8c0a77575180","order_by":3,"name":"Xue-chang Ren","email":"","orcid":"","institution":"Lanzhou Jiaotong University","correspondingAuthor":false,"prefix":"","firstName":"Xue-chang","middleName":"","lastName":"Ren","suffix":""}],"badges":[],"createdAt":"2024-09-03 03:45:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5021647/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5021647/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":65888688,"identity":"5ff9f950-0725-4b79-8d54-7fa3c30e58ca","added_by":"auto","created_at":"2024-10-04 04:34:49","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":100640,"visible":true,"origin":"","legend":"\u003cp\u003eLocation map of vegetable bases (sampling sites) surrounding the Lanzhou city in Gansu province, China\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5021647/v1/543e342c1ab740d02c83ce2f.jpg"},{"id":65888690,"identity":"650997a8-b052-40ec-a8fd-3a67c3e2cb27","added_by":"auto","created_at":"2024-10-04 04:34:49","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":19322,"visible":true,"origin":"","legend":"\u003cp\u003ePollution index (P\u003csub\u003en\u003c/sub\u003e) for HMs in farmland soils in eight planting bases surrounding the Lanzhou city in Gansu province, China\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5021647/v1/939a060e794c3cb5fb77a99a.jpg"},{"id":65888691,"identity":"08a3329b-d9c6-4656-929e-2078d70bf53e","added_by":"auto","created_at":"2024-10-04 04:34:49","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":26748,"visible":true,"origin":"","legend":"\u003cp\u003eThe geo-accumulation index (I\u003csub\u003egeo\u003c/sub\u003e) for HMs from farmland soils in eight planting bases surrounding the Lanzhou city in Gansu province, China\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5021647/v1/0a592e8b1d112d423cb49a96.jpg"},{"id":65888539,"identity":"90a108bd-4d90-41e2-8dcd-7a40d49dadfc","added_by":"auto","created_at":"2024-10-04 04:26:49","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":35469,"visible":true,"origin":"","legend":"\u003cp\u003eZn concentration (mg/kg) of vegetables in eight planting bases surrounding the Lanzhou city in Gansu province, China\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5021647/v1/a5cd7be3e51f56c4f4105354.jpg"},{"id":65888550,"identity":"39257230-309c-4c27-b711-8e19ef437241","added_by":"auto","created_at":"2024-10-04 04:26:50","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":33478,"visible":true,"origin":"","legend":"\u003cp\u003eCd concentration (mg/kg) of vegetables in eight planting bases surrounding the Lanzhou city in Gansu province, China\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5021647/v1/0e922248f42c4adff0388c84.jpg"},{"id":65888545,"identity":"c0ea09a2-4467-4ea3-8f81-71bad66ff052","added_by":"auto","created_at":"2024-10-04 04:26:49","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":37773,"visible":true,"origin":"","legend":"\u003cp\u003eCr concentration (mg/kg) of vegetables in eight planting basessurrounding the Lanzhou city in Gansu province, China\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5021647/v1/ce8f49f1f1dd0a6a3cbc88a1.jpg"},{"id":65889503,"identity":"8b073fae-81ba-4a70-b5a8-acda5cd21e8d","added_by":"auto","created_at":"2024-10-04 04:42:49","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":35067,"visible":true,"origin":"","legend":"\u003cp\u003eCu concentration (mg/kg) of vegetables in eight planting basessurrounding the Lanzhou city in Gansu province, China\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5021647/v1/5fb207e0b313976544f75161.jpg"},{"id":65888547,"identity":"db7f0600-eb88-4c87-aa07-1a791f156bd6","added_by":"auto","created_at":"2024-10-04 04:26:49","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":38123,"visible":true,"origin":"","legend":"\u003cp\u003ePb concentration (mg/kg) of vegetables in eight planting bases surrounding the Lanzhou city in Gansu province, China\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5021647/v1/95db6d934fe2a41920e71320.jpg"},{"id":65888541,"identity":"75aa4a2b-8351-49ef-ab40-9e9c2a46505d","added_by":"auto","created_at":"2024-10-04 04:26:49","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":25923,"visible":true,"origin":"","legend":"\u003cp\u003eTarget hazard quotients (THQ) of different vegetables in eight planting bases surrounding the Lanzhou city in Gansu province, China\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5021647/v1/b56b6f1948fb3d755c077e6b.jpg"},{"id":65888542,"identity":"117ce383-4ff3-486c-b496-b512cba629bf","added_by":"auto","created_at":"2024-10-04 04:26:49","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":23878,"visible":true,"origin":"","legend":"\u003cp\u003eHazard index (HI) of vegetables in eight planting bases surrounding the Lanzhou city in Gansu province, China\u003c/p\u003e","description":"","filename":"10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5021647/v1/4d3f74cfd0c0f3baf496d581.jpg"},{"id":65888548,"identity":"2e1d88d0-baa4-4f18-a426-10a9d251af52","added_by":"auto","created_at":"2024-10-04 04:26:49","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":31255,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation plot of P\u003csub\u003en\u003c/sub\u003e, RI, physicochemical properties and HMs of soils in eight vegetable bases surrounding the Lanzhou city in Gansu province, China\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5021647/v1/2b46db123ff1111f569b022a.jpg"},{"id":65888549,"identity":"6aecaa47-5b7e-4b20-a4f9-cccef77f45e2","added_by":"auto","created_at":"2024-10-04 04:26:49","extension":"jpg","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":68551,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between the contents of HMs in the vegetables with that in the soils in eight vegetable bases surrounding the Lanzhou city in Gansu province, China\u003c/p\u003e","description":"","filename":"12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5021647/v1/a819a6a2f26d3d6e59df227c.jpg"},{"id":65889707,"identity":"37d6904e-dea1-44ca-b471-63b4fd23894d","added_by":"auto","created_at":"2024-10-04 04:50:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1376448,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5021647/v1/133e456a-5ec4-47bb-b575-2cc0cf751ef3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pollution Evaluation in Soils and Health Risk in Vegetables of Heavy Metals in Surrounding Lanzhou City in Gansu Province, China","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe main sources of heavy metals in the atmosphere, hydrosphere, and biota are soil (Ahmad \u0026amp; Goni 2010; Minhaz et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Alturiqi et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and HM pollution and accumulation in the ecosystem pose serious problems worldwide. Heavy metal (HM) contamination of water, soil, and crops is a severe environmental problem that has attracted worldwide attention. Agricultural soils are prone to contamination with HMs from atmospheric deposition and various anthropogenic activities such as uncontrolled discharge from industrial and urban waste materials, sewage sludge, wastewater irrigation, and excessive chemical fertilizers and pesticides (Chen et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Jalali \u0026amp; Meyari \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Excessive HMs in soil always cause potential threats to the environment and food safety, and have damaging effects on human and animal health (Osma et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Swartjes et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Zeng et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Gebeyehu \u0026amp; Bayissa \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lai et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Moghaddam et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Nolos et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Recently, the pollution problem in agricultural soils has begun to draw the attention of many scientists and countries. Thus, studying HM contamination of soil, conducting risk assessments, and identifying pollution sources can provide evidence for relevant departments to develop approaches to control pollution. Most HMs do not undergo microbial or chemical degradation, which poses a significant threat to the environment and food safety. HMs can be harmful because of their potential to accumulate in different body parts of human beings and have adverse health effects, even at low concentrations (Khan et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eVegetables are important edible crops and an essential part of the human diet. They are rich in nutrients required for human health and are an important source of carbohydrates, vitamins, minerals, and fiber. HMs in soils can be readily taken up by vegetable roots and can accumulate at high levels in the edible parts of vegetables, even at low levels in soil (Gaurav et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The uptake and bioaccumulation of HMs in vegetables are influenced by a number of factors, such as climate, atmospheric deposition, the concentrations of HMs in soil, the physicochemical properties of the soil on which the vegetables are grown, and the degree of maturity of the plants at the time of harvest (Zhou et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Leblebici et al, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Gupta et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Many phosphate rocks contain HMs such as Pb and Cd, and high application rates of phosphorus (P) fertilizer may not only increase soil P but also lead to the accumulation of metals above the maximum limited values (Ogbonna et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Xu et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe vegetable planting bases are on the outskirts of Lanzhou city, which is the principal vegetable production site for people living in Lanzhou and nearby. However, HMs accumulate in soils and vegetables because of the excessive use of chemical and organic fertilizers, pesticides, and growth-regulating agents. To date, the HM content of agricultural soil in the vegetable plots of Lanzhou and its pollution problem have been studied very little, and there has been no systematic investigation of HMs in soil and vegetables, as well as the accumulation and transfer characteristics of HMs in these districts (Khan et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Khan et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As HMs in soil have a long residence time and are potentially dangerous, it is very important to study the condition of HMs accumulation in soil and vegetables (Agbenin et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Fang et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Eliku \u0026amp; Leta \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Chen et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Deng et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It is also vital to pay attention to food safety, which will bring about potential adverse effects on human beings through vegetables polluted by HMs (Sawut et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Alfaro et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, field investigation and systematic sampling were carried out for HMs, including Zn, Cd, Cr, Cu, and Pb, in soil and vegetables in the vicinity of Lanzhou. The aims of this study were: 1) to detect the contents of five metals in soil and six main species of vegetables, and to examine the relationship between them; 2) to assess the bioaccumulation factor of heavy metals from soil to vegetables; 3) to investigate the relationship and difference between the metals and the species of vegetables; and 4) to assess the risk of HMs in vegetables and soils in eight planting bases surrounding Lanzhou City in Gansu Province, China. The results can provide a scientific basis for harmless cultivation and a more scientific method for the risk assessment of HM hazards in vegetables by using a comprehensive risk index to jointly evaluate the impact of HMs in soil and vegetables on human health.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1. Study area\u003c/h2\u003e\n \u003cp\u003eEight vegetable planting bases are located in the vicinity of Lanzhou city in Gansu province, China, at longitudes of 103\u0026deg;35ʹ\u0026ndash;103\u0026deg;55ʹ east and latitudes of 36\u0026deg;00ʹ\u0026ndash;36\u0026deg;08ʹ north. These planting bases are situated in the upper reaches of the Yellow River and are named Anning, Xigu, Chengguan, Heping, Dingyuan, Zhonghe, Pingan, and Huazhuang (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The climate is subtropical monsoon, with an average annual temperature of 10.3\u0026deg;C, average annual precipitation of 327.8 mm and inadequate rainfall. The farmland is irrigated with the Yellow River water. The four distinct seasons and superior water heat conditions were conducive to crop growth.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2. Vegetables and soils sampling\u003c/h2\u003e\n \u003cp\u003eEight sampling sites were randomly selected in the vicinity of Lanzhou city, each sampling site was recorded by using global position system (GPS) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e), six vegetables and corresponding soil samples in each site were collected from April to October 2021, each sampling was carried out with six replicates. Soil samples were collected from the surface layer (0\u0026ndash;20 cm), air-dried and disaggregated. The identifiable stones and plant debris were removed and the samples were passed through 2 mm mesh sieve. To determine HM contents, a representative subsample of every soil sample was finely ground with a porcelain mortar, passed through 0.15 mm mesh sieve, and stored in closed plastic containers.\u003c/p\u003e\n \u003cp\u003eThe most common vegetables from the soil sampling sites were selected for the analysis. These included six different vegetable samples locally grown and consumed by the population: lettuce (\u003cem\u003eLactuca sativa\u003c/em\u003e L.), rape (\u003cem\u003eBrassica campestris\u003c/em\u003e L.), leek (\u003cem\u003eAllium tuberosum\u003c/em\u003e Rottl. ex Spreng), scallion (\u003cem\u003eAllium fistulosum\u003c/em\u003e L.) cucumber (\u003cem\u003eCucumis sativus\u003c/em\u003e L.) and zucchini (\u003cem\u003eCucurbita maxima\u003c/em\u003e Duch. ex Lam.). The edible parts of the vegetable samples were first lightly washed with tap water to remove surface dust, then washed with deionized water, dried with filter paper, weighed, dehydrated in an oven at 105\u0026deg;C for 2 h, and finally stored at 75\u0026deg;C for 48 h.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3. Analysis of samples\u003c/h2\u003e\n \u003cp\u003eThe pH and electrical conductivity (EC) of the soil samples were determined using a soil/water slurry (1:5 w/v). The organic matter (OM) of the soil was measured using the K\u003csub\u003e2\u003c/sub\u003eCr\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e7\u003c/sub\u003e volumetric method in an oil bath. Soil samples were digested with concentrated nitric acid (HNO\u003csub\u003e3\u003c/sub\u003e), hydrofluoric acid (HF), hydrochloric acid (HCl), and perchloric acid (HClO\u003csub\u003e4\u003c/sub\u003e). The plant samples were digested with concentrated HNO\u003csub\u003e3\u003c/sub\u003e. All containers were soaked at least 24h with 2% nitric acid before use. To ensure the accuracy of the analysis, each sample was subjected to \u0026amp;, and the mean was used as the final determination of the metal concentration. The Zn, Cd, Cr, Cu, and Pb contents were determined using inductively coupled plasma atomic emission spectroscopy (ICP-AES).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4. Evaluation of heavy metal pollution in soil\u003c/h2\u003e\n \u003cp\u003eThe pollution levels of single and comprehensive HMs in soil were assessed using single-factor (P\u003csub\u003ei\u003c/sub\u003e) and Nemerow\u0026rsquo;s synthetic pollution index (P\u003csub\u003en\u003c/sub\u003e). These indices were computed using the following equations (Sawut et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Yu et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Where P\u003csub\u003ei\u003c/sub\u003e is the single-factor index, C\u003csub\u003ei\u003c/sub\u003e is the concentration of each HM, and S\u003csub\u003ei\u003c/sub\u003e is the standard value for each HM (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). P\u003csub\u003eimax\u003c/sub\u003e is the maximum of single-factor index, and P\u003csub\u003en\u003c/sub\u003e is classified as safety (P\u003csub\u003en\u003c/sub\u003e\u0026le;0.7, Class I), precaution (0.7\u0026thinsp;\u0026lt;\u0026thinsp;P\u003csub\u003en\u003c/sub\u003e\u0026le;1.0, Class II), slightly polluted (1.0\u0026thinsp;\u0026lt;\u0026thinsp;P\u003csub\u003en\u003c/sub\u003e\u0026le;2.0, Class III), moderately polluted (2.0\u0026thinsp;\u0026lt;\u0026thinsp;P\u003csub\u003en\u003c/sub\u003e\u0026le;3.0, Class IV), and seriously polluted (P\u003csub\u003en\u003c/sub\u003e\u0026gt;3.0, Class V).\u003c/p\u003e\n \u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\:{\\text{P}}_{\\text{i}}={\\text{C}}_{\\text{i}}/{\\text{S}}_{\\text{i}}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e$$\\:{\\text{P}}_{\\text{n}}=\\sqrt{({\\text{P}}_{\\text{i}\\text{m}\\text{a}\\text{x}}^{2}+{\\stackrel{-}{\\text{P}}}^{2})/2}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eThe ecological risk index (RI), which comprehensively considers HMs content, environmental influence, and biotoxicity (Hakanson \u003cspan class=\"CitationRef\"\u003e1980\u003c/span\u003e), was used to evaluate the risk of multiple HMs from soils to assess HM pollution levels. The RI is computed by following equations, where \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e represents the potential ecological risk index of each HM, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{C}}_{\\text{s}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e is the concentration of each HM in soil, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{C}}_{\\text{b}}^{\\text{i}}\\:\\)\u003c/span\u003e\u003c/span\u003eis the background value of HM in soil in this region, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{T}}_{\\text{r}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e is the toxic response coefficients and the values of Cu, Cr, Pb, Cd, and Zn are 5, 2, 5, 30 and 1, respectively. The RI classifications were low risk (RI\u0026thinsp;\u0026lt;\u0026thinsp;150), moderate risk (150\u0026thinsp;\u0026le;\u0026thinsp;RI\u0026thinsp;\u0026lt;\u0026thinsp;300), considerable risk (300\u0026thinsp;\u0026le;\u0026thinsp;RI\u0026thinsp;\u0026lt;\u0026thinsp;600), and high risk (RI\u0026thinsp;\u0026ge;\u0026thinsp;600). The risk degree of single HM (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e) is low ecological risk (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e\u0026lt;40), moderate ecological risk (40\u0026le;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e\u0026lt;80), considerable ecological risk (80\u0026le;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e\u0026lt;160), high ecological risk (160\u0026le;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e\u0026lt;320), and very high ecological risk (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e\u0026ge;320).\u003c/p\u003e\n \u003cdiv id=\"Equc\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"113\" height=\"77\"\u003e\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eThe geo-accumulation index (I\u003csub\u003egeo\u003c/sub\u003e) is usually applied to assess the pollution level of HMs in soil and is calculated using the following equation (Wang et al., \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e), where K is introduced as a constant 1.5 to minimize the possible influence of background values due to geogenic variation. The pollution degrees of I\u003csub\u003egeo\u003c/sub\u003e was classified as unpolluted (I\u003csub\u003egeo\u003c/sub\u003e\u0026le;0), slightly to moderately polluted (0\u0026thinsp;\u0026lt;\u0026thinsp;I\u003csub\u003egeo\u003c/sub\u003e\u0026le;1), moderately polluted (1\u0026thinsp;\u0026lt;\u0026thinsp;I\u003csub\u003egeo\u003c/sub\u003e\u0026le;2), moderately to heavily polluted (2\u0026thinsp;\u0026lt;\u0026thinsp;I\u003csub\u003egeo\u003c/sub\u003e\u0026le;3), heavily polluted (3\u0026thinsp;\u0026lt;\u0026thinsp;I\u003csub\u003egeo\u003c/sub\u003e\u0026le;4), heavily to extremely polluted (4\u0026thinsp;\u0026lt;\u0026thinsp;I\u003csub\u003egeo\u003c/sub\u003e\u0026le;5), and extremely polluted (I\u003csub\u003egeo\u003c/sub\u003e\u0026gt;5).\u003c/p\u003e\n \u003cdiv id=\"Eque\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Eque\" name=\"EquationSource\"\u003e$$\\:{\\text{I}}_{\\text{g}\\text{e}\\text{o}}={\\text{l}\\text{o}\\text{g}}_{2}({\\text{C}}_{\\text{s}}^{\\text{i}}/{(\\text{K}\\times\\:\\text{C}}_{\\text{b}}^{\\text{i}}))$$\u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5. Health risk assessment of heavy metals for vegetable\u003c/h2\u003e\n \u003cp\u003eThe health risk of HMs in vegetables can be assessed by the target hazard quotients (THQ) and hazard index (HI), which were proposed by the US Environmental Protection Agency (USEPA 2000). The THQ\u003csub\u003eij\u003c/sub\u003e was calculated using Eq. 6 to assess the non-carcinogenic risks of vegetable i HM and j, and HI\u003csub\u003ei\u003c/sub\u003e was computed to estimate the potential risk of i HMs for all vegetables using Eq. 7 (Alfaro et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Where C\u003csub\u003eij\u003c/sub\u003e is the concentration of HM in j vegetables (mg/kg, fresh weight), IR is the ratio of vegetable ingestion (kg/day) for lettuce (0.09), rape (0.08), leek (0.06), scallion (0.03), cucumber (0.12), and zucchini (0.09) (Swartjes et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e); EF is exposure frequency (365 d/a); ED is exposure duration (76.4 years, life expectancy in China according to World Health Statistics 2018); BW represents the average of body weight (70 kg); AT represents the average exposure time for non-carcinogenic effects (assuming 76.4 years, 365 days a year); RfD is the daily reference dose of HMs (mg/kg\u0026middot;d), the values of RfD for Cu, Cr, Cd, Zn and Pb were 0.04, 0.003, 0.001, 0.3 and 0.0035, respectively (Wang et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). If the value of THQ or HI is \u0026le;\u0026thinsp;1.0, there is no obvious health risk to residents; on the contrary, non-carcinogenic risks are likely to occur when THQ or HI is \u0026gt;\u0026thinsp;1.0, and the health risk increases with an increase in THQ or HI.\u003c/p\u003e\n \u003cdiv id=\"Equf\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equf\" name=\"EquationSource\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"185\" height=\"96\"\u003e\u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Equg\" class=\"Equation\"\u003e\u003cbr\u003e\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.6. Bioconcentration factors for heavy metals (BCF)\u003c/h2\u003e\n \u003cp\u003eThe bioconcentration factor (BCF) was used to evaluate the potential for HM accumulation in vegetables related to HM concentrations in soils. BCF was calculated using the following equation (Alfaro et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), Where C\u003csub\u003evegetable\u003c/sub\u003e is the HM content in vegetables and C\u003csub\u003esoil\u003c/sub\u003e is the HM concentration in the soil.\u003c/p\u003e\n \u003cp\u003eBCF\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\frac{{\\text{C}}_{\\text{v}\\text{e}\\text{g}\\text{e}\\text{t}\\text{a}\\text{b}\\text{l}\\text{e}}}{{\\text{C}}_{\\text{s}\\text{o}\\text{i}\\text{l}}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e2.7. Data processing and analyses\u003c/h2\u003e\n \u003cp\u003eStatistical analyses were performed using STATISTICA 7.0. Summary statistics such as mean, standard deviation, minimum and maximum concentrations, median, and skewness were obtained to characterize soil properties and HM contents. To assess contamination status, Government Standards or guidelines from the China State Environmental Protection Administration (CSEPA) for HMs in soils (GB15618-2018) and vegetables (GB 2762\u0026thinsp;\u0026minus;\u0026thinsp;2017) were consulted as appropriate standards. The data were analyzed using two-way and one-way analysis of variance (ANOVA) to determine the effect of plantation base and species. Duncan\u0026rsquo;s multiple comparison tests were performed to determine the statistical significance of the differences between vegetable species.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Levels of heavy metals in soil\u003c/h2\u003e \u003cp\u003eThe accumulation of five HM elements in the soil and six vegetables from eight planting bases surrounding Lanzhou City occurred in varying degrees, and the ecological risk of HMs in the Chengguan and Huazhuang regions was always at lower levels, where the Dingyuan and Xigu regions were significantly higher than other regions, which were the largest recipients of industrial wastewater, urban sewage, domestic waste, and solid waste soil in the city and an important source of HM pollution. The soils in the eight vegetable bases were all alkalic because the soil pH values were higher than 8.0, with a mean of 8.35 and ranged from 8.10 to 8.66. The electrical conductivities of the soils in the eight planting-based treatments were low, range from 0.26 0.57. The mean HM concentrations (i.e., Zn, Cr, Pb, Cd and Cu) in the soils of eight different vegetable bases exceeded the natural background levels. In comparison, for soils, the HM levels were 1.1 to 3.0 times higher than the natural background levels. The concentrations of Zn, Cd, Cr, Cu, and Pb exceeded natural background levels by 1.05-, 3.00-, 1.17-, 1.18 and 1.32 times, respectively. The coefficient of variation (VC) indicated the degree of variation in the sampling sites, and the VC values for Zn, Cd, Cr, Cu, and Pb were 13.18%, 25.01%, 11.03%, 17.04, and 9.04, respectively. The mean HM content in soils followed the order: Cr\u0026thinsp;\u0026gt;\u0026thinsp;Zn ˃ Cu\u0026thinsp;\u0026gt;\u0026thinsp;Pb ˃ Cd. The Cr and Zn contents of soils in the eight planting bases were much higher than those of the other three metals. The Zn content was high in Chengguan district with 78.66 mg/kg while low in Anning district with 54.10 mg/kg. The Cr content was high in Dingyuan District, with a value of 78.43 mg/kg while low in Chengguan (55.03 mg/kg (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe pH, EC (dS/m), organic matter (OM, %) 1.28\u0026ndash;1.69 and the content (mg/kg) of HMs in farmland soils in eight planting bases surrounding the Lanzhou city in Gansu province, China\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.10\u0026thinsp;\u0026plusmn;\u0026thinsp;4.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.80\u0026thinsp;\u0026plusmn;\u0026thinsp;6.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29.24\u0026thinsp;\u0026plusmn;\u0026thinsp;3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.27\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXigu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.37\u0026thinsp;\u0026plusmn;\u0026thinsp;5.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e68.40\u0026thinsp;\u0026plusmn;\u0026thinsp;8.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40.46\u0026thinsp;\u0026plusmn;\u0026thinsp;5.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.23\u0026thinsp;\u0026plusmn;\u0026thinsp;3.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChengguan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78.66\u0026thinsp;\u0026plusmn;\u0026thinsp;6.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55.03\u0026thinsp;\u0026plusmn;\u0026thinsp;6.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.90\u0026thinsp;\u0026plusmn;\u0026thinsp;3.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e24.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeping\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.31\u0026thinsp;\u0026plusmn;\u0026thinsp;4.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61.98\u0026thinsp;\u0026plusmn;\u0026thinsp;5.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33.14\u0026thinsp;\u0026plusmn;\u0026thinsp;2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDingyuan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.48\u0026thinsp;\u0026plusmn;\u0026thinsp;7.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e78.43\u0026thinsp;\u0026plusmn;\u0026thinsp;9.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30.71\u0026thinsp;\u0026plusmn;\u0026thinsp;2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZhonghe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.88\u0026thinsp;\u0026plusmn;\u0026thinsp;8.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e68.73\u0026thinsp;\u0026plusmn;\u0026thinsp;8.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29.75\u0026thinsp;\u0026plusmn;\u0026thinsp;2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29.03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePingan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.28\u0026thinsp;\u0026plusmn;\u0026thinsp;6.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e66.68\u0026thinsp;\u0026plusmn;\u0026thinsp;6.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.38\u0026thinsp;\u0026plusmn;\u0026thinsp;3.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e24.87\u0026thinsp;\u0026plusmn;\u0026thinsp;2.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuazhuang\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.86\u0026thinsp;\u0026plusmn;\u0026thinsp;4.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.02\u0026thinsp;\u0026plusmn;\u0026thinsp;5.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22.69\u0026thinsp;\u0026plusmn;\u0026thinsp;1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e65.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e24.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eBackground value of heavy metal in soil \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eRisk standard of heavy metal for soil (S\u003csub\u003ei\u003c/sub\u003e) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e300.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e250.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e170.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ea\u003c/sup\u003e Soil background values in Gansu province (Soil background values of Chinese elements 1990); \u003csup\u003eb\u003c/sup\u003e Soil environment quality: Risk control standard for soil contamination of agricultural land (GB15618-2018, Ministry of Environment Protection)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe contents of Cr, Zn, Cu, Pb, and Cd in the soils of the eight sites were lower than the risk control standard for soil contamination of agricultural land (GB15618-2018), indicating that these heavy metals in the soils were safe. The Cd, Cr, and Pb contents were higher than the soil background values. For Cd, the accumulation of lettuce at the Dingyuan site exceeded the grade II national standard of China. The application of fertilizers and livestock manure can also lead to the accumulation of heavy metals in the soil and vegetables of agricultural bases in cities. Relevant research has also confirmed that the large and long-term application of organic fertilizers and phosphorus-containing fertilizers from livestock and poultry manure has led to a serious accumulation of HMs (Cupara et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Greenhouse vegetables are commonly cultivated with heavy metal-containing pesticides, and films are added during the planting process, which may also contribute to the accumulation of HMs (Henry et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fan et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). At the same time, some studies have shown that vegetable plots are transformed from farmlands with a history of frequent use, which can leave a large amount of HM contaminants. In this study, we found that the HMs (Zn, Cr, Pb, Hg, and Cd) in the soil of the Anning region were greater than the background levels in the soil, and only Cd exceeded the grade II national standard of China. Except for the Anning, Heping, and Huazhuang sites, the Zn content in the other sites was higher than the soil background value, and the Cu content was higher than the soil background value, except for the Huazhuang site (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Pollution assessment of heavy metals in soil\u003c/h2\u003e \u003cp\u003eThe P\u003csub\u003en\u003c/sub\u003e indexes of the eight vegetable bases showed lesser variations, and only the Xigu site exceeded the safety line (Class I); specifically, The P\u003csub\u003en\u003c/sub\u003e indexes of the Dingyuan site were higher than 0.7 and lower than 1 (Class II), which resulted in slight pollution. The P\u003csub\u003en\u003c/sub\u003e values ranged from 0.48 to 0.94, exposing two ranges from precaution to slight pollution, the P\u003csub\u003en\u003c/sub\u003e of eight vegetable bases decreased in the following order: Dingyuan\u0026thinsp;\u0026gt;\u0026thinsp;Xigu\u0026thinsp;\u0026gt;\u0026thinsp;Anning\u0026thinsp;\u0026gt;\u0026thinsp;Heping\u0026thinsp;\u0026gt;\u0026thinsp;Zhonghe\u0026thinsp;=\u0026thinsp;Pingan\u0026thinsp;\u0026gt;\u0026thinsp;Chengguan\u0026thinsp;\u0026gt;\u0026thinsp;Huazhuang. The soil pollution levels in these vegetable bases indicate a certain degree of heavy metal pollution. Consequently, we assume that this might be due to unreasonable agricultural activities, such as the overuse of pesticides and chemical fertilizers, as well as the influence of the petrochemical industry located near these vegetable bases (Wang et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe potential ecological risk indexes (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}})\\)\u003c/span\u003e\u003c/span\u003e of each HM (Zn, Cd, Cr, Cu, Pb) in the soils of eight vegetable bases and the comprehensive potential ecological risk index (RI) of multiple HMs were calculated, and the results indicated that Cd contributed to the majority of the ecological risk (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In Chengguan and Huazhuang sites, the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e values for Cd both were 62.50, suggesting a moderate ecological risk, and in other six sites, the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e values for Cd were 80\u0026le;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e\u0026lt;160, posing the considerable ecological risk. The \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e of Zn, Cr, Cu and Pb in all vegetable bases were much less than 40, all belonged to low ecological risk. For the five tested HMs, the single contributions to the total potential ecological risk (RI) followed the order of Cd\u0026thinsp;\u0026gt;\u0026thinsp;Pb\u0026thinsp;\u0026gt;\u0026thinsp;Cu\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;Zn. The RI of the total samples was low, based on the ecological risk index for multiple HMs (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEcological risk index (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}})\\)\u003c/span\u003e\u003c/span\u003e for single HM and RI for multiple HMs from farmland soils in eight planting bases surrounding the Lanzhou city in Gansu province, China\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{E}}_{\\text{r}}^{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.50\u0026thinsp;\u0026plusmn;\u0026thinsp;9.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e107.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXigu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107.50\u0026thinsp;\u0026plusmn;\u0026thinsp;13.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e125.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChengguan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.50\u0026thinsp;\u0026plusmn;\u0026thinsp;6.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e77.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeping\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87.50\u0026thinsp;\u0026plusmn;\u0026thinsp;5.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e103.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDingyuan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130.00\u0026thinsp;\u0026plusmn;\u0026thinsp;12.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e146.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZhonghe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.00\u0026thinsp;\u0026plusmn;\u0026thinsp;8.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e102.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePingan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.00\u0026thinsp;\u0026plusmn;\u0026thinsp;7.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuazhuang\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.50\u0026thinsp;\u0026plusmn;\u0026thinsp;7.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e76.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe negative I\u003csub\u003egeo\u003c/sub\u003e values of Zn and Cr indicated that the eight vegetable bases were free from Zn and Cr contamination. The I\u003csub\u003egeo\u003c/sub\u003e-Cu in all vegetable bases, except for the Xigu site, and I\u003csub\u003egeo\u003c/sub\u003e-Pb in all vegetable bases, except for the Zhonghe site, were less than zero. Additionally, the I\u003csub\u003egeo\u003c/sub\u003e-Cu at the Xigu site and I\u003csub\u003egeo\u003c/sub\u003e-Pb at the Zhonghe site were within the range of 0\u0026thinsp;\u0026lt;\u0026thinsp;I\u003csub\u003egeo\u003c/sub\u003e\u0026le;1, suggesting that the degrees of Cu and Pb pollution at these two sites were slightly to moderately polluted. The I\u003csub\u003egeo\u003c/sub\u003e-Cd performed larger spatial variation, the I\u003csub\u003egeo\u003c/sub\u003e-Cd values in Chengguan, Heping, Zhonghe, Pingan and Huazhuang sites were in 0\u0026thinsp;\u0026lt;\u0026thinsp;I\u003csub\u003egeo\u003c/sub\u003e\u0026le;1, indicating that the pollution degrees of Cd in these five sites were slightly to moderately polluted, and the I\u003csub\u003egeo\u003c/sub\u003e-Cd values in Anning, Xigu and Dingyuan sites were in 1\u0026thinsp;\u0026lt;\u0026thinsp;I\u003csub\u003egeo\u003c/sub\u003e\u0026le;2, indicating these two sites existed moderately polluted for Cd (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Levels of heavy metals in vegetables\u003c/h2\u003e \u003cp\u003eTwo-way ANOVA showed that the contents of Zn, Cd, Cr, and Cu were significantly affected by sites and vegetable species, and the interactions between sites and vegetables were not significant (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The Zn content of the vegetables varied significantly within species in each vegetable base (one-way ANOVA: F\u003csub\u003e5,25\u003c/sub\u003e=3.16, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Anning; F\u003csub\u003e5,25\u003c/sub\u003e=3.34, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Xigu; F\u003csub\u003e5,25\u003c/sub\u003e=2.95, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Chengguan; F\u003csub\u003e5,25\u003c/sub\u003e=7.58, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for Heping; F\u003csub\u003e5,25\u003c/sub\u003e=3.23, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Dingyuan; F\u003csub\u003e5,25\u003c/sub\u003e=3.54, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Zhonghe; F\u003csub\u003e5,25\u003c/sub\u003e=6.65, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for Pinganu; F\u003csub\u003e5,25\u003c/sub\u003e=3.76, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Huazhuang). At the Anning and Heping sites, the Zn content in lettuce was significantly higher than that in other vegetables, and the Zn content did not exhibit significant differences among the other five vegetables. At the Xigu site, the Zn contents in rape, scallion, and cucumber were not significantly different, and they were significantly higher than those in leek and lower than those in lettuce. At the Chengguan site, the Zn content in scallions was significantly higher than that in other vegetables, and the other five vegetables did not show significant differences. At the Dingyuan site, no significant differences were observed among rape, scallion, cucumber, and zucchini, which were significantly higher than lettuce and lower than leek. At the Zhonghe site, the highest Zn content was observed in cucumbers, and zucchini showed the lowest accumulation capacity. At the Pingan site, the Zn contents of lettuce, rapeseed, and leek did not show significant differences, and were significantly higher than those of the other three vegetables, with no significant differences observed. Among the scallions, cucumber and zucchini. In Huazhuang, the Zn content in cucumber was significantly higher than that in the other vegetables, and there was no significant difference among the other five vegetables (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe analysis of variance for the effects of different site, vegetable and their interaction on HM accumulation in vegetables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSource of variation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evegetable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esite \u0026times; vegetable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8346\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evegetable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esite \u0026times; vegetable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0663\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evegetable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esite \u0026times; vegetable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0748\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evegetable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esite \u0026times; vegetable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evegetable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7751\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esite \u0026times; vegetable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe Cd content of vegetables was significantly different among vegetables on eight bases (One-way ANOVA: F\u003csub\u003e5,25\u003c/sub\u003e=4.47, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Anning; F\u003csub\u003e5,25\u003c/sub\u003e=4.13, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Xigu; F\u003csub\u003e5,25\u003c/sub\u003e=9.39, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for Chengguan; F\u003csub\u003e5,25\u003c/sub\u003e=4.03, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Heping; F\u003csub\u003e5,25\u003c/sub\u003e=4.89, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Dingyuan; F\u003csub\u003e5,25\u003c/sub\u003e=5.59, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for Zhonghe; F\u003csub\u003e5,25\u003c/sub\u003e=3.98, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Pingan; F\u003csub\u003e5,25\u003c/sub\u003e=4.36, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Huazhuang). In the Xigu and Heping sites, the Cd content in rape was significantly higher than that in other vegetables and did not differ significantly among the other five vegetables, whereas in the Pingan and Huazhuang sites, the opposite performance was observed. At the Anning site, the Cd contents of lettuce, leek, and cucumber were not significantly different, but were significantly higher than those of scallion and zucchini and lower than that of rape. At the Chengguan site, lettuce, leek, cucumber, and zucchini consistently showed lower Cd contents, and the Cd contents of rape and scallion were significantly higher than those of the other four vegetables. Only in Dingyuan site, the Cd content of lettuce exceeded the government standards from the China for HMs in vegetables (GB 2762\u0026thinsp;\u0026minus;\u0026thinsp;2017), and significantly higher than other five vegetables, there were significant difference among these five vegetables. At the Zhonghe site, the Cd contents of lettuce, rape, leek, scallion, and zucchini were not significantly different, but were significantly lower than those of cucumber (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThere was a significant difference in Cr content among the eight vegetables at the Dingyuan site (One-way ANOVA: F\u003csub\u003e5,25\u003c/sub\u003e=4.59, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and no significant differences were observed among the other seven sites. The Cr contents of rape and scallion at the Xigu site, lettuce and scallion at the Zhonghe site, and rape in Pingan slightly exceeded the National Food Safety Standards for contaminant Limits in China (GB 2762\u0026thinsp;\u0026minus;\u0026thinsp;2017). More serious Cr pollution was found at the Dingyuan site; the Cr contents of lettuce, rape, scallion, and zucchini exceeded the standard, and leek and cucumber were relatively safe (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The Cu contents of the six vegetables in the eight vegetable bases did not show significant differences; lettuce and cucumber always accumulated Cu at most sites, and scallion always showed less Cu uptake (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThere were significant difference for Pb contents among vegetables in seven bases (One-way ANOVA: F\u003csub\u003e5,25\u003c/sub\u003e=3.45, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Anning; F\u003csub\u003e5,25\u003c/sub\u003e=4.56, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Xigu; F\u003csub\u003e5,25\u003c/sub\u003e=3.29, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Chengguan; F\u003csub\u003e5,25\u003c/sub\u003e=3.03, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Dingyuan; F\u003csub\u003e5,25\u003c/sub\u003e=4.24, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01 for Zhonghe; F\u003csub\u003e5,25\u003c/sub\u003e=3.23, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Pingan; F\u003csub\u003e5,25\u003c/sub\u003e=3.26, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for Huazhuang). At the Anning site, the Pb content in rape was significantly higher than that in other vegetables and did not show significant differences among the other five vegetables. At the Xigu site, the Pb content of rape, scallion, and cucumber was significantly higher than that of rape and lower than that of lettuce. At the Chengguan site, scallions showed the highest Pb content, and no significant difference was observed among the other five vegetables. There was a significant difference in the Pb content among the six vegetables at the Heping site. In Dingyuan site, the Pb content of leek exceeded the government standards from the China for HMs in vegetables (GB 2762\u0026thinsp;\u0026minus;\u0026thinsp;2017), and was significantly higher than other five vegetables, there were significant difference among these five vegetables. At the Zhonghe site, the Pb contents of scallions, cucumbers, and zucchini were not significantly different but were significantly higher than those of lettuce, rape, and leek. At the Huazhuang and Pingan sites, the Pb content of leek was significantly higher than that of the other five vegetables and slightly exceeded the standards (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHM contents in soils of the vegetable base in Lanzhou followed the order Cr\u0026thinsp;\u0026gt;\u0026thinsp;Zn\u0026thinsp;\u0026gt;\u0026thinsp;Cu\u0026thinsp;\u0026gt;\u0026thinsp;Pb\u0026thinsp;\u0026gt;\u0026thinsp;Cd. The detected sequences of the five metals were significantly affected by plantation base and species. From the linear model regression analysis, the remarkable significant positive relationships were concluded between metal accumulation of vegetables and soils for Zn in \u003cem\u003eAllium tuberosum, Cucumis sativus, Cucurbita maxima\u003c/em\u003e, Cd in \u003cem\u003eLactuca sativa, Allium tuberosum, Cucumis sativus\u003c/em\u003e, Cr in \u003cem\u003eAllium fistulosum, Cucurbita maxima\u003c/em\u003e, Cu in all vegetables except \u003cem\u003eCucurbita maxima\u003c/em\u003e, Pb in \u003cem\u003eLactuca sativa, Allium fistulosum\u003c/em\u003e. The concentrations of all HMs in the soil in this study were higher than the background values and accumulated significantly, but the contents of the vegetables were relatively low; only one leafy vegetable sample had a Cd content exceeding the national standard, indicating that the accumulation of HMs in vegetables was influenced by conditions other than the total amount of HMs in the soil. Studies have shown that many factors affect the uptake of HMs in vegetables, such as soil physicochemical characteristics, speciation distribution of HM in soil, biological effectiveness, vegetable varieties, planting management conditions, and spatial differences (Fan et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Idrees et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Shama et al. 2017; Henry et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, when investigating HM accumulation in vegetables, more attention should be paid to the possible effects of factors other than HM in the soil.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.4. The health risks of heavy metals in vegetables\u003c/h2\u003e \u003cp\u003eThe target hazard quotients (THQ) and hazard index (HI) were applied to assess the human health risk of HMs from vegetable growth in the vegetable bases surrounding Lanzhou City, Gansu Province, China. There were some differences in the THQs because the HMs that contaminated the soils were different for the eight vegetable bases. The THQs of HMs for each vegetable from the Xigu, Dingyuan, Heping, and Zhonghe sites were always higher. All THQ values of HMs for the eight vegetable bases were less than 1, indicating no obvious health risk to the surrounding residents who took up HMs via an individual vegetable (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). The HI values of Cu in all vegetable bases and Cr in Zhonghe, Dingyuan, and Xigu sites were more than 1, suggesting that all sites were likely to pose health risks for Cu and Cr from these three sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe hazard index (HI) has been approved as an important index for health risk assessment and is used to assess the health risks associated with the uptake of HM in food crops. In this study areas, it was as follows: Cu\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;Cd\u0026thinsp;\u0026gt;\u0026thinsp;Zn\u0026thinsp;\u0026gt;\u0026thinsp;Pb. The HIs of all of the HMs investigated in this study were \u0026lt;\u0026thinsp;1, except for Cu at all sites and Cr at the Zhonghe, Dingyuan, and Xigu sites. In the present study, we investigated the THQ indexes of not only non-essential metals but also essential metals. Different vegetable species always have different HM accumulation ability to HMs. It has been reported that Cd uptake in leafy vegetables is higher than that in non-leafy vegetables. In this study, no significant differences were found in the HM content of the edible parts of different vegetable types. Cucumber had higher concentrations and THQs of HMs, and may be classed as \u0026ldquo;high accumulators\u0026rdquo; for Cd. Lower THQs of HMs were found in scallions, which were classed as \u0026ldquo;low accumulators\u0026rdquo; (Lai et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This suggests that the low accumulators were suitable for planting on heavy metal-polluted soil, whereas the high accumulators were unsuitable. The high concentration and the strong accumulation ability of HMs in leafy vegetables were possibly due to the leaves being the main parts of the vegetables used for photosynthesis and more metals flowing to the leaves by strong transpiration. However, Fruit vegetables accumulate more HMs in the edible part, which may be due to the longer growth period and longer accumulation time of HMs (Leblebici et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, atmospheric deposition may be one of the reasons for the metal uptake of leafy vegetables through leaf stomata (Chen et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBoth Cu and Zn are important nutrient elements for humans and are considered to pose much lower health risks than Pb, Cd, Hg, As, and Cr (Zhou et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Deng et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Nolos et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Poor health can be caused by a lack of these required metal elements; however, excessive ingestion can also pose health risks. Currently, there are several methods for estimating the potential health risks of HMs from carcinogenic and non-carcinogenic effects. Non-cancer risk assessment is typically based on the THQ method, which is the ratio of the determined pollutant dose to the reference oral dose (Li et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). THQ values were associated with HM intake, exposure period, body weight, and reference oral dose. Vegetables are only a part of human diets, and in addition to vegetable consumption, consumption of rice, meat, fish, and tobacco also leads to the intake of large amounts of HMs (Qureshi et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Rehman et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBioconcentration factors (BCFs) of HMs for vegetables from eight vegetable bases surrounding Lanzhou city in Gansu province, China. Values with the same lowercase letters indicate no significant difference among vegetables for each HM, and values with capital letters indicate no significant difference among HMs for each vegetable at the 5% level of probability by Duncan\u0026rsquo;s multiple comparison test.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVegetable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elettuce\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0755Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0840Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0070A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2844B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0058A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79.8301***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003erape\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0726Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1081Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0073B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2733C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0063B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.2892***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eleek\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0478Ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0496Ac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0061B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2763C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0065B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e249.7786***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003escallion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0442Ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0665Ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0078B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2329C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0058B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e141.0772***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecucumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0715Aa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0699Ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0060B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3035C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0068B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e335.2488***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ezucchini\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0494Ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0336Ac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0068B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2402C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0063B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e273.8285***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.1880**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.3202***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.0736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.7582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.5. The bioconcentration factor of heavy metals\u003c/h2\u003e \u003cp\u003eThe BCF of each vegetable showed significant differences among the five HMs and among the six vegetables for Zn and Cd. All six vegetables showed consistent Cr, Cu, and Pb uptake capacities. The BCFs of Zn in lettuce, rape, and cucumber were significantly higher than those in the other three vegetables, and there were no significant differences in the BCFs of Zn among lettuce, rape, and cucumber. Leek, scallion, and zucchini were not significantly different for Zn levels. The BCFs of scallion and cucumber for Cd were significantly higher than those of leek and zucchini and lower than those of lettuce and rape. The BCFs of different HMs responded differently to the various vegetables. The BCFs of Cu in all vegetables were much higher than those of the other four HMs, and lettuce did not show significant differences in Zn, Cd, Cr, and Pb. The BCFs of rape, leek, scallion, cucumber and zucchini for Zn and Cd were higher than lower than Cr and Pb, there were significant differences between Zn and Cd, between Cr and Pb (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Correlation analysis\u003c/h2\u003e \u003cp\u003eThe physicochemical parameters EC and OM of soils from the eight vegetable bases showed a strong positive correlation (r\u0026thinsp;=\u0026thinsp;0.96). There were extremely significant correlation at P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 between pH and Cr (r=-0.91), and Pb (r=-0.90), and a relatively significant correlation at P\u0026thinsp;\u0026lt;\u0026thinsp;0.01 between pH and Cr (r=-0.70), and Pb (r=-0.72), and between EC and Cr (r=-0.84), and Cu (r=-0.89), and Cu (r=-0.88), and a significant correlation at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 between OM and Cd (r=-0.78) and Cu (r\u0026thinsp;=\u0026thinsp;0.69). RI and P\u003csub\u003en\u003c/sub\u003e both showed significant correlations with EC, OM, and Cr and Cd contents (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e). A significant correlation between HM content in the soil and edible parts of the vegetables was observed according to the correlation analysis (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) for five HMs and eight vegetables (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e). It was speculated that the HMs in vegetables may come from the soil, which may indicate that HMs in vegetables tend to accumulate in the edible parts but not in the roots or other parts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eCr and Zn in soils from eight vegetable bases were much higher than Cd, Pb, and Cu; there were different levels of heavy metal pollution, and the soils of the Dingyuan and Xigu sites exhibited higher levels of heavy metal pollution and were moderately polluted by Cd. The ecological risk followed the order of Cd\u0026thinsp;\u0026gt;\u0026thinsp;Pb\u0026thinsp;\u0026gt;\u0026thinsp;Cu\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;Zn for all vegetable bases.\u003c/p\u003e \u003cp\u003eCu and Zn in six vegetables from all eight plantation bases did not exceed the Chinese government standards for heavy metals in vegetables (GB 2762\u0026thinsp;\u0026minus;\u0026thinsp;2017). In the Xigu, Dingyuan, and Zhonghe sites, the contents of Cd, Pb, and Cu in vegetables exceeded this standard, and there were certain food safety risks. None of the vegetables from the Xigu, Dingyuan, Heping, or Zhonghe sites presented obvious health risks. It is likely to pose health risks for Cu and Cr from the Zhonghe, Dingyuan, and Xigu sites because of the excessive hazard index. The vegetables always exhibited different accumulation abilities for different heavy metals, and Cu and Cd were more easily accumulated in the edible parts of vegetables. The EC and OM of soils usually promote the uptake of heavy metals, and there are significant correlations between the content of heavy metals in soil and vegetables.\u003c/p\u003e \u003cp\u003eThe main heavy metal sources in vegetable bases are human activities and natural sources. Referential strategies and methods should be adopted to minimize the impacts of heavy metals on human health through the consumption and cultivation of vegetables in the surrounding vegetable bases of the city. Meanwhile, the calculation of the risk assessment model was based on the sampling data, which could lead to uncertainties owing to the lack of comprehensive data for soil and local vegetables in this research. Uncertainties may be caused by factors related to regional vegetable planting methods and land use modes, which would inevitably increase the uncertainty of the results. The parameters published in this research may also need to be updated to represent the current condition more accurately (Ullah et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although the abovementioned factors may bring some uncertainties, this investigation can still provide valuable information for better control of environmental risk and adjustment of vegetable planting modes by local governments and farmers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Materials:\u003c/strong\u003e No supplementary material is available\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eHanru Ren: Visualization, Methodology, Resources, Supervision, Data processing. Jun Ren: Methodology, Resources, Formal analysis, Laboratory analyses. Ling Tao: Conceptualization, Investigation, Data processing, Formal analysis, Visualization, Supervision, Funding acquisition. Xuechang Ren: Conceptualization, Investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003eGansu Provincial Education Department Industry Support Plan Project (2021CYZC-31); Science and Technology Plan Project of Gansu Provincial Science and Technology Department (22CX3GA076); Special Project of Gansu Science and Technology Commissioner (23CXGA0082); Gansu Key Research and Development programs (22YF7GA139)；the Innovation Fund Project of higher education in Gansu Province (2023A-036).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u003c/strong\u003e Exclude this statement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u003c/strong\u003e Informed consent was obtained from all subjects involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e All relevant data are within the paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eThis research was funded by the Foundation of Key Laboratory of Yellow River Environment of Gansu Province (20JR2RA002, 21YRWEK007, 21YRWEG003), Industrial Support Program of Education Department of Gansu Province (2021CYZC-31), the Lanzhou Talent Innovation and Entrepreneurship Project (2021-RC-41), the National Training Programs of Innovation and Entrepreneurship for Undergraduates (202210753012). The “Innovative Star” Project for Outstanding Graduate Students in Gansu Province (2022CXZX-514).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAgbenin, J.O.; Danko, M.; Welp, G. Soil and vegetable compositional relationships of eight potentially toxic metals in urban garden fields from northern Nigeria. \u003cem\u003eJ. Sci. Food Agric.\u003c/em\u003e \u003cstrong\u003e2009\u003c/strong\u003e, \u003cem\u003e89\u003c/em\u003e, 49-54.\u003c/li\u003e\n\u003cli\u003eAhmad, J.U.;\u0026middot;Goni, M.A. Heavy metal contamination in water, soil, and vegetables of the industrial areas in Dhaka, Bangladesh. \u003cem\u003eEnviron. Monit. Assess.\u003c/em\u003e \u003cstrong\u003e2010\u003c/strong\u003e, \u003cem\u003e166\u003c/em\u003e, 347-357.\u003c/li\u003e\n\u003cli\u003eAlfaro, M.R.; Ugarte, O.M.; Lima, L.H.V.; Silva, J.R.; Silva, F.B.V.; Lins, S.A.S.; Nascimento, C.W.A. Risk assessment of heavy metals in soils and edible parts of vegetables grown on sites contaminated by an abandoned steel plant in Havana. \u003cem\u003eEnviron. Geochem. Health\u003c/em\u003e, \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e44\u003c/em\u003e, 43-56.\u003c/li\u003e\n\u003cli\u003eAlturiqi, A.S.; Albedair, L.A.; Ali M.H.H. Health risk assessment of heavy metals in irrigation water, soil and vegetables from different farms in Riyadh district, \u003cem\u003eSaudi Arabia. J. Elem.\u003c/em\u003e \u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e25(4)\u003c/em\u003e, 1269-1289.\u003c/li\u003e\n\u003cli\u003eChen, M.; Li, F.G.; Hu, L.W.; Yang, T.; Yang, Q.; Tao, M.X.; Deng, Y.W. Heavy metal pollution in topsoil and vegetables in the typical mining area near Gannan, Jiangxi Province, China. \u003cem\u003eEnviro. Eng. Sci\u003c/em\u003e. \u003cstrong\u003e2019\u003c/strong\u003e, \u003cem\u003e36(10)\u003c/em\u003e, 1307-1314.\u003c/li\u003e\n\u003cli\u003eChen, Y.C.; Yuan, L.; Xu, C. The accumulation characteristics and potential health risks of heavy metals in vegetables from reclaimed area of China. \u003cem\u003eHuman Ecol. Risk Assess. \u003c/em\u003e\u003cstrong\u003e2018\u003c/strong\u003e, \u003cem\u003e4\u003c/em\u003e, 949-960.\u003c/li\u003e\n\u003cli\u003eCupara, N., Nikolic, R.; Durovic, D.; Milasevic; I.; Medin, D.; Krivokapic, S. Heavy metal assessment in agricultural soils and vegetables in the vicinity of industrial pollutants in the Pljevlja municipality (Montenegro): ecological and health risk approach. \u003cem\u003eEnviron. Monit. Assess.\u003c/em\u003e \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e194\u003c/em\u003e, 819\u003c/li\u003e\n\u003cli\u003eDeng, B.; Li, W.Y.; Xu, W.H.; He, Z.M.; Tan, X. Correlation and the concentrations of Pb, Cd, Hg and As in vegetables and soils of Chongqing, China. \u003cem\u003eEnviron. Geochem. Health\u003c/em\u003e \u003cstrong\u003e2021\u003c/strong\u003e \u003cem\u003e43\u003c/em\u003e, 2357-2376.\u003c/li\u003e\n\u003cli\u003eEliku, T.; Leta, S. Heavy metals bioconcentration from soil to vegetables and appraisal of health risk in Koka and Wonji farms, Ethiopia. \u003cem\u003eEnviron. Sci. Pollut. Res. \u003c/em\u003e\u003cstrong\u003e2017\u003c/strong\u003e, \u003cem\u003e24\u003c/em\u003e, 11807-11815.\u003c/li\u003e\n\u003cli\u003eFan, Y.; Li, H.; Xue, Z.J.; Zhang, Q.; Cheng, F.Q. Accumulation characteristics and potential risk of heavy metals in soil-vegetable system under greenhouse cultivation condition in Northern China. \u003cem\u003eEcol. Eng.\u003c/em\u003e \u003cstrong\u003e2017\u003c/strong\u003e, \u003cem\u003e102\u003c/em\u003e, 367-373.\u003c/li\u003e\n\u003cli\u003eFang, S.B.; Hu, H.; Sun, W.C.; Pan, J. J. Spatial variations of heavy metals in the soils of vegetable-growing land along urban-rural gradient of Nanjing, China. \u003cem\u003eInt. J. Environ. Res. Public Health\u003c/em\u003e \u003cstrong\u003e2011\u003c/strong\u003e, \u003cem\u003e8\u003c/em\u003e, 1805-1816.\u003c/li\u003e\n\u003cli\u003eGaurav, V.K.; Kumar, D.; Sharma, C. Assessment of metal accumulation in the vegetables and associated health risk in the upper-most Ganga-Yamuna Doab Region, India. \u003cem\u003eAm. J. Plant Sci. \u003c/em\u003e\u003cstrong\u003e2018\u003c/strong\u003e, \u003cem\u003e9\u003c/em\u003e, 2347-2358.\u003c/li\u003e\n\u003cli\u003eGebeyehu, H.R.; Bayissa, L.D. Levels of heavy metals in soil and vegetables and associated health risks in Mojoarea, Ethiopia. \u003cem\u003ePLoSONE\u003c/em\u003e, \u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e15(1)\u003c/em\u003e: e0227883\u003c/li\u003e\n\u003cli\u003eGupta, N.; Yadav, K.K.; Kumar, V.; Krishnan, S. Kumar, S.; Nejad, Z.D.;Khan, M.A.M.; Alam, J. Evaluating heavy metals contamination in soil and vegetables in the region of North India: Levels, transfer and potential human health risk analysis \u003cem\u003eEnvironmental Toxicology and Pharmacology\u003c/em\u003e, \u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e82\u003c/em\u003e, 103563\u003c/li\u003e\n\u003cli\u003eHakanson, L. An ecological risk index for aquatic pollution control. A sedimentological approach. \u003cem\u003eWater Res.\u003c/em\u003e \u003cstrong\u003e1980\u003c/strong\u003e, \u003cem\u003e14\u003c/em\u003e, 975-1001.\u003c/li\u003e\n\u003cli\u003eHenry, M.U.; Ogenyi, R.A.; Henry, U.I.; Dogun, O. Assessment of heavy metal concentration in water, soil and vegetable in ex-mining pond, Jos South L.G.A Plateau State, Nigeria. \u003cem\u003eInt. J. of Sci. Res. Public.\u003c/em\u003e \u003cstrong\u003e2018\u003c/strong\u003e, \u003cem\u003e8(8)\u003c/em\u003e, 840-845.\u003c/li\u003e\n\u003cli\u003eIdrees, M.; Rehman, Z.U.; Bibi, S.; Shan, F.; Gulab, H.; Ali, L.; Mabood, F.; Multivariate analysis of the heavy metal concentrations in the vegetable and soil samples-acase study from district Ｃharsadda and district Mardan. \u003cem\u003ePak. J. Bot.\u003c/em\u003e \u003cstrong\u003e2017\u003c/strong\u003e, \u003cem\u003e49(3)\u003c/em\u003e, 1167-1171.\u003c/li\u003e\n\u003cli\u003eJalali, M.; Meyari, J.M. Assessment of the health risks of heavy metals in soils and vegetables from greenhouse production systems in Iran. \u003cem\u003eInt. J. Phytoremediat. \u003c/em\u003e\u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e22(8)\u003c/em\u003e, 834-848.\u003c/li\u003e\n\u003cli\u003eKhan, M.N.; Aslam, M.A.; Muhsinah, A.B.; Uddin, J. Heavy metals in vegetables: screening health risks of irrigation with wastewater in Peri-Urban areas of Bhakkar, Pakistan. \u003cem\u003eToxics\u003c/em\u003e \u003cstrong\u003e2023a\u003c/strong\u003e, \u003cem\u003e11(5)\u003c/em\u003e, 460.\u003c/li\u003e\n\u003cli\u003eKhan, M.N.; Aslam, M.A.; Zada, I.; Albekairi, T.H. Statistical analysis and health risk assessment: vegetables irrigated with wastewater in Kirri Shamozai, Pakistan. \u003cem\u003eToxics\u003c/em\u003e \u003cstrong\u003e2023b\u003c/strong\u003e, \u003cem\u003e11(11)\u003c/em\u003e, 899\u003c/li\u003e\n\u003cli\u003eLai, L.; Li, B.; Li, Z.R.; He, Y.M.; Hu, W.Y.; Zu, Y.Q.; Zhan, F.D. Pollution and health risk assessment of heavy metals in farmlands and vegetables surrounding a lead-zinc mine in Yunnan province, China. \u003cem\u003eSoil Sediment Contam.\u003c/em\u003e \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e31\u003c/em\u003e, 483-497.\u003c/li\u003e\n\u003cli\u003eLeblebici, Z.; Kar, M.; Basaran, L. Assessment of the heavy metal accumulation of various green vegetables grown in Nevsehir and their risks human health. \u003cem\u003eEnviron. Monit. Assess. \u003c/em\u003e\u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e192\u003c/em\u003e, 483.\u003c/li\u003e\n\u003cli\u003eLi, B.; Wang, Y.H.; Jiang, Y.; Li, G.C.; Cui, J.H.; Wang, Y.; Zhang, H.; Wang, S.C.; Xu, S.; Wang, R.Z. The accumulation and health risk of heavy metals in vegetables around a zinc smelter in northeastern China. \u003cem\u003eEnviron. Sci. Pollut. Res.\u003c/em\u003e \u003cstrong\u003e2016\u003c/strong\u003e, \u003cem\u003e23\u003c/em\u003e, 25114-25126.\u003c/li\u003e\n\u003cli\u003eLi, H.X.; Rehman, A.; Rahman, S.; Li, K.D.; Yang, T.R.; Akuetteh, P.; Khalid, M. Biosynthesized zinc oxide nanoparticles modulate the phytoremediation potential of \u003cem\u003ePennisetum giganteum\u003c/em\u003e and its rhizocompartments associated microbial community structure. \u003cem\u003eJ. Clean. Prod.\u003c/em\u003e \u003cstrong\u003e2024\u003c/strong\u003e, \u003cem\u003e434\u003c/em\u003e, 140346.\u003c/li\u003e\n\u003cli\u003eMinhaz, A.; Masaru, M.; Kiyoshi, K. Heavy metal contamination of irrigation water, soil, and vegetable in a multi-industry district of Bangladesh. \u003cem\u003eInt. J. Environ. Res.\u003c/em\u003e \u003cstrong\u003e2018\u003c/strong\u003e, \u003cem\u003e12\u003c/em\u003e, 531-542.\u003c/li\u003e\n\u003cli\u003eMoghaddam, V.K.; Latifi, P.; Darrudi, R.; Askari, S.G.; Mohammadi, A.A.; Marufi, N.; Javan, S. Heavy metal contaminated soil, water, and vegetables in northeastern Iran: potential health risk factors. \u003cem\u003eJ. Environ. Health Sci\u003c/em\u003e. \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e20\u003c/em\u003e, 65-77.\u003c/li\u003e\n\u003cli\u003eNolos, R.C.; Agarin, C.J.M.; Domino, M.Y.R.; Bonifacio, P.B.; Chan, E.B.; Mascarenas, D.R.; Senoro, D.B. Health risks due to metal concentrations in soil and vegetables from the six municipalities of the Island province in the Philippines. \u003cem\u003eInt. J. Environ. Res. Public. Health.\u003c/em\u003e \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e19\u003c/em\u003e, 1578.\u003c/li\u003e\n\u003cli\u003eOgbonna, P.C.; Odukaesieme, C.; Silva, J.A.T. Distribution of heavy metals in soil and accumulation in plants at an agricultural area of Umudike, Nigeria. \u003cem\u003eChem. Ecol\u003c/em\u003e. \u003cem\u003e2013\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e, 595-603.\u003c/li\u003e\n\u003cli\u003eOsma, E.; Serin, M.; Leblebici, Z.; Aksoy, A. Assessment of heavy metal accumulations (Cd, Cr, Cu, Ni, Pb, and Zn) in vegetables and soils. \u003cem\u003ePol. J. Environ. Stud. \u003c/em\u003e\u003cstrong\u003e2013\u003c/strong\u003e, \u003cem\u003e22(5)\u003c/em\u003e, 1449-1455.\u003c/li\u003e\n\u003cli\u003eQureshi, A.S.; Hussain, M.I.; Ismall, S.; Khan, Q.M. Evaluating heavy metal accumulation and potential health risks in vegetables irrigated with treated wastewater. \u003cem\u003eChemosphere\u003c/em\u003e, \u003cstrong\u003e2016\u003c/strong\u003e, \u003cem\u003e163\u003c/em\u003e, 54-61.\u003c/li\u003e\n\u003cli\u003eRehman, Z.U.; Khan, S.; Shah, M.T.; Brusseau, M.L., Khan, S.A.; Mainhagu, J. Transfer of heavy metals from soils to vegetables and associated human health risks at selected sites in Pakistan. \u003cem\u003ePedosphere\u003c/em\u003e \u003cstrong\u003e2018\u003c/strong\u003e, \u003cem\u003e28(4)\u003c/em\u003e, 666-679.\u003c/li\u003e\n\u003cli\u003eSawut, R.; Kasim, N.; Maihemuti, B.; Hu, L.; Abliz, A.; Abdujappar, A.; Kurban, M. Pollution characteristics and health risk assessment of heavy metals in the vegetable bases of northwest China. \u003cem\u003eSci. Total Environ.\u003c/em\u003e \u003cstrong\u003e2018\u003c/strong\u003e, \u003cem\u003e642\u003c/em\u003e, 864-878.\u003c/li\u003e\n\u003cli\u003eSwartjes, F.A.; Versluijs, K.W., Otte, P.F. A tiered approach for the human health risk assessment for consumption of vegetables from with cadmium-contaminated land in urban areas. \u003cem\u003eEnviron. Res.\u003c/em\u003e, \u003cstrong\u003e2013\u003c/strong\u003e, \u003cem\u003e126\u003c/em\u003e, 223-231.\u003c/li\u003e\n\u003cli\u003eUllah, H.; Khaliq, M.; Ullah, N.; Iqbal, A.; Fozia; Ullah, I. Health risk assessment and multivariate statistical analysis of heavy metals in vegetables of Khyber Pakhtunkhwa region, Pakistan. \u003cem\u003eBiol. Trace Elem. Res.\u003c/em\u003e \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e200\u003c/em\u003e, 3023-3038.\u003c/li\u003e\n\u003cli\u003eWang, Y.H.; Zhan,M.G.; Zhu, H.X.; Guo, S.J.; Wang, W.S. Xue, B.M. Distribution and accumulation of metals in soils and plant from a lead-zinc mine land in Guangxi, South China. Bull. \u003cem\u003eEnviron. Contam. Toxicol.\u003c/em\u003e \u003cstrong\u003e2012\u003c/strong\u003e, \u003cem\u003e88\u003c/em\u003e, 198-203.\u003c/li\u003e\n\u003cli\u003eWang, Z.; Bao, J.G.; Wang, T.; Moryani, H.T.; Kang, W., Zheng, J., Zhan, C.L. \u0026amp; Xiao, W.S. Hazardous heavy metals accumulation and health risk assessment of different vegetable species in contaminated soils from a typical mining city, central China. \u003cem\u003eInt. J. Environ. Res. Public Health.\u003c/em\u003e \u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e18\u003c/em\u003e, 2617\u003c/li\u003e\n\u003cli\u003eXu, X.; Shi, M.Y.; Yu, X.M., Liu, M.D. Heavy metal pollution and health risk assessment of vegetable-soil systems of facilities irrigated with wastewater in Northern China. \u003cem\u003eInt. J. Environ. Res. Public Health.\u003c/em\u003e \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e19\u003c/em\u003e, 9835.\u003c/li\u003e\n\u003cli\u003eYu, H.L., Shen, X.F., Chen, H.Y., Dong, H.R., Zhang, L.J., Yuan, T., Zhang, D., Shang, X.D., Tan, Q., Liu, J.Y., Lv, B.B. \u0026amp; Li, Y. Analysis of heavy metal content in \u003cem\u003eLentinula edodes\u003c/em\u003e and the main influencing factors. \u003cem\u003eFood Control\u003c/em\u003e \u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e130\u003c/em\u003e, 108198\u003c/li\u003e\n\u003cli\u003eZeng, L.P.; Zhou, F.; Zhang, X.C.; Qin, J.H.; Li, H.S. Distribution of heavy metals in soils and vegetables and health risk assessment in the vicinity of three contaminated sites in Guangdong Province, China. \u003cem\u003eHuman Ecol. Risk Assess. \u003c/em\u003e\u003cstrong\u003e2018\u003c/strong\u003e, \u003cem\u003e7\u003c/em\u003e, 1901-1915.\u003c/li\u003e\n\u003cli\u003eZhou, H., Yang, W.T., Zhou, X., Liu, L., Gu, J.F., Wang, W.L., Zou, J.L., Tian, T., Peng, P.Q., Liao, B.H. Accumulation of heavy metals in vegetable species planted in contaminated soils and the health risk assessment. \u003cem\u003eInt. J. Environ. Res. Public Health.\u003c/em\u003e \u003cstrong\u003e2016\u003c/strong\u003e, \u003cem\u003e13\u003c/em\u003e, 289.\u003c/li\u003e\n\u003cli\u003eKhan, M.N., Aslam, M.A., Muhsinah, A.B., Uddin, J. Heavy metals in vegetables: Screening health risks of irrigation with wastewater in Peri-Urban areas of Bhakkar, Pakistan. \u003cem\u003eToxics.\u003c/em\u003e \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e11\u003c/em\u003e, 460.\u003c/li\u003e\n\u003cli\u003eKhan, M.N., Aslam, M.A., Zada, I., Albekairi, T.H. Statistical analysis and health risk assessment: vegetables irrigated with wastewater in Kirri Shamozai, Pakistan. \u003cem\u003eToxics.\u003c/em\u003e \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e11\u003c/em\u003e, 899.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-geochemistry-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"egah","sideBox":"Learn more about [Environmental Geochemistry and Health](https://www.springer.com/journal/10653)","snPcode":"10653","submissionUrl":"https://submission.nature.com/new-submission/10653/3","title":"Environmental Geochemistry and Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Heavy metals, Vegetable, Soil, Bioconcentration, Health risk","lastPublishedDoi":"10.21203/rs.3.rs-5021647/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5021647/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHeavy\u003cstrong\u003e \u003c/strong\u003emetal (HMs) contamination in soil causes secondary pollution of vegetables and poses a great threat to health. Soil and vegetable samples were collected from eight different districts in the vegetable base of Lanzhou city in Gansu province. The heavy metal (Zn, Cd, Cr, Cu, and Pb) contents were determined using inductively coupled plasma atomic emission spectroscopy. The results suggest that the Cr and Zn contents of soils in the eight plantation bases were much higher than those of the other three metal contents. The metal concentrations showed significant differences among plantation bases and vegetable species, and the mean HM concentrations of vegetable bases exceeded background levels by 1.1~3.0 times. The accumulation of Cu in vegetables was significantly higher than that of other metals. Remarkable differences were found among the vegetables in the uptake abilities of Zn, Cd, Cr, and Cu. From the linear model regression analysis, significant positive relationships were found between the accumulation of HMs in vegetables and soil content. The information found in this work may be used to provide referential strategies and methods to minimize the impact of HMs on human health through the consumption and cultivation of vegetables.\u003c/p\u003e","manuscriptTitle":"Pollution Evaluation in Soils and Health Risk in Vegetables of Heavy Metals in Surrounding Lanzhou City in Gansu Province, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-04 04:26:44","doi":"10.21203/rs.3.rs-5021647/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorAssigned","content":"","date":"2024-09-05T21:25:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-03T17:42:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Geochemistry and Health","date":"2024-09-03T03:43:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-geochemistry-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"egah","sideBox":"Learn more about [Environmental Geochemistry and Health](https://www.springer.com/journal/10653)","snPcode":"10653","submissionUrl":"https://submission.nature.com/new-submission/10653/3","title":"Environmental Geochemistry and Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"55ebfd75-f6cc-4c1b-a888-0de507688002","owner":[],"postedDate":"October 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-10-04T04:26:44+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-04 04:26:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5021647","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5021647","identity":"rs-5021647","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}