Hostname: page-component-745bb68f8f-s22k5 Total loading time: 0 Render date: 2025-02-11T06:53:45.909Z Has data issue: false hasContentIssue false

Distributions and risks of Cu, Cd, Pb and Zn in soils and rice in the North River Basin, South China

Published online by Cambridge University Press:  19 November 2018

Jing BAI
Affiliation:
College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, PR China. Email: yongtao@scau.edu.cn College of Agriculture and Biotechnology, Hunan University of Humanities, Science and Technology, Loudi, 417000, PR China.
Wenyan LI
Affiliation:
College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, PR China. Email: yongtao@scau.edu.cn
Yulong ZHANG
Affiliation:
College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, PR China. Email: yongtao@scau.edu.cn
Ling XIAO
Affiliation:
College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, PR China. Email: yongtao@scau.edu.cn
Weisheng LU
Affiliation:
College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, PR China. Email: yongtao@scau.edu.cn
Yongtao LI*
Affiliation:
College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, PR China. Email: yongtao@scau.edu.cn
*
*Corresponding author
Rights & Permissions [Opens in a new window]

Abstract

As the largest industrial and population centre in China, the Pearl River Delta is facing a growing threat of heavy metal pollution from local mining and power industries. This study investigates the distribution and potential health risks of copper (Cu), cadmium (Cd), lead (Pb) and zinc (Zn) in paddy soils and rice at four typical sites. The Nemerow synthetic pollution index (PN) of soils from Fogang, Dabao Mountain, Shaoguan and Lechang were 8.40, 9.10, 4.64 and 10.28, respectively, indicating serious pollution at all four sampling sites. The average concentrations of Cu, Cd, Pb and Zn in rice grains were 2.23, 10.98, 29.84 and 1.62 times their corresponding maximum allowable levels, indicating potential health risks to humans. Cd has greater bioavailability because of its high mobility from soil to roots, and its subsequent transfer to grains. Pb mainly accumulates in roots because of its lower translocation rate from roots to grains. The greatest health risk index for Cd and Pb for adults and children was at the Shaoguan site, probably due to pollution from atmospheric deposition. Cd and Pb had greater health risk indices than Cu and Zn at almost all sites, indicating a major health risk to local people.

Type
Articles
Copyright
Copyright © The Royal Society of Edinburgh 2018 

The Pearl River Delta (PRD) covers an area of 54,733km2, including 13,357km2 of agricultural land, of which 4829km2 is used for rice production. Grain yield in the area totals 3383.50 thousand tonnes per year or 80.7% of the total grain output of Guangdong province (Guangdong Statistics Bureau 2015). During the past three decades, the PRD has undergone a rapid transition from a traditional agricultural region to an increasingly industrial and technological one. As a consequence, the soils in the PRD have been extensively contaminated by heavy metals due to the rapid expansion of agriculture, industry, the economy and urbanisation (Hu et al. Reference Hu, Liu, Bai, Shih, Zeng and Cheng2013). Rice is the primary staple food for more than half of the world's population (Qian et al. Reference Qian, Chen, Zhang, Li, Chen and Li2010). The PRD is the largest industrial and population centre in China and is subject to increasing pollution from local mining and power industries.

Heavy metals in soil may remain in local ecosystems for a long time and pose a potential threat to public health (Ben Fredj et al. Reference Ben Fredj, Wali, Khadhraoui, Han, Funamizu, Ksibi and Isoda2014). Mining and smelting processes are primary sources of heavy metal pollution in the PRD due to the transportation of mine tailings and acid mine drainage to ecosystems (Zhuang et al. Reference Zhuang, Zou, Xia and Wang2013). Studies have shown that industrial activities are causing continuous damage to PRD ecosystems (Kuang et al. Reference Kuang, Zhou, Wen and Liu2007). Some traditional industries, especially the coal-fired power plants, release heavy metals into the environment through leaching and atmospheric emission (Fernandez-Turiel et al. Reference Fernandez-Turiel, de Carvalho and Cabanas1994; Cheng Reference Cheng2003). Heavy metals then enter the soils, directly or indirectly, through wastewater, irrigation or atmospheric deposition (Wong et al. Reference Wong, Li, Zhang, Qi and Peng2003). Heavy metal uptake by crops generally includes direct absorption from atmospheric deposition and translocation from agricultural soils (Kachenko & Singh Reference Kachenko and Singh2006; Kabata-Pendias & Mukherjee Reference Kabata-Pendias and Mukherjee2007). When grown in water-flooded soils, rice may take up more heavy metals than other crops and the absorbed heavy metals can be easily transferred to grains (Khan et al. Reference Khan, Islam, Panaullah, Duxbury, Jahiruddin and Loeppert2010). Food consumption is the main pathway for human exposure to heavy metals (Meharg et al. Reference Meharg, Norton, Deacon, Williams, Adomako, Price, Zhu, Li, Zhao and Mcgrath2013). Because of toxicity, non-degradability and easy bioaccumulation, the accumulation of heavy metals in the edible plant parts pose a persistent threat (Banat et al. Reference Banat, Howari and Al-Hamad2005; McBride Reference McBride2007; Chang et al. Reference Chang, Yu, Chen, Li, Zhang and Liu2014). Prolonged exposure to heavy metals may cause damage to the central nervous system, causing chronic diseases such as cancer (Waisberg et al. Reference Waisberg, Joseph, Hale and Beyersmann2003; Omar et al. Reference Omar, Praveena, Aris and Hashim2015). Therefore, a better understanding of the transfer and accumulation of heavy metals from paddy soils to rice grains is critical for an accurate assessment of potential risk.

The North River Basin (NRB), upstream of the PRD, also has large opencast mines and is also a major producer of rice (Luo et al. Reference Luo, Liu, Fu, Liu, Wang and Zhou2008; Li et al. Reference Li, Becquer, Dai, Quantin and Benedetti2009a, Reference Li, Rouland, Benedetti, Li, Pando, Lavelle and Daib). Emissions from mining, smelting and industry in the NRB have not been strictly controlled in recent decades, and large amounts of wastewater, sludge, e-waste and exhaust, which often contain elevated concentrations of heavy metals, have been released, much of which has ended up in the PRD (Zhou et al. Reference Zhou, Dang, Cai and Liu2007; Zhao et al. Reference Zhao, Xia, Fan, Zhao and Shen2012). Previous studies have confirmed an increase in heavy metals in the soil in the PRD, and the degree of heavy metal pollution in soils diminishes in the following order: cadmium (Cd) > copper (Cu) > nickel (Ni) > zinc (Zn) > arsenic (As) > chromium (Cr) > mercury (Hg) > lead (Pb) (Bai & Liu Reference Bai and Liu2014). Li et al. (Reference Li, Becquer, Dai, Quantin and Benedetti2009a, Reference Li, Rouland, Benedetti, Li, Pando, Lavelle and Daib) report that the total contents of four heavy metals had the average values of 283mgCukg–1, 393mgPbkg–1, 296mgZnkg–1 and 0.67mgCdkg–1 in agricultural fields along the Yanghe Valley, near the Dabaoshan polymetallic mine in the NRB. As a consequence, the transfer of heavy metals downstream may lead to the severe contamination of soils and crops, as well as causing health problems in people (Liu et al. 2009; Quan et al. Reference Quan, Yan, Lei, Yang, Li, Xiao and Fu2014). Associated soil and air contaminants may intensify heavy metal accumulation in rice grains. The ‘cadmium rice' contamination incident, which occurred in 2013 in the NRB, demonstrates the exposure that people in this region can be subjected to (Yang et al. Reference Yang, Lan, Wang, Zhuang and Shu2006). The basin's dominant paddy soil type, Plinthudult, is highly acidic. The cultivation pattern of alternating periods of flooding and drying results in the high mobility and bioavailability of heavy metals in paddy soils. Therefore, more attention should be paid to potential food safety issues associated with paddy ecosystems (Neumann et al. Reference Neumann, St Vincent, Roberts, Badruzzaman, Ali and Harvey2011; Li et al. Reference Li, Chen, Fu, Cui, Shi, Wang and Liu2012). The complicated natural conditions (parent material and water regime) combined with intensive anthropogenic activities (mining and smelting, industrial processes) make the NRB region a perfect fit for research on heavy metals (Zhang et al. Reference Zhang, Guo and Wu2015). Few studies have been conducted on heavy metal uptake by rice plants in this critical region, and even less on the potential health risks posed by the rice from the paddy soils in the NRB. Thus, it is of practical significance to investigate the distribution and health risks of heavy metals in the paddy soils of the NRB.

In the present study, the total concentrations of Cu, Cd, Pb and Zn in the paddy soils and the various rice organs sampled from four typical sites around mining and industrial sites in the NRB were determined. The objectives of the present research were to (1) investigate the distribution of Cu, Cd, Pb and Zn in paddy soils and rice plants to quantify the effects of heavy metals from mining and power industry activities on the surrounding environment; (2) explore the differences in metal bioaccumulation by rice plants grown in different sites and the potential factors that influence metal transportation by rice; and (3) evaluate the potential health risks faced by the people living in the study area because of dietary intake of heavy metals via rice consumption. The results provide an evaluation of health risks associated with the consumption of rice grown in highly polluted soils in industrial or mining areas, in the hope of drawing attention to both the safety and quality of agricultural products in the PRD.

1. Material and methods

1.1. Site description

The study area is in the north of Guangdong Province, South China [23°51′53″–25°07′51″N; 113°22′05″–113°47′56″E] (Fig. 1). It has a typical subtropical monsoon climate with an average annual temperature of 21°C and an average annual precipitation of ∼1800mm. The rainy season is from April to September and contributes >70% of the total annual precipitation. The main crop is rice. Four sampling sites around different contaminant sources in the NRB were selected. The Fogang (FG) site [23°51′53″–23°51′56″N; 113°39′16″–113°39′52″E] (Fig. 1a), a pyrite and Pb/Zn mine site in Shuitou Town, Fogang County, is situated in the southern portion of the NRB. The Dabao Mountain (DB) site [24°30′00″–24°38′38″N; 113°45′11″–113°47′56″E] (Fig. 1b) is approximately 3–6km away from an opencast mine producing mainly pyrite, pyrrhotite and chalcopyrite, with also the minor production of sphalerite, chalcocite, galena, limonite and calaverite in Shaxi Town, Qujiang County. The Shaoguan (SD) site [24°34′47″?24°36′05″N; 113°33′48″?113°35′40″E] (Fig. 1c) is mainly affected by mining and atmospheric deposition from a power plant in Wushi Town, Qujiang County. The Lechang (LC) site [25°07′48″?25°07′51″N; 113°22′05″?113°23′13″E] (Fig. 1d) is close to a Pb/Zn mine which has been operating since 1959 in Liantang Village, Lechang County. The mine covers an area of 1.5km2 and annually produces 25,000 tonnes of waste rocks and 30,000 tonnes of tailings (Shu et al. Reference Shu, Ye, Lan, Zhang and Wong2001).

Figure 1 The sampling sites in the North River Basin, Guangdong Province, South China. (a) Shuitou Town, Fogang County. (b) Shaxi Town, Qujiang County. (c) Wushi Town, Qujiang County. (d) Liantang Village, Lechang County. Abbreviations: FG = Fogang site; DB = Dabao Mountain site; SD = Shaoguan site; LC = Lechang site.

1.2. Soil and rice sampling and pre-treatment

The sampling sites are shown in Figure 1. Thirty-six paddy rhizosphere soil samples (0–20cm in depth) were collected, including seven samples from FG, ten samples from DB, ten samples from SD and nine samples from LC. Each of these 36 samples were a composite sample of four random sub-samples. In addition, four replicates of mature rice plants corresponding to each rhizosphere soil sample were collected. All rhizosphere, soil and rice plant samples were stored in clean polyethylene bags and brought back to the laboratory. The rhizosphere soil samples were air-dried and ground to pass through a 2mm and 0.15mm plastic sieve, respectively. After being washed, first with tap water and then with distilled water, the rice plants were blotted with filter paper and fresh weights of each were recorded. The rice plants were then separated into roots, stems, leaves and grains and dried at 105°C for 0.5h and 65°C to reach a constant weight. Before use, the plant parts were pulverised, sieved to pass a 1-mm plastic sieve, homogenised and then stored in polythene zip-bags.

1.3. Sample analysis

Soil pH was measured using a soil/water ratio of 1:2.5. Organic carbon (OC) content was determined by the dichromate digestion method (Pansu & Gautheyrou Reference Pansu and Gautheyrou2006). The results of pH and OC determinations are summarised in Table 1. Soil samples and plant tissues were digested using concentrated HCl-HNO3-HF-HClO4 (Sparks et al. Reference Sparks, Page, Helmke, Loeppert, Soltanpour, Tabatabai, Johnston and Sumner1996) and concentrated HNO3-HClO4 (Kashem & Singh Reference Kashem and Singh1999) for heavy metal analysis, respectively. Concentrations of Cu, Pb and Zn were determined by ICP-AES (Prodigy XP, Leeman, USA), and Cd concentration was determined by AAS (Z-2300, Hitachi, Japan). For quality assurance and quality control, internal standard soil samples (GSS-5) and grain samples (GBW 080684) were analysed with recoveries of 98–102%. The samples were all analysed in triplicate. The heavy metal contents of soils and rice were calculated on dry weight basis.

Table 1 The physico-chemical properties of the paddy soils from the four sampling sites. Abbreviations: FG=Fogang site; DB=Dabao Mountain site; SD=Shaoguan site; LC=Lechang site.

1 The values shown are mean±standard deviation. Different letters in the same column denote significant differences (P<0.05).

1.4. Pollution index method

The single-factor pollution index (Pi) and Nemerow synthetic pollution index (PN) were calculated to assess the degree of metal pollution in the soils (Cheng et al. Reference Cheng, Shi and Zhu2007; Chen et al. Reference Chen, Huang, Hu, Weindorf, Liu and Niedermann2014). The single-factor pollution index was calculated as follows:

(1) $$P_i = { C_i \over S_i }$$

where Pi is the single-factor pollution index of metal i in soil; Ci is the on-the-spot concentration of metal i; and Si is the standard value (GB15618-1995, Grade II) of metal i. Pi > 1 represents heavy metal pollution.

The Nemerow synthetic pollution index was calculated using the following formula:

(2) $$P_N = \sqrt{ { P^2_{ MAX} + P^2_{AVE} \over 2 } }$$

where PN is the Nemerow synthetic pollution index for all assessed samples; P MAX is the maximum of the single-factor pollution indices for all samples; and P AVE represents the arithmetic average of the single-factor pollution indices for all samples. Heavy metal pollution was classified into five grades based on the Nemerow index (Zhao & Li Reference Zhao and Li2013): PN<0.7, safe; 0.7<PN<1.0, precaution needed; 1.0<PN<2.0, slight pollution; 2.0<PN<3.0, moderate pollution; and PN<3.0, serious pollution.

1.5. Transfer factor (TF)

TF, an index indicating the ability of plants to accumulate a certain metal in different tissues relative to the metal's concentration in soil (Wang et al. Reference Wang, Angle, Chaney, Delorme and Reeves2006a, Reference Wang, Su, Chen, Lin, Luo and Gaob; Luo et al. Reference Luo, Liu, Wang, Liu, Li, Zhang and Li2011), was calculated using the following equation:

(3) $${TF_{soil {\hbox -}root}} = {C_{root} \over C_{soil} }}$$
(4) $${TF_{root{\hbox -}grain}} = {C_{grain} \over C_{root} }}$$
(5) $${TF_{soil{\hbox -}grain}} = {C_{grain} \over C_{soil} }}$$

where C root, C soil and C grain represent the heavy metal's concentrations in rice roots, soils and grains, respectively.

1.6. The daily intake of metals (DIM) and estimated daily exposure to metals (EDEM)

EDEM through rice depends on metal concentration in rice grains, the daily rice consumption rate as well as body weight (Jallad Reference Jallad2015), and was calculated with the following formula:

(6) $$\eqalign{ DIM &amp;= Daily\ grain\ consumption \cr &amp;\times Mean\ grain\ metal\ concentration |$$
(7) $$EDEM = { DIM \over Body\ weight }$$

where the average daily grain consumption is 491.5 gday–1 person–1 and 289.6gday–1person–1 for local adults and children, respectively (Liu et al. Reference Liu, Luo, Gao, Li, Lin, Wu and Li2010), and the average body weight is 55.9kg and 32.7kg for adults and children, respectively (Li et al. Reference Li, Chen, Fu, Cui, Shi, Wang and Liu2012).

1.7. Health risk index (HRI)

The HRI for the locals through the consumption of contaminated grains was calculated based on the food chain and the reference oral dose (RfDO) for each metal (Eq. 6). The RfDO was 40μgkg–1d–1 for Cu, 0.5μgkg–1d–1 for Cd, 3.5μgkg–1d–1 for Pb and 300μgkg–1d–1 for Zn (JECFA, 1993; USEPA 2002).

(8) $$HRI = { EDEM \over RfD }$$

HRI<1 means the exposed population is assumed to be safe. HRI > 1 means a potential risk associated with the contaminant (Harmanescu et al. Reference Harmanescu, Alda, Bordean, Gogoasa and Gergen2011).

1.8. Statistical analysis

The data were statistically analysed using the statistical package SPSS 10.0 (SPSS, USA). Differences in total metal content among different sampling sites were determined by one-way analysis of variance (ANOVA) with a significance level of P<0.05. Principal component analysis (PCA) was carried out using the ADE-4 software.

2. Results and discussion

2.1. Soil properties and heavy metal contents

The characteristics of the soils sampled at the four sites are presented in Table 1. The pH values of the soils ranged from 4.14 to 6.72. The paddy soils at DB and FG were acidic (pH 4.61 and 4.79, respectively). The low soil pH at these two sites can be attributed to decades of irrigation with waste water derived from mining. The soil at SD was slightly acidic (pH 5.42) while the soil at LC was nearly neutral (pH 6.12). The average OC content ranged from 32.41 to 69.22gkg–1, with the highest and lowest levels in SD and LC soils, respectively.

As shown in Fig. 2, the paddy soils were seriously contaminated with Cu, Cd, Pb and Zn. The average contents of the four heavy metals at the four sites were generally greater than their corresponding background levels in Guangdong (17mgkg–1 for Cu, 0.06mgkg–1 for Cd, 36mgkg–1 for Pb and 47.3mgkg–1 for Zn; Soil General Survey Office of Guangdong Province 1993), and much greater than their corresponding average contents in the paddy soils of the PRD (Wong et al. Reference Wong, Li, Zhang, Qi and Min2002). Moreover, the average contents of the four metals were greater than their corresponding threshold levels (indicated by the red dotted lines in Fig. 2) as regulated by the China Environmental Quality Standards for Soil (GB15618-1995, grade II for agricultural land). The Cd contents in all of the soil samples exceeded the threshold level (0.3mgkg–1), with the average contents at FG, DB, SD and LC being 10.27, 6.03, 6.27 and 13.6 times higher than the threshold, respectively. Overall, the results indicated that Cu, Cd, Pb and Zn had accumulated in the paddy soils at all four sites.

Figure 2 Boxplots of the heavy metal concentrations in the soils from the four sampling sites. (a) Cu contents in soil. (b) Cd contents in soil. (c) Pd contents in soil. (d) Zn contents in soil. Abbreviations: FG = Fogang site; DB = Dabao Mountain site; SD = Shaoguan site; LC = Lechang site; Cu = copper; Cd = cadmium; Pb = lead; Zn = zinc.

Correlation matrices of the four heavy metals at the sampling sites are presented in Table 2. Significant relationships between Cu, Cd, Pb and Zn at the FG site and the SD site were obtained, indicating that the contaminants might have originated from a common source (Rahman et al. Reference Rahman, Khanam, Adyel, Islam, Ahsan and Akbor2012). The metal composition of the SD soil was comparable to that of fly ash from a thermal power plant (Fernandez-Turiel et al. Reference Fernandez-Turiel, de Carvalho and Cabanas1994). This suggested the SD power plant as a likely source of the metals. The results exhibited a significant correlation between Cu and Pb at the DB site, indicating that Cu and Pb might have originated from a similar source. The average contents of Cu (512.64mgkg–1) and Pb (824.39mgkg–1) at DB were, respectively, 10.25 and 3.30 times higher than their corresponding threshold levels (Fig. 2), indicating a strong influence of mining at DB on the surrounding agricultural paddy soils. This is consistent with previous findings (Li et al. Reference Li, Becquer, Dai, Quantin and Benedetti2009a, Reference Li, Rouland, Benedetti, Li, Pando, Lavelle and Daib; Zhuang et al. Reference Zhuang, McBride, Xia, Li and Li2009). Most of the soil samples from the DB site were collected from fields close to the Hengshi River. Cu and Pb are the major heavy metals in the acid mine drainage from the DB mine (Zhuang et al. Reference Zhuang, McBride, Xia, Li and Li2009; Zhuang et al. Reference Zhuang, Zou, Xia and Wang2013). The fields were frequently irrigated with river water that was contaminated with acid mine drainage from the mining field, thus causing high Cu and Pb contents in DB. At the LC Pb/Zn mine site, the highest average contents of Cd (4.08mgkg–1) and Zn (1035.18mgkg–1) were found in the soil (Fig. 2). A significant correlation was found between Pb and Zn, and between Cd and Pb or Zn, while no relationship was found between Cu and Cd or Zn. The metal concentrations and their correlations reflect the significant impact of mining and power industry activities in the heavy metal pollution of the surrounding soils.

Table 2 Correlation (Pearson) coefficient matrices between the heavy metal concentrations in soils from the four sampling sites. Abbreviations: FG=Fogang site; DB=Dabao Mountain site; SD=Shaoguan site; LC=Lechang site; Cu=copper; Cd=cadmium; Pb=lead; Zn=zinc.

* Correlation is significant at the 0.05 level.

** Correlation is significant at the 0.01 level.

2.2. Assessment of potential environmental risks

The pollution indices of the metals in the soils were calculated according to Eqs 1 and 2, and the metal pollution grades are shown in Table 3. Pi varied greatly between metals and sites. Only five Pi (31.25% of the entire sample set) were <1, while the majority were >1. The Cu, Pb and Zn at SD had Pi values<1 and, thus, are considered to have been at a safe level. For all the metals at DB, Pi > 1 and it was also found that P Cu > 10, indicating an extensive Cu/Cd/Pb/Zn multi-pollution at the sampling site. The PN values of FG, DB, SD and LC were 8.40, 9.10, 4.64 and 10.28, respectively, indicating serious pollution at all of the four sampling sites and a high potential risk from the rice grown at these sites.

Table 3 Soil heavy metal pollution indices for the four sampling sites. Abbreviations: FG=Fogang site; DB=Dabao Mountain site; SD=Shaoguan site; LC=Lechang site; Cu=copper; Cd=cadmium; Pb=lead; Zn=zinc.

1 Pi is the single-factor pollution index of metal i in soil.

2 PN is the Nemerow synthetic pollution index for all assessed samples.

3 Grade of pollution is the classification criterions for pollution index of soil environmental quality.

2.3. Heavy metal concentrations in rice plants

The distributions of heavy metal concentrations in different tissues of rice plants are shown in Fig. 3. Significantly higher concentrations of the heavy metals were found in the roots, indicating that translocation from soil is the main pathway for heavy metal uptake by rice. Compared to heavy metal content in the roots, the corresponding heavy metal concentrations in the grains were significantly less, which is consistent with the findings from a previous study in Nanjing, China (Lu et al. 2003). This suggests that only a minor fraction of the metals present in the soil was transferred to the cereal grains. The concentrations of Cu, Cd, Pb and Zn in the rice tissues were, in general, in the order of stem > leaf > grain. One exception was at SD, where the concentrations of Cu and Cd in the grain were greater than their corresponding concentrations in the stem and leaf. A similar exception was found for Cu at LC. The correlation analysis (Table 2) suggests that Cu at LC was likely derived from a different source relative to the other three metals, and atmospheric deposition was the likely alternative pathway for heavy metals to enter rice.

Figure 3 Boxplots of the heavy metal concentrations in the rice organs (root, stem, leaf and grain) from the four sampling sites. Abbreviations: FG = Fogang site; DB = Dabao Mountain site; SD = Shaoguan site; LC = Lechang site; Cu = copper; Cd = cadmium; Pb = lead; Zn = zinc.

As shown in Figure 3, the metal concentrations in rice roots differed significantly among the four sites. The greatest average concentrations of Cu and Zn were 76.82 and 528.94mgkg–1, respectively, which were at the FG Pb/Zn mine site. The greatest average concentration of Cd (6.99mgkg–1) was at SD, and Pb (372.83mgkg–1) at LC. There were significant differences between FG, DB, SD and LC in the metal concentrations in stems and leaves. The greater Cu, Cd and Pb concentrations in the above-ground rice tissues at SD might have been partially caused by atmospheric particles from the nearby power plant. Qiu et al. (Reference Qiu, Guan, Song and Huang2009) show that the concentrations of Cu (914.6mgkg–1), Cd (12.8mgkg–1) and Pb (184.0mgkg–1) were high in foliar dust near a coal-fired power station in Huizhou, Guangdong.

The heavy metal concentrations in the grains were much less than their corresponding concentrations in the roots and stems. However, they still exceeded their corresponding food safety limits. The maximum allowable levels (MAL) defined by the Ministry of Health of China are 10mgkg–1 for Cu (GB 15199-94), 0.2mgkg–1 for Cd (GB 2762-2012), 0.2mgkg–1 for Pb (GB 2762-2012) and 20mgkg–1 for Zn (GB 13106-91). The average concentrations of Cu, Cd, Pb and Zn at the four sites were 2.23, 10.98, 29.84 and 1.62 times their corresponding MALs. It is worth noting that hazardous Cd and Pb concentrations in the grain from the four sites all exceeded the limits. For Cu and Zn, the majority (83.33 % and 88.89 %, respectively) of the samples had contents greater than the corresponding MALs. Moreover, the contents of all four metals in rice at FG exceeded the corresponding MALs. In summary, the data indicate that rice grains from the four sites were heavily contaminated by the four metals, meaning there was a potential health risk to humans.

2.4. Heavy metal transfer from soils to rice plants

Metal transfer from soils to plants is an important first step for metals entering humans. Metals with high TFs are more easily transferred from soils to edible plant parts than those with low TFs (Bošković-Rakočević et al. Reference Bošković-Rakočević, Milivojević, Milošević and Paunović2014). The Pearson coefficient matrices (see supplementary Tables 1–4 available at https://doi.org/10.1017/S1755691018000646) show that metals in roots correlate with metals in soils at FG, DB and LC, and the metals in grain correlate with metals in leaves at all sites. Additionally, the results of PCA demonstrate that TFsoil-grain of Pb, Cu and Cd were closely associated in first principal components (PC1), suggesting that the distribution of heavy metals of rice plants at SD leading to the differentiation of SD region and the other three regions (Fig. 4). This fact, together with the high correlation between the heavy metals in soils at SD (Table 2), the lack of significant correlation between the total Cu, Cd, Pb and Zn contents in soil, and their corresponding contents in roots (supplementary Table 3), supports the hypothesis that heavy metals in grain at the SD power plant site were largely affected by atmospheric deposition. This could result in a substantial increase in the TFs of the four metals at SD relative to those at the other sites. As a consequence, the TF values of the SD samples are not included in the following discussion.

Figure 4 Principal component analysis of the total heavy metal concentrations, other properties of the soils, and the soil-to-grain transfer factors. (a) Loading plot of PC1 and PC2. (b) Score plot of four sampling sites. Abbreviations: FG = Fogang site; DB = Dabao Mountain site; SD = Shaoguan site; LC = Lechang site; Cu = copper; Cd = cadmium; Pb = lead; Zn = zinc; TF = transfer factor; TOC = total organic carbon.

The TF values of the metals at the sampling sites are shown in Table 4. The TFsoil-root values of Cd were significantly greater than other TFs, and TFroot-grain and TFsoil-grain values of Cu, Cd and Zn were comparable and much greater than those for Pb. This infers that Cd had the greatest bioavailability, based on metal uptake by roots, and Pb had the least bioavailability because of the lowest translocation from root to grains at these sites, although the soil Pb content was much greater than the soil Cd content (Fig. 2). The TFsoil-root and TFroot-grain of Cd highlight that Cd was translocated from soil to grains. This is consistent with previous studies showing that Cu and Cd are transported easily into the edible parts of plants (Kirkham Reference Kirkham2006; Gimbert et al. Reference Gimbert, Mench, Coeurdassier, Badot and de Vaufleury2008), whereas Pb accumulates mainly in plant roots (Yoon et al. Reference Yoon, Cao, Zhou and Ma2006). This may be related to the mechanisms of Cd2+ translocation from roots to shoots via Ca channels (Mark Reference Mark1990; Kim et al. Reference Kim, Yang and Lee2002) and endogenous Zn transporters by active transport (Pence et al. Reference Pence, Larsen, Ebbs, Letham, Lasat, Garvin, Eide and Kochian2000; Uraguchi & Fujiwara Reference Uraguchi and Fujiwara2012). Pb precipitation in cell walls can decrease Pb transport from stem to grain (Liu et al. Reference Liu, Mei, Cai and Wang2015).

Table 4 The transfer factors (TFs) of the heavy metals in soil–plant systems from the four sampling sites. Abbreviations: FG=Fogang site; DB=Dabao Mountain site; SD=Shaoguan site; LC=Lechang site; Cu=copper; Cd=cadmium; Pb=lead; Zn=zinc.

1 The values shown are mean±standard deviation. Different letters in the same column denote significant differences (P<0.05).

The TFsoil-root values of Cu, Cd, Pb and Zn from FG were greater than DB and LC. Heavy metal uptake by food crops depends on soil physicochemical characteristics and plant species (Luo et al. Reference Luo, Liu, Wang, Liu, Li, Zhang and Li2011). The average soil pH at FG was 4.79, significantly lesser than those at SD and LC. The average soil OC content at FG was substantially greater than those at the other sites (Table 1). Soil pH and OC content are believed to be the two important factors governing heavy metal mobility and bioavailability (Zeng et al. Reference Zeng, Ali, Zhang, Ouyang, Qiu, Wu and Zhang2011). Soil pH has a great influence on the solubility and speciation of metals, and thus metal movement in soils (Muehlbachova et al. Reference Muehlbachova, Simon and Pechova2005). A higher soil pH could reduce the bioavailability of heavy metals in the soil solution, while a lower pH releases ‘soil-bound' metal ions into the soil solution (Wang et al. Reference Wang, Angle, Chaney, Delorme and Reeves2006a, Reference Wang, Su, Chen, Lin, Luo and Gaob). Soil organic matter, especially fulvic acid, can chelate with metals and increase metal bioavailability to plants (Hettiarachchi et al. Reference Hettiarachchi, Ryan, Chaney and La Fleur2003). Organic matter provides organic chemicals to the soil solution, causing metal bioavailability to increase through organic matter chelation (Vega et al. Reference Vega, Covelo, Andrade and Marcet2004). The results suggest that metals at the four sites and their surrounding areas are being transferred to rice grains, making the contaminated areas unsuitable for rice.

2.5. DIM through food chain and human health risk

The daily intake of heavy metals was estimated based on average rice consumption. The HRI is a useful index for the evaluation of risk associated with the consumption of metal-contaminated foods (Cao et al. Reference Cao, Duan, Zhao, Ma, Dong, Huang, Sun, He and Wei2014). The DIMs and HRIs of the metals via rice consumption for both adults and children are shown in Table 5. DIM values show that humans at the FG site had the greatest intake of Cu and Zn through rice, and people at the SD site had the greatest intake of Cd and Pb through rice. The total intake of the four metals via rice at DB and LC were less than at other sites. Almost all HRI values were greater than 1, except for Zn at DB and LC, and all heavy metal HRI values for children were higher than those for adults at the four sites. This indicates that the local residents at the four sites were subject to serious health risks from heavy metals, with children being at a greater risk than adults despite the lesser consumption rates for children.

Table 5 The daily intake (DIM), estimated daily exposure (EDEM) and health risk index (HRI) of the heavy metals at the four sampling sites. Abbreviations: FG=Fogang site; DB=Dabao Mountain site; SD=Shaoguan site; LC=Lechang site.

The HRI values of Cu, Cd, Pb and Zn at the four sites ranged from 3.28 to 4.57, 5.23 to 35.98, 3.08 to 13.97 and 0.81 to 2.21, respectively, for adults, while the values ranged from 3.54 to 4.94, 5.65 to 38.89, 3.33 to 15.10 and 0.87 to 2.39, respectively, for children. The potential health risks of Cu, Cd and Pb were greater compared to that of Zn. Cd had relatively greater HRIs compared to the other metals, with the greatest values of 38.89, 13.87, 9.28 and 5.65 at SD, FG, DB and LC, respectively, for children. Pb and Cd are regarded as potential carcinogens and are associated with serious systemic health problems, such as cardiovascular, kidney as well as blood diseases (Komarnicki Reference Komarnicki2005; Pruvot et al. Reference Pruvot, Douay, Herve and Waterlot2006). If soils and dusts from a smelter are ingested, Pb can dissolve in the stomach, potentially causing a blood disease (Bosso & Enzweiler Reference Bosso and Enzweiler2008). An excessive risk of cardiovascular mortality in Cd-exposed inhabitants and a moderate relationship between the contents of Cu and Cd in soil and cardiovascular morbidity in adolescence have been reported (Nishijo et al. Reference Nishijo, Nakagawa, Morikawa, Tabata, Senma, Miura, Takahara, Kawano, Nishi, Mizukoshi and Et1995; Kharlamova & Val'Tseva Reference Kharlamova and Val'Tseva2014). In general, the results show that Cd was the most hazardous metal among the studied metals for both adults and children.

For both adults and children, the Cd HRI values at the four sites were in the decreasing order of SD > FG > DB > LC, and the Pd HRI values at the four sites were in the decreasing order of SD > LC > FG > DB. The SD power plant site had the highest HRI values for Cd and Pb, although its metal pollution levels in the soil were low. The atmospheric deposition of heavy metals from the power plant at SD was likely to be responsible for the potential risk to rice consumption. Compared with the findings of studies on farmland (Chen et al. Reference Chen, Teng, Lu, Wang and Wang2015) and near mining (Liu et al. Reference Liu, Zhang, Tran, Wang and Zhu2011; Ackah et al. Reference Ackah, Anim, Gyamfi, Zakaria, Hanson, Tulasi, Enti-Brown, Saah-Nyarko, Bentil and Osei2014), the HRI values for adults and children through rice consumption in this study were markedly higher. Cu HRI values at the four sites were in the decreasing order of FG > SD > LC > DB, and the Zn HRI values at four sites were in the decreasing order of FG > SD > LC > DB. The highest HRI values for Cu and Zn were obtained at the FG Pb/Zn mine site. As Cd and Pb are more hazardous than Cu and Zn, it is expected that inhabitants close to the SD site would be experiencing relatively greater health risks than other sites, as indicated by the high HRI values for Cd and Pb.

3. Conclusions

In this study, untreated or poorly treated effluents and wastes from mining factories and unrestrained gas emissions from the power plant lead to the accumulation of Cu, Cd, Pb and Zn in the paddy soils of the NRB, South China. The average contents of the four metals were greater than their corresponding threshold levels, indicating serious multi-pollution at the sampling sites. Rice tended to take up heavy metals from soil and through atmospheric deposition. The metal contents in the rice grains commonly exceeded the permissible food guideline limits in China, and posed a great health risk to the local population. The HRIs of the metals at the four sites confirmed that ingestion of the contaminated rice was unsafe, children facing a greater risk than adults. Of the four heavy metals, Cd was more easily transferred from soil to rice, and was the most hazardous metal for both adults and children. The SD power plant site posed the greatest risk, as indicated by the HIR values of Cd and Pb. The atmospheric deposition of heavy metals from the SD power plant is likely to have been responsible for the potential risk, although its metal pollution levels in soil were small. Effective measurement is needed to manage and remediate the toxic metals in the NRB.

4. Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (project numbers U1401234, 41271266 and 41401249), the National Science and Technology Support Program (2015BAD05B05) and the National Environmental Protection Special Project (201509032). The authors would like to thank the anonymous reviewers for their helpful comments and suggestions.

5. Supplementary material

Supplementary material is available online at https://doi.org/10.1017/S1755691018000646.

Footnotes

Both authors contributed equally to this work

References

6. References

Ackah, M., Anim, A. K., Gyamfi, E. T., Zakaria, N., Hanson, J., Tulasi, D., Enti-Brown, S., Saah-Nyarko, E., Bentil, N. O. & Osei, J. 2014. Uptake of heavy metals by some edible vegetables irrigated using wastewater: a preliminary study in Accra, Ghana. Environmental Monitoring and Assessment 186, 621634.Google Scholar
Bai, J. M. & Liu, X. P. 2014. Heavy metal pollution in surface soils of Pearl River Delta, China. Environmental Monitoring and Assessment 186, 80518061.Google Scholar
Banat, K. M., Howari, F. M. & Al-Hamad, A. A. 2005. Heavy metals in urban soils of central Jordan: should we worry about their environmental risks? Environmental Research 97(3), 258273.Google Scholar
Ben Fredj, F., Wali, A., Khadhraoui, M., Han, J., Funamizu, N., Ksibi, M. & Isoda, H. 2014. Risk assessment of heavy metal toxicity of soil irrigated with treated wastewater using heat shock proteins stress responses: case of El Hajeb, Sfax, Tunisia. Environmental Science and Pollution Research 21, 47164726.Google Scholar
Bošković-Rakočević, L., Milivojević, J., Milošević, T. & Paunović, G. 2014. Heavy metal content of soils and plum orchards in an uncontaminated area. Water, Air, & Soil Pollution 225, 113.Google Scholar
Bosso, S. T. & Enzweiler, J. 2008. Bioaccessible lead in soils, slag, and mine wastes from an abandoned mining district in Brazil. Environmental Geochemistry and Health 30, 219229.Google Scholar
Cao, S. Z., Duan, X. L., Zhao, X. G., Ma, J., Dong, T., Huang, N., Sun, C. Y., He, B. & Wei, F. S. 2014. Health risks from the exposure of children to As, Se, Pb and other heavy metals near the largest coking plant in China. Science of The Total Environment 472, 10011009.Google Scholar
Chang, C. Y., Yu, H. Y., Chen, J. J., Li, F. B., Zhang, H. H. & Liu, C. P. 2014. Accumulation of heavy metals in leaf vegetables from agricultural soils and associated potential health risks in the Pearl River Delta, South China. Environmental Monitoring and Assessment 186(3), 15471560.Google Scholar
Chen, H. Y., Teng, Y. G., Lu, S. J., Wang, Y. Y. & Wang, J. S. 2015. Contamination features and health risk of soil heavy metals in China. Science of The Total Environment , 143153.Google Scholar
Chen, Y., Huang, B., Hu, W. Y., Weindorf, D. C., Liu, X. X. & Niedermann, S. 2014. Assessing the risks of trace elements in environmental materials under selected greenhouse vegetable production systems of China. Science of The Total Environment , 11401150.Google Scholar
Cheng, J. L., Shi, Z. & Zhu, Y. W. 2007. Assessment and mapping of environmental quality in agricultural soils of Zhejiang Province, China. Journal of Environmental Sciences 19, 5054.Google Scholar
Cheng, S. 2003. Heavy metal pollution in China: origin, pattern and control. Environmental Science and Pollution Research 10(3), 192198.Google Scholar
Fernandez-Turiel, J. L., de Carvalho, W. & Cabanas, M. 1994. Mobility of heavy metals from coal fly ash. Environmental Geology 23, 264270.Google Scholar
Gimbert, F., Mench, M., Coeurdassier, M. L., Badot, P. & de Vaufleury, A. 2008. Kinetic and dynamic aspects of soil–plant–snail transfer of cadmium in the field. Environmental Pollution 152, 736745.Google Scholar
Guangdong Statistics Bureau. 2015. Statistical yearbook of Guangdong, China. Beijing: China Statistics.Google Scholar
Harmanescu, M., Alda, L. M., Bordean, D. M., Gogoasa, I. & Gergen, I. 2011. Heavy metals health risk assessment for population via consumption of vegetables grown in old mining area; a case study: Banat County, Romania. Chemistry Central Journal 5, 6474.Google Scholar
Hettiarachchi, G. M., Ryan, J. A., Chaney, R. L. & La Fleur, C. M. 2003. Sorption and desorption of cadmium by different fractions of biosolids-amended soils. Journal of Environmental Quality 32, 16841693.Google Scholar
Hu, Y. N., Liu, X. P., Bai, J. M., Shih, K. M., Zeng, E. Y. & Cheng, H. F. 2013. Assessing heavy metal pollution in the surface soils of a region that had undergone three decades of intense industrialization and urbanization. Environmental Science and Pollution Research 20, 61506159.Google Scholar
Jallad, K. N. 2015. Heavy metal exposure from ingesting rice and its related potential hazardous health risks to humans. Environmental Science and Pollution Research 22, 1544915458.Google Scholar
Joint FAO/WHO Expert Committee on Food Additives (JECFA). 1993. Toxicological evaluation of certain food additives and contaminants. WHO Technical Report Series, no. 837. Geneva: Joint FAO/WHO Expert Committee on Food Additives.Google Scholar
Kabata-Pendias, A. & Mukherjee, A. B. 2007. Trace elements from soil to human. Berlin: Springer.Google Scholar
Kachenko, A. & Singh, B. 2006. Heavy metals contamination in vegetables grown in urban and metal smelter contaminated sites in Australia. Water, Air, & Soil Pollution 169, 101123.Google Scholar
Kashem, A. & Singh, B. R. 1999. Heavy metal contamination of soil and vegetation in the vicinity of industries in Bangladesh. Water, Air, & Soil Pollution 115, 347361.Google Scholar
Khan, M. A., Islam, M. R., Panaullah, G. M., Duxbury, J. M., Jahiruddin, M. & Loeppert, R. H. 2010. Accumulation of arsenic in soil and rice under wetland condition in Bangladesh. Plant and Soil 333, 263274.Google Scholar
Kharlamova, E. N. & Val'Tseva, E. A. 2014. Assessment of the impact of environmental factors on the morbidity rate of respiratory and cardiovascular diseases in adolescents of the city of Samara. Gigiena i Sanitariia 93, 8791.Google Scholar
Kim, Y. Y., Yang, Y. Y. & Lee, Y. S. 2002. Pb and Cd uptake in rice roots. Physiologia Plantarum 116, 368372.Google Scholar
Kirkham, M. B. 2006. Cadmium in plants on polluted soils: effects of soil factors, hyperaccumulation, and amendments. Geoderma 137, 1932.Google Scholar
Komarnicki, G. J. K. 2005. Lead and cadmium in indoor air and the urban environment. Environmental Pollution 136, 4761.Google Scholar
Kuang, Y. W., Zhou, G. Y., Wen, D. Z. & Liu, S. Z. 2007. Heavy metals in bark of Pinus massoniana (Lamb.) as an indicator of atmospheric deposition near a smeltery at Qujiang, China. Environmental Science and Pollution Research 14, 270275.Google Scholar
Li, Q. S., Chen, Y., Fu, H. B., Cui, Z. H., Shi, L., Wang, L. L. & Liu, Z. F. 2012. Health risk of heavy metals in food crops grown on reclaimed tidal flat soil in the Pearl River Estuary, China. Journal of Hazardous Materials 227, 148154.Google Scholar
Li, Y. T., Becquer, T., Dai, J., Quantin, C. & Benedetti, M. F. 2009a. Ion activity and distribution of heavy metals in acid mine drainage polluted subtropical soils. Environmental Pollution 157, 12491257.Google Scholar
Li, Y. T., Rouland, C., Benedetti, M., Li, F. B., Pando, A., Lavelle, P. & Dai, J. 2009b. Microbial biomass, enzyme and mineralization activity in relation to soil organic C, N and P turnover influenced by acid metal stress. Soil Biology and Biochemistry 41, 969977.Google Scholar
Liu, C. P., Luo, C. L., Gao, Y., Li, F. B., Lin, L. W., Wu, C. A. & Li, X. D. 2010. Arsenic contamination and potential health risk implications at an abandoned tungsten mine, southern China. Environmental Pollution 158, 820826.Google Scholar
Liu, J., Zhang, X. H., Tran, H., Wang, D. Q. & Zhu, Y. N. 2011. Heavy metal contamination and risk assessment in water, paddy soil, and rice around an electroplating plant. Environmental Science and Pollution Research 18, 16231632.Google Scholar
Liu, J. G., Mei, C. C., Cai, H. & Wang, M. X. 2015. Relationships between subcellular distribution and translocation and grain accumulation of Pb in different rice cultivars. Water, Air, & Soil Pollution 226, 93.Google Scholar
Liu, J. L., Li, Y. L., Zhang, B., Cao, J. L., Cao, Z. G. & Domagalski, J. 2009. Ecological risk of heavy metals in sediments of the Luan River source water. Ecotoxicology 18, 748758.Google Scholar
Lu, Y., Gong, Z. T., Zhang, G. L. & Burghardt, W. 2003. Concentrations and chemical speciations of Cu, Zn, Pb and Cr of urban soils in Nanjing, China. Geoderma 115, 101111.Google Scholar
Luo, C. L., Liu, C. P., Wang, Y., Liu, X., Li, F. B., Zhang, G. & Li, X. D. 2011. Heavy metal contamination in soils and vegetables near an e-waste processing site, south China. Journal of Hazardous Materials 186, 481490.Google Scholar
Luo, Y., Liu, S., Fu, S. L., Liu, J. S., Wang, G. Q. & Zhou, G. Y. 2008. Trends of precipitation in Beijiang River Basin, Guangdong Province, China. Hydrological Processes 22, 23772386.Google Scholar
Mark, T. 1990. Tansley review No. 21 plant ion channels: whole-cell and single channel studies. New Phytologist 114, 305340.Google Scholar
McBride, M. B. 2007. Trace metals and sulfur in soils and forage of a chronic wasting disease locus. Environmental Chemistry 4(2), 134139.Google Scholar
Meharg, A. A., Norton, G., Deacon, C., Williams, P., Adomako, E. E., Price, A., Zhu, Y., Li, G. Zhao, F. J. & Mcgrath, S. 2013. Variation in rice cadmium related to human exposure. Environmental Science & Technology 47, 56135618.Google Scholar
Muehlbachova, G., Simon, T. & Pechova, M. 2005. The availability of Cd, Pb and Zn and their relationships with soil pH and microbial biomass in soils amended by natural clinoptilolite. Plant, Soil and Environment 51, 2633.Google Scholar
Neumann, R. B., St Vincent, A. P., Roberts, L. C., Badruzzaman, A. B. M., Ali, M. A. & Harvey, C. F. 2011. Rice field geochemistry and hydrology: An explanation for why groundwater irrigated fields in Bangladesh are net sinks of arsenic from groundwater. Environmental Science & Technology 45, 20722078.Google Scholar
Nishijo, M., Nakagawa, H., Morikawa, Y., Tabata, M., Senma, M., Miura, K., Takahara, H., Kawano, S., Nishi, M., Mizukoshi, K. & Et, A. 1995. Mortality of inhabitants in an area polluted by cadmium: 15 year follow up. Occupational and Environmental Medicine 52, 181184.Google Scholar
Omar, N. A., Praveena, S. M., Aris, A. Z. & Hashim, Z. 2015. Health risk assessment using in vitro digestion model in assessing bioavailability of heavy metal in rice: a preliminary study. Food Chemistry 188, 4650.Google Scholar
Pansu, M. & Gautheyrou, J. 2006. Handbook of soil analysis: mineralogical, organic and inorganic methods. Berlin and Heidelberg: Springer.Google Scholar
Pence, N. S., Larsen, P. B., Ebbs, S. D., Letham, D. L. D., Lasat, M. M., Garvin, D. F., Eide, D. & Kochian, A. L. V. 2000. The molecular physiology of heavy metal transport in the Zn/Cd hyperaccumulator Thlaspi caerulescens. Proceedings of the National Academy of Sciences 97, 49564960.Google Scholar
Pruvot, C., Douay, F., Herve, F. & Waterlot, C. 2006. Heavy metals in soil, crops and grass as a source of human exposure in the former mining areas. Journal of Soils and Sediments 6, 215220.Google Scholar
Qian, Y. Z., Chen, C., Zhang, Q., Li, Y., Chen, Z. J. & Li, M. 2010. Concentrations of cadmium, lead, mercury and arsenic in Chinese market milled rice and associated population health risk. Food Control 21, 17571763.Google Scholar
Qiu, Y., Guan, D. S., Song, W. W. & Huang, K. Y. 2009. Capture of heavy metals and sulfur by foliar dust in urban Huizhou, Guangdong Province, China. Chemosphere 75, 447452.Google Scholar
Quan, S. X., Yan, B., Lei, C., Yang, F., Li, N., Xiao, X. M. & Fu, J. M. 2014. Distribution of heavy metal pollution in sediments from an acid leaching site of e-waste. Science of The Total Environment 499, 349355.Google Scholar
Rahman, S. H., Khanam, D., Adyel, T. M., Islam, M. S., Ahsan, M. A. & Akbor, M. A. 2012. Assessment of heavy metal contamination of agricultural soil around Dhaka export processing zone (DEPZ), Bangladesh: implication of seasonal variation and indices. Applied Sciences 2, 584601.Google Scholar
Shu, W. S., Ye, Z. H., Lan, C. Y., Zhang, Z. Q. & Wong, M. H. 2001. Acidification of lead/zinc mine tailings and its effect on heavy metal mobility. Environment International 26, 389394.Google Scholar
Soil General Survey Office of Guangdong Province. 1993. Soils in Guangdong. Beijing: Science Press.Google Scholar
Sparks, D. L., Page, A. L., Helmke, P. A., Loeppert, R. H., Soltanpour, P. N., Tabatabai, M. A., Johnston, C. T. & Sumner, M. E. 1996. Methods of soil analysis. part 3-chemical methods. Madison, WI: Soil Science Society of America Inc.Google Scholar
United States Environmental Protection Agency (USEPA). 2002. Region 9, preliminary remediation goals. http://www.epa.gov/region09/waste/sfund/prg (accessed 10 December 2015).Google Scholar
Uraguchi, S. & Fujiwara, T. 2012. Cadmium transport and tolerance in rice: perspectives for reducing grain cadmium accumulation. Rice 5, 5.Google Scholar
Vega, F. A., Covelo, E. F., Andrade, M. L. & Marcet, P. 2004. Relationships between heavy metals content and soil properties in minesoils. Analytica Chimica Acta 524(1-2), 141150.Google Scholar
Waisberg, M., Joseph, P., Hale, B. & Beyersmann, D. 2003. Molecular and cellular mechanisms of cadmium carcinogenesis. Toxicology 192, 95117.Google Scholar
Wang, A. S., Angle, J. S., Chaney, R. L., Delorme, T. A. & Reeves, R. D. 2006a. Soil pH effects on uptake of Cd and Zn by Thlaspi caerulescens. Plant and Soil 281, 325337.Google Scholar
Wang, G., Su, M. Y., Chen, Y. H., Lin, F. F., Luo, D. & Gao, S. F. 2006b. Transfer characteristics of cadmium and lead from soil to the edible parts of six vegetable species in southeastern China. Environmental Pollution 144, 127135.Google Scholar
Wong, C. S. C., Li, X. D., Zhang, G., Qi, S. H. & Peng, X. Z. 2003. Atmospheric deposition of heavy metals in the Pearl River Delta, China. Atmospheric Environment 37, 767776.Google Scholar
Wong, S. C., Li, X. D., Zhang, G., Qi, S. H. & Min, Y. S. 2002. Heavy metals in agricultural soils of the Pearl River Delta, South China. Environmental Pollution 119, 3344.Google Scholar
Yang, Q. W., Lan, C. Y., Wang, H. B., Zhuang, P. & Shu, W. S. 2006. Cadmium in soil–rice system and health risk associated with the use of untreated mining wastewater for irrigation in Lechang, China. Agricultural Water Management 84, 147152.Google Scholar
Yoon, J., Cao, X., Zhou, Q. & Ma, L. Q. 2006. Accumulation of Pb, Cu, and Zn in native plants growing on a contaminated Florida site. Science of The Total Environment 368, 456464.Google Scholar
Zeng, F., Ali, S., Zhang, H., Ouyang, Y., Qiu, B., Wu, F. & Zhang, G. 2011. The influence of pH and organic matter content in paddy soil on heavy metal availability and their uptake by rice plants. Environmental Pollution 159, 8491.Google Scholar
Zhang, L., Guo, S. & Wu, B. 2015. The source, spatial distribution and risk assessment of heavy metals in soil from the pearl river Delta based on the national multi-purpose regional geochemical survey. PLoS ONE 10, e132040.Google Scholar
Zhao, H. R., Xia, B. C., Fan, C., Zhao, P. & Shen, S. L. 2012. Human health risk from soil heavy metal contamination under different land uses near Dabaoshan Mine, Southern China. Science of The Total Environment 417, 4554.Google Scholar
Zhao, H. T. & Li, X. Y. 2013. Risk assessment of metals in road-deposited sediment along an urban–rural gradient. Environmental Pollution 174, 297304.Google Scholar
Zhou, J. M., Dang, Z., Cai, M. F. & Liu, C. Q. 2007. Soil heavy metal pollution around the Dabaoshan Mine, Guangdong Province, China. Pedosphere 17, 588594.Google Scholar
Zhuang, P., McBride, M. B., Xia, H., Li, N. & Li, Z. 2009. Health risk from heavy metals via consumption of food crops in the vicinity of Dabaoshan mine, South China. Science of The Total Environment 407, 15511561.Google Scholar
Zhuang, P. L. Z. A., Zou, B., Xia, H. P. & Wang, G. 2013. Heavy metal contamination in soil and soybean near the Dabaoshan mine, South China. Pedosphere 23, 298304.Google Scholar
Figure 0

Figure 1 The sampling sites in the North River Basin, Guangdong Province, South China. (a) Shuitou Town, Fogang County. (b) Shaxi Town, Qujiang County. (c) Wushi Town, Qujiang County. (d) Liantang Village, Lechang County. Abbreviations: FG = Fogang site; DB = Dabao Mountain site; SD = Shaoguan site; LC = Lechang site.

Figure 1

Table 1 The physico-chemical properties of the paddy soils from the four sampling sites. Abbreviations: FG=Fogang site; DB=Dabao Mountain site; SD=Shaoguan site; LC=Lechang site.

Figure 2

Figure 2 Boxplots of the heavy metal concentrations in the soils from the four sampling sites. (a) Cu contents in soil. (b) Cd contents in soil. (c) Pd contents in soil. (d) Zn contents in soil. Abbreviations: FG = Fogang site; DB = Dabao Mountain site; SD = Shaoguan site; LC = Lechang site; Cu = copper; Cd = cadmium; Pb = lead; Zn = zinc.

Figure 3

Table 2 Correlation (Pearson) coefficient matrices between the heavy metal concentrations in soils from the four sampling sites. Abbreviations: FG=Fogang site; DB=Dabao Mountain site; SD=Shaoguan site; LC=Lechang site; Cu=copper; Cd=cadmium; Pb=lead; Zn=zinc.

Figure 4

Table 3 Soil heavy metal pollution indices for the four sampling sites. Abbreviations: FG=Fogang site; DB=Dabao Mountain site; SD=Shaoguan site; LC=Lechang site; Cu=copper; Cd=cadmium; Pb=lead; Zn=zinc.

Figure 5

Figure 3 Boxplots of the heavy metal concentrations in the rice organs (root, stem, leaf and grain) from the four sampling sites. Abbreviations: FG = Fogang site; DB = Dabao Mountain site; SD = Shaoguan site; LC = Lechang site; Cu = copper; Cd = cadmium; Pb = lead; Zn = zinc.

Figure 6

Figure 4 Principal component analysis of the total heavy metal concentrations, other properties of the soils, and the soil-to-grain transfer factors. (a) Loading plot of PC1 and PC2. (b) Score plot of four sampling sites. Abbreviations: FG = Fogang site; DB = Dabao Mountain site; SD = Shaoguan site; LC = Lechang site; Cu = copper; Cd = cadmium; Pb = lead; Zn = zinc; TF = transfer factor; TOC = total organic carbon.

Figure 7

Table 4 The transfer factors (TFs) of the heavy metals in soil–plant systems from the four sampling sites. Abbreviations: FG=Fogang site; DB=Dabao Mountain site; SD=Shaoguan site; LC=Lechang site; Cu=copper; Cd=cadmium; Pb=lead; Zn=zinc.

Figure 8

Table 5 The daily intake (DIM), estimated daily exposure (EDEM) and health risk index (HRI) of the heavy metals at the four sampling sites. Abbreviations: FG=Fogang site; DB=Dabao Mountain site; SD=Shaoguan site; LC=Lechang site.

Supplementary material: File

Bai et al. supplementary material

Tables S1-S4

Download Bai et al. supplementary material(File)
File 75.9 KB