Catena 175 (2019) 339–348
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Human health risks of heavy metals in paddy rice based on transfer characteristics of heavy metals from soil to rice
Changping Maoa, Yinxian Songb, , Lingxiao Chenc, Junfeng Jic, Jizhou Lib, Xuyin Yuanb, Zhongfang Yangd, Godwin A. Ayokoe, Ray L. Froste, Frederick Theisse a
School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing 210098, China c Key Laboratory of Surﬁcial Geochemistry, Ministry of Education, School of Earth Sciences and Engineering, Nanjing University, Nanjing 210046, China d School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China e Discipline of Nanotechnology and Molecular Sciences, School of Chemistry, Physics and Mechanical Engineering, Science and Engineering Faculty, Queensland University of Technology, 2 George Street, GPO Box 2324, Brisbane, QLD 4001, Australia b
A R T I C LE I N FO
A B S T R A C T
Keywords: Heavy metals Paddy rice Transfer factor Health risk assessment Yangtze River Delta
In order to investigate the transfer and accumulation pathways of heavy metals in cropland ecosystems, an investigation of the geochemical behaviors of heavy metals in soil and rice plants was carried out in the Yangtze River Delta. Soil is one of the biggest reservoirs of heavy metals and aﬀects food safety at the beginning of the food chain. The results of this study demonstrate that heavy metal levels in soil decreased with increasing soil pH, while rice shoots accumulated heavy metals more readily under low soil pH conditions. The non-carcinogenic hazard quotients (HQ) of heavy metals show that health risks for humans were primarily due to Pb and As. Furthermore, cancer risk (Risk) results suggested that ~76% and ~15.7% of cancer risk was caused by Cd and As levels, respectively. Decreasing soil pH enhanced the non-carcinogenic and carcinogenic health risks for the human body. Through exponential change between transfer factor (TFgrain/soil) and soil metals, HQ, a direct monitoring method for rice plants, was built using regression curves. It is proposed that besides condition of soil with high heavy metal concentration, for rice grown with surface soil metals, the safety of the rice product should be monitored when soil metals are under the following levels after harvest: non-carcinogenic risk, As < 20 mg/kg, Pb < 100 mg/kg, Cd < 0.07–0.68 mg/kg and Cu 7.56–30.87 mg/kg; and cancer risk, As < 20 mg/kg, Cd < 4 mg/kg and Cr < 200 mg/kg.
1. Introduction Due to increasing industrial development, the contamination of paddy rice by carcinogenic and toxic pollutants such as heavy metals has increased, with the potential to have an adverse impact on the entire food chain and subsequently on human health (Cheng et al., 2006; McLaughlin et al., 1999; Williams et al., 2009; Williams et al., 2007b). For example, in addition to being carcinogenic, As, Cd, Pb and Hg are known to induce a variety of other adverse eﬀects in humans (IARC, 1993, 2004, 2006). Arsenic in particular can be harmful to the skin, respiratory and cardiovascular systems (IARC, 2004), while Cd and Pb can impact the nervous system and lead to renal failure (Bandara et al., 2008; Yang et al., 2004). The majority of non-occupational exposure of the general population to heavy metals has been shown to result from foods rather than from atmospheric pollution ⁎
(Moon et al., 1995; Watanabe et al., 1998). Given that rice is a staple food in many countries, heavy metal contamination in rice paddies has attracted worldwide attention (Shimbo et al., 2001; Zarcinas et al., 2004). In order to protect humans from consuming heavy metals in their diet, the maximum limits of heavy metals in rice grains in China, the largest producer of paddy rice in the world (FAOSTAT (Food and Agriculture Organization of the United Nations), 2007), are 0.15 mg/kg for As, 0.02 mg/kg for Hg, 0.2 mg/kg for Cd and Pb, and 1.0 mg/kg for Cr (Ministry of Health, 2005). The US Environmental Protection Agency (US EPA) has established an assessment method and criteria for non-carcinogenic and carcinogenic risks of heavy metals through oral, dermal, and inhalation pathways (US EPA, 1989, 2001). This method considers the levels of heavy metals in speciﬁc environmental media, such as soil, sediment, water, atmospheric particles or food, to provide quantitative evaluations of the
Corresponding author. E-mail addresses: [email protected]
(Y. Song), [email protected]
https://doi.org/10.1016/j.catena.2018.12.029 Received 28 November 2017; Received in revised form 29 November 2018; Accepted 16 December 2018 0341-8162/ © 2018 Elsevier B.V. All rights reserved.
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Fig. 1. Distribution of sampling sites in the Yangtze River Delta, China.
et al., 2000). In addition, in some studies, the transfer of heavy metals in soil-rice and shoot-grain had an exponential correlation (Williams et al., 2007a, b). Through these methods, the characteristics of heavy metal transfer in multiple types of media can be measured and understood. It appears that exponential change accurately represents the process of high concentrations of heavy metals accumulating in rice or wheat; however, there are still low levels of metals in the soil (Williams et al., 2007a, b). In this situation, the standard and limits of heavy metals for an individual medium are not enough to monitor the environmental/ecological risk caused by heavy metals. However, early investigations have shown evidence for enhancement of bioavailability and transfer of heavy metals in rice inﬂuenced by soil pH (Bravin et al., 2009; Zeng et al., 2011). According to statistical analyses, acidiﬁcation of cropland soil became serious over the past 20 years (Guo et al., 2010). The eﬀect of soil acidiﬁcation on human health has not been analysed quantitatively. Thus, in this study, rice and soil samples from Yangtze River Delta, which is the oldest and the largest rice-cultivating region in the world (National Bureau of Statistics of China, 2017), were collected and investigated. The goals of this study were to assess the spatial distribution of health (non-carcinogenic and carcinogenic) risks with respect to changes in soil pH through spatial distribution and transfer characteristics of heavy metals, and to build conservative observation levels for heavy metals to connect potential health risks with transfer characteristics and heavy metals in soil.
health risks to humans or the ecological risks. The method also allows for assessment of the accumulation of heavy metals in the human body and potential adverse eﬀects based on data from toxicity experiments. The process of health risk assessment integrates the observation of heavy metal levels in an individual environmental medium, transfer/ translocation of heavy metals from one medium to another, and eﬀects of accumulation in humans. Many studies have applied the EPA method to evaluate heavy metal intake and health risks especially through oral pathways, such as daily intake of heavy metals and health risk due to daily consumption of foodstuﬀs (Llobet et al., 2003; Santos et al., 2004; Zheng et al., 2007; Zhuang et al., 2009), and risks from water and soil (Li et al., 2014; Lu et al., 2015). In some studies, health risks of a speciﬁc pathway or food were also used to identify the environmental or ecological risk caused by human activities. For example, industrial and mining activities could have signiﬁcant impacts on health risk and heavy metal accumulation in humans through rice and vegetable consumption (Cao et al., 2010; Zhuang et al., 2009), but an appropriate change in water source could decrease health risk from heavy metals through consumption of water and rice (Zhang et al., 2015). Heavy metals found in rice mainly come from the soil in which it is grown. Heavy metal pollution in soil is one of the most serious environmental issues in China and many other places around the world (Cheng, 2003; Nriagu, 1988). It is clearly important to understand the potential risk to human health by investigating accumulation and translocation of heavy metals in soil-rice systems. Recent studies have emphasized health risk assessments through the food chain, or environmental pollution status based on health risk (Zhang et al., 2015; Zheng et al., 2007; Zhuang et al., 2009). For crops grown in the soil such as rice, wheat, and vegetables, few studies have reported the correlation between health risk and transfer/translocation of heavy metals. The uptake and transfer of heavy metals is related to the growth of rice. The bioavailable fraction and transfer process of heavy metals can be modelled and characterized mathematically. For example, Zn uptake by rice was successfully described by a model using the BarberCushman approach (Adhikari and Rattan, 2000), and a Freundlich-type function was used to estimate/predict metal content in rice from soil metal analysis (Efroymson et al., 2001; Krauss et al., 2002; McGrath
2. Materials and methods 2.1. Study area and sample collection The Yangtze River Delta is located in eastern China, and it includes Jiangsu Province, Zhejiang Province and Shanghai (28°00′–33°10′N; 118°40′–122°20′E), and generally has a subtropical monsoon climate (Fig. 1). The arable land area is 6736.5 × 103 ha and the annual rice production totalled 2607 × 104 t in 2016 (National Bureau of Statistics of China, 2017). Paired surface soil and rice plant (Oryza sativa L.) samples were harvested from 137 sites in the crop ﬁelds of Jiangsu Province (n = 62), Zhejiang (n = 71) and Shanghai (n = 4) in 2011. At 340
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Table 1 Summary of concentrations (mg/kg) of heavy metals and transfer factor (TF) in grain, shoot and surface soil and soil pH from the rice ﬁelds of the Yangtze River Delta, China.
Min Max Mean Min Max Mean Min Max Mean Min Max Mean Min Max Mean Min Max Mean
0.030 0.340 0.132 ± 0.005 0.210 13.860 3.507 ± 0.238 1.900 18.000 7.267 ± 0.245 0.009 0.476 0.069 ± 0.006 0.035 2.128 0.526 ± 0.038 0.002 0.053 0.020 ± 0.001
0.005 0.692 0.064 ± 0.008 0.018 5.022 0.339 ± 0.053 0.081 3.815 0.356 ± 0.035 0.021 1.127 0.253 ± 0.014 0.057 9.911 1.211 ± 0.149 0.012 1.514 0.224 ± 0.023
1.846 9.014 5.241 ± 0.117 11.774 80.800 26.277 ± 0.838 9.900 295.500 40.961 ± 3.645 0.082 0.343 0.212 ± 0.005 0.073 2.486 0.842 ± 0.037 0.011 0.811 0.172 ± 0.008
0.058 0.807 0.193 ± 0.007 0.224 3.139 0.832 ± 0.035 22.140 191.900 72.910 ± 1.952 0.067 1.040 0.279 ± 0.014 0.003 0.043 0.013 ± 0.001 0.001 0.026 0.003 ± 0.000
0.002 0.017 0.007 ± 0.000 0.007 0.526 0.060 ± 0.008 0.040 0.466 0.146 ± 0.007 0.013 0.909 0.223 ± 0.014 0.054 4.501 0.532 ± 0.072 0.015 0.281 0.058 ± 0.004
0.039 0.233 0.098 ± 0.003 0.704 6.554 1.970 ± 0.085 11.120 89.680 31.633 ± 0.883 0.015 0.202 0.058 ± 0.003 0.022 0.259 0.065 ± 0.003 0.001 0.008 0.003 ± 0.000
13.874 41.640 22.792 ± 0.433 21.389 250.833 63.790 ± 3.090 47.600 470.400 116.532 ± 5.693 0.137 0.899 0.424 ± 0.013 0.155 1.832 0.596 ± 0.025 0.056 0.483 0.223 ± 0.006
– – – – – – 4.64 8.40 6.83 ± 0.08
mixture of 10 ml HCl (ρ = 1.19 g ml−1), followed by 10 ml HNO3 (ρ = 1.42 g ml−1), 10 ml HClO4 (ρ = 1.68 g ml−1) and 10 ml HF (ρ = 1.49 g ml−1) in reactor vessels at 180 °C in a microwave oven (ETHOS TOUCH CONTROL, Milestone Inc., Italy). The digested samples were subsequently diluted to 50 ml with ultrapure deionised water (18.2 MΩ) obtained from a Milli-Q system (Millipore Corp., USA) prior to the chemical analysis.
Table 2 Median concentrations (mg/kg) and probability (P) values of heavy metals in rice grain, shoot, and surface soil in samples with diﬀerent soil pH ranges. Metals
Grain Shoot Soil Grain Shoot Soil Grain Shoot Soil Grain Shoot Soil Grain Shoot Soil Grain Shoot Soil Grain Shoot Soil
pH < 6.5 (n = 53)
pH 6.5–7.5 (n = 43)
pH > 7.5 (n = 41)
0.120 2.800 6.300 0.054 0.296 0.232 5.465 25.192 30.900 0.187 0.765 67.580 0.008 0.036 0.124 0.097 2.111 33.290 25.176 69.648 99.500
0.120 3.780 6.900 0.027 0.141 0.247 5.062 24.280 35.500 0.192 0.845 77.110 0.006 0.028 0.140 0.100 1.739 29.730 21.185 52.625 101.400
0.110 1.720 7.400 0.027 0.095 0.242 5.302 24.632 30.200 0.172 0.740 74.880 0.005 0.023 0.088 0.083 1.379 26.190 20.033 38.075 90.000
0.871 0.453 0.066 < 0.0001 < 0.0001 0.411 0.417 0.394 0.756 0.679 0.382 0.096 < 0.0001 0.001 0.010 0.019 < 0.0001 0.004 < 0.0001 < 0.0001 0.406
2.2.2. Soil The soil samples were air-dried at 25 °C for 2 weeks, then passed through a 2 mm sieve to remove large debris, stones and pebbles before analysis. Small quantities (1.0 g dry weight) of dried soil samples were ground to 80-mesh size (0.2 mm) and dissolved using HCl, HNO3, HClO4 and HF. Samples were digested at 180 °C in a microwave oven (ETHOS TOUCH CONTROL, Milestone Inc., Italy). The digested solutions were diluted with deionised water prior to the chemical analysis. 2.3. Chemical and physical analysis of elements Arsenic and mercury in the samples were measured by hydride generation atomic ﬂuorescence spectrometry (HG-AFS) (XGY-1011A, IGGE, China), using thiourea, hydrochloric acid, ascorbic acid and a 0.07% KBH4 solution as reducing agents. Inductively coupled plasma mass spectrometry (ICP-MS, Thermo ICP-MS X SERIES, Thermo Fisher Scientiﬁc, USA) was used to measure Cd, Cu, Cr, Pb and Zn in the prepared samples and every 10th sample was analysed in duplicate for comparison purposes. The soil samples were also tested for pH using the Delta 320 pH meter (Mettler Toledo Delta 320, Mettler-Toledo Inc., Switzerland).
P values are calculated using Several-Sample Jonckheere-Terpstra Test.
each site where paired samples were collected, one crop ﬁeld was chosen, and four random sub-samples were taken in the ﬁeld. Every paired sub-sample consisted of entire rice plants (grain and shoot) from a ~50 × 50 cm area and a 30–50 g sub-sample of surface soil from 0 to 15 cm directly under the sampled plant after the sub samples of the rice plant were pulled out. The sub-samples taken at each site were mixed to create whole samples for rice and soil.
2.4. Quality control The analysed data was assessed for accuracy and precision using quality assurance and quality control (QA/QC) measures, which included reagent blanks, duplicate samples and certiﬁed reference materials. The certiﬁed reference material GSB-1 was used to validate elemental concentrations in rice plants, while GSF-2, 3 was used for heavy metals in soil, and GSS-2, 3, 4, 6 were used for soil pH. The relative diﬀerence (RD) in values for all replicates was lower than 5%.
2.2. Sample preparation 2.2.1. Plants The raw paddy rice was dried under the sun for 5 days to protect it from degenerating. The shoot and rice ears were separated, and all materials were washed using deionised water to remove soil before air drying at room temperature. Rice ears were threshed to remove the husk and the unpolished rice grains and shoot were air dried and milled. Approximately 0.5 g (dry weight) of milled rice grain and shoot samples were put into separate tubes. The samples were digested with a
2.5. Data and statistics For statistical analyses, concentration data were presented in mg/kg of oven dry-weight soil or paddy rice samples. The transfer factor (TF) 341
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Fig. 2. Spatial distributions of heavy metals in soil, shoot and rice grain from the Yangtze River Delta with Kriging griding interpolation (Kriging griding information shown in Figs. S1 and S2).
2.6. Health exposure risk assessment
Table 3 Median values and probability (P) of transfer factors of heavy metals between rice grain, shoot, and surface soil in samples with diﬀerent soil pH ranges. Metal
Transfer factor (TF)
pH < 6.5 (n = 53)
pH 6.5–7.5 (n = 43)
pH > 7.5 (n = 41)
Grain/shoot Shoot/soil Grain/soil Grain/shoot Shoot/soil Grain/soil Grain/shoot Shoot/soil Grain/soil Grain/shoot Shoot/soil Grain/soil Grain/shoot Shoot/soil Grain/soil Grain/shoot Shoot/soil Grain/soil Grain/shoot Shoot/soil Grain/soil
0.049 0.424 0.020 0.192 1.277 0.211 0.210 0.831 0.179 0.241 0.011 0.003 0.153 0.253 0.043 0.044 0.059 0.003 0.362 0.701 0.245
0.042 0.477 0.017 0.224 0.538 0.101 0.201 0.619 0.133 0.242 0.011 0.003 0.207 0.184 0.045 0.053 0.058 0.003 0.384 0.516 0.193
0.059 0.284 0.016 0.221 0.347 0.094 0.215 0.787 0.181 0.246 0.009 0.003 0.224 0.213 0.059 0.056 0.054 0.003 0.507 0.429 0.210
Human health exposure risk assessment is a method of estimating the probability of adverse health eﬀects in humans who may be exposed to chemicals in contaminated environments. In this study, people who live in the study area were divided into two groups, children and adults, for estimation and analysis. The health exposure risk equation was proposed by the US EPA (US EPA, 1989, 2002, 2011). For estimation of health exposure risk to heavy metals, the average daily intake (ADI) (mg/kg-day) should be calculated using Eq. (1):
0.452 0.098 0.062 0.070 < 0.0001 < 0.0001 0.798 0.535 0.499 0.412 0.035 0.135 0.303 0.314 0.246 0.091 0.054 0.774 < 0.0001 < 0.0001 0.007
C × IR × EF × ED BW × AT
where C is the heavy metal concentration in the rice grain (mg/kg), IR is the ingestion rate of rice (kg/day), EF is the exposure frequency (day/ per year), ED is the exposure duration (year), BW is the body weight of the exposed individual (kg), and AT is the time period over which the dose is averaged (day). In this study, AT can be calculated as: AT = ED × 365 day, for carcinogens ED is 72 years; and average BW is 61.75 kg for adults and 32.75 kg for children (NHFPC (National Health and Family Planning Commission), 2015). The IR for residents in the Yangtze River Delta was selected as 327.9 g/day for adults and 198.4 g/ day for children (Pan et al., 2007; Zheng et al., 2007; Zhong et al., 2006). The non-carcinogenic hazard for a speciﬁc single metal in rice was characterized by the hazard quotient (HQ) calculated using Eq. (2), and the non-carcinogenic hazard for multiple metals (THQ) was calculated using Eq. (3) as follows:
P values are calculated using Several-Sample Jonckheere-Terpstra Test.
represented the ratio of metals in one section of the plant to another or to the soil as shown below:
HQ i = ADIi /RfDi
TFgrain/shoot = Cgrain /Cshoot ; TFshoot/soil = Cshoot /Csoil
∑ HQi i=1
TFgrain/soil = Cgrain /Csoil ;
where RfDi is the reference dose of a speciﬁc metal i. The oral reference doses (mg/kg·day) for As (0.0003), Cd (0.001), Cu (0.04), Cr (1.5), Zn (0.3) were selected from the US EPA Integrated Risk Information System (IRIS) (US EPA, 2016). RfD for Hg (0.00016 mg/kg·day) was calculated by the US EPA, meanwhile Pb was 0.00014 mg/kg·day from Oak Ridge National Laboratory, US (Qu et al., 2012). THQ is the sum of HQ for heavy metal i. If the HQ and THQ are above one, it is considered likely that the exposed people will experience adverse health eﬀects.
where Cgrain, Cshoot, and Csoil represent the metal concentrations in rice grain, shoot and soil respectively. Correlations between the elemental concentrations in the soil and paddy rice were determined using Pearson's correlation analysis and a curve estimate. All statistical analyses were performed using Microsoft Excel and SPSS software (SPSS Inc. Version 16, 2007). 342
Catena 175 (2019) 339–348 1.19 × 10−3 (0.30–3.10 × 10−3) 5.8 × 10−3 (0.05–6.29 × 10−2) – 5.85 × 10−4 (1.74–24.43 × 10−4) – 5.06 × 10−6 (2.03–12.00 × 10−6) – 7.6 × 10−3 (0.21–6.48 × 10−2) 1.05 × 10−3 (0.20–2.70 × 10−3) 5.1 × 10−3 (0.04–5.52 × 10−2) – 5.13 × 10−4 (1.53–21.41 × 10−4) – 4.44 × 10−6 (1.78–10.51 × 10−6) – 6.7 × 10−3 (0.18–5.68 × 10−2)
Consequently, if HQ and THQ are less than one, the heavy metal is thought to be safe for human health (Li et al., 2014; US EPA, 1989). The cancer risk is related to the cancer slope factor (SF). The risk of a single metal can be calculated using Eq. (4), and total risk is the sum of the risks of single metals calculated by Eq. (5):
Riski = ADIi × SFi
3.1. Accumulation of heavy metals in the surface soil and paddy rice 3.1.1. Soil The concentrations of heavy metals in soil, rice shoot and rice grain samples are shown in Table 1. Soil pH ranged from 4.64 to 8.40 with a mean value of 6.83. In this study, heavy metals in soil were at similar levels to those in previous reports (Hang et al., 2009; Williams et al., 2009). Only soil Cd (0.08–3.82 mg/kg) and Hg (0.04–0.466 mg/kg) were slightly higher in comparison to the global range of heavy metals in soil (McLaughlin et al., 1999). According to the soil standards for China (GB15618-1995) (Ministry of Environmental Protection, 1995), more than 50% of samples exceeded the limits for Cd and Zn, which is in accordance with previously reported soil Cd and Zn pollution in this area (Cheng et al., 2005). About 30% of samples were found to be polluted by Cu, Hg and Pb and most soil As levels were below 15 mg/ kg. Heavy metal pollution in soils appeared to be inﬂuenced by soil pH (Blake and Goulding, 2002; Zeng et al., 2011). Hg (P = 0.01) and Pb (P < 0.0001) levels in soil samples decreased signiﬁcantly as pH increased from < 6.5 to > 7.5 (Table 2). This means that low soil pH seemed to enhance the mobilization of Hg and Pb. Levels of As, Cd, Cu and Cr were lower in samples with pH < 6.5, even though the level of these metals did not diﬀer signiﬁcantly under Several-Sample Jonckheere-Terpstra Tests (Table 2).
2.661 0.387 0.794 0.001 0.253 0.165 0.460 4.721 2.332 (0.531–6.018) 0.339 (0.028–3.677) 0.696 (0.245–1.197) 0.001 (0.000–0.003) 0.222 (0.060–0.577) 0.145 (0.058–0.344) 0.403 (0.246–0.737) 4.138 (2.72–8.023)
3. Results and discussion
3.1.2. Shoots Heavy metal concentrations in rice shoot samples are shown in Table 1. The levels of all heavy metals, with the exception of As, were below the standard for feeds in China (General Administration of Quality Supervision and Inspection and Quarantine of the People's Republic of China (AQSIQ), 2001) in most samples. About 60% of samples were polluted by As with levels above 2.0 mg/kg. The variation of As contamination in rice shoots reported in this study was similar to results reported from Spain (Williams et al., 2007b). Shoot samples collected from locations with lower soil pH appeared to contain signiﬁcantly higher levels of Cd (P < 0.0001), Hg (P = 0.001), Pb (P < 0.0001) and Zn (P < 0.0001) (Table 2). Likewise, the levels of As, Cu and Cr in shoots decreased with soil pH, although these diﬀerences were not signiﬁcant. For the samples collected from sites where the soil pH was below 6.5 approximately 30% of shoot samples contained higher levels of Cd than the corresponding soil sample. In addition, 10% of shoot samples contained higher levels of Hg, Cu and Zn than corresponding soil samples. It can be concluded that low soil pH is a risk factor that leads to increased transfer of heavy metals from soil to rice shoots.
As Cd Cu Cr Hg Pb Zn Total
0.700 (0.159–1.805) 0.339 (0.028–3.677) 27.828 (9.801–47.868) 1.026 (0.305–4.283) 0.035 (0.010–0.092) 0.522 (0.210–1.237) 121.028 (73.675–221.113) –
0.798 (0.182–2.060) 0.387 (0.032–4.195) 31.748 (11.182–54.609) 1.171 (0.348–4.886) 0.040 (0.011–0.105) 0.596 (0.239–1.411) 138.074 (84.051–252.256) –
where Riski is the potential risk of a speciﬁc carcinogenic metal, i. The cancer slope factor SF (kg·day/mg) is 1.5 for As and 0.5 for Cr, from US EPA Integrated Risk Information System (IRIS), 0.0085 for Pb and 15 for Cd from California OEHHA Toxicity Criteria Database (Zhang et al., 2015). The Risktotal is the sum of cancer risk of heavy metal i. The cancer risk could be classiﬁed as no signiﬁcant health risk (Riski or Risktotal < 10−6); acceptable/tolerable (10−6 < Riski or −4 Risktotal < 10 ); or unacceptable (Riski or Risktotal > 10−4) (US EPA, 2001).
(0.606–6.866) (0.032–4.195) (0.280–1.365) (0.000–0.003) (0.068–0.659) (0.067–0.392) (0.028–0.841) (2.591–9.153)
Children Adults Adults Adults
Risk HQ ADI (μg/kg·day)
Table 4 Average daily intake (ADI), hazard quotient (HQ), total hazard quotient (THQ), cancer risk (Risk) and total cancer risk (Risktotal) of heavy metals from rice for adults and children (~10-year old). (Values are expressed as “average (min-max)”).
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Fig. 3. Spatial change of THQ with pH (a) for adults; (c) for children, and contribution of individual heavy metals to the THQ (b) for adults; (d) for children.
soil. TFshoot/soil of Cd (P < 0.0001), Cr (P = 0.035) and Zn (P < 0.0001) increased with decreasing soil pH (Table 3). The transfer of Cd and Zn from soil to rice shoot was signiﬁcantly inﬂuenced by soil pH as demonstrated by the results in Table 2. Fig. 2 shows that the high levels of Cd, Cr and Zn in rice shoots occurred in the area with high levels of Cd, Cr and Zn in the soil. Likewise, the spatial distribution of As, Pb, Hg and Cu in soil and rice shoot were similar (Fig. 2), while the TFshoot/soil of As, Pb, Hg and Cu were not signiﬁcantly diﬀerent across regions with diﬀerent soil pH (Table 3). It is therefore reasonable to conclude that low soil pH could increase the transfer of heavy metals from soil to rice plants.
3.1.3. Grain The variation of heavy metal content in the rice grain was similar to that of the shoots. About 36% of samples had As concentrations ranging from 0.03 to 0.34 mg/kg, meaning that some samples had higher As concentrations than the 0.15 mg/ kg government standard for grain (Ministry of Health, 2005). Meanwhile, 13% of samples contained Cd, however, the levels of Cu and Zn fell into the range that could potentially cause health problems (Zhuang et al., 2009). The levels of Cd (P < 0.0001), Hg (P < 0.0001), Pb (P = 0.019) and Zn (P < 0.0001) increased signiﬁcantly in grain grown in low pH soils (Table 2), which echoes the observations reported for rice shoots. This variation of heavy metals in rice grains and shoots was veriﬁed through the observation of the spatial distribution of heavy metals (Cd, Cu, Hg, Pb and Zn) (Fig. 2) (spatial analysis information shown in Figs. S1 and S2). According to the spatial change of heavy metals in soil, rice shoot and grain, it was clear that the soil pH of Jiangsu was higher than that of Zhejiang, at least in the study area, and that low soil pH seemed to enhance the accumulation of heavy metals in rice. Diﬀerences in the distribution of Cu and Cr in the rice might be related to plant metabolism (GardeaTorresdey et al., 2004; Kabata-Pendias and Pendias, 2001).
3.2.2. Shoot to grain transfer Compared with TFshoot/soil, the transfer levels of heavy metals from rice shoot to grain were relatively lower, except for Cr (Table 1). This veriﬁed that heavy metals accumulate in rice shoot based on heavy metal concentrations shown in Table 1. Transfer factors of As and Pb from rice shoot to grain were the lowest, at 0.069 and 0.058, respectively, and TFgrain/shoot of Zn reached 0.424. These could be caused by the activity of toxicity (Johnson et al., 2011) and nutrient metabolism (Kabata-Pendias and Pendias, 2001) of the rice plant. Heavy metal tolerance of rice plants might cause TFgrain/shoot to increase with soil pH, although the TFgrain/shoot of heavy metals were not signiﬁcantly diﬀerent (Table 3). As shown in Figs. S3 and S4, TFgrain/shoot changed exponentially with heavy metal levels in shoot and TFshoot/soil, which displayed the same results as in previous studies (Williams et al., 2007a, b). Heavy metal accumulation in rice was impacted by characteristics of the rice plant. This is consistent with the spatial observation and variation of heavy metals in the rice grain and shoot discussed before.
3.2. Transfer of heavy metals in paddy rice and surface soil 3.2.1. Soil to shoot transfer Based on the ratios of heavy metal concentration in rice grains, shoot and soil, the transfer factors TFgrain/shoot, TFshoot/soil and TFgrain/ soil were calculated and are shown in Table 1. The average TFshoot/soil for Cd and Cu reached 1.211 and 0.8, respectively, which means that Cd and Cu easily enter rice from soil within the study area. The TFshoot/soil levels of Cr (mean value 0.013) and Pb (mean value 0.065) were < 0.1, suggesting it is relatively diﬃcult for Cr and Pb to enter rice from the 344
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Fig. 4. Spatial change of cancer Risktotal (×103) with pH (a) for adults; (c) for children, and contribution of individual heavy metals to the Risktotal (b) for adults; (d) for children.
Non-carcinogenic hazard assessment results calculated using Eq. (2) are shown in Table 4. Although adults consume more rice than children, the hazard quotient (HQ) values of heavy metals for adults were slightly lower than those for children. HQ values of Pb and As were the highest, exceeding 1, meaning that people were exposed to health risks from the consumption of Pb and As. Additionally, the levels of Cd and Cu in some samples could also lead to potential health risks. The total hazard quotient (THQ) values of heavy metals for adults and children reached 7.722 and 8.809, respectively. As displayed in Fig. 3, the variation of the THQ value for adults and children was the same, and the spatial distribution of THQ values decreased signiﬁcantly with increasing soil pH (P = 0.003). As and Pb contributed 30.20% and 48.29% of THQ. Because of the contributions of As and Pb, the THQ distribution is same as the As and Pb of the rice grain shown in Fig. 2. In this study, only As, Cd, Cr and Pb were considered for cancer risk assessment. Cancer risk (Risk) of Cd and As was higher than one of Cr and Pb (Table 4), and the risk of high levels of Cd for adults and children was 0.51 × 10−2 and 0.58 × 10−2 respectively, which means that 51 per 10,000 adults and 58 per 10,000 children are at risk for cancer caused by Cd intake. In the case of As, the Risk was lower at 105 per 100,000 adults and 119 per 100,000 children. The Risk of Pb fell into the acceptable range of 10−6–10−4. As shown in Fig. 4, the spatial distribution of THQ was similar to areas with low soil pH and a higher Risktotal (P < 0.0001). The levels of Cd and As contributed ~76% and ~15.7% of total cancer risk (Risktotal). The risk of Cr with values of 5.13 × 10−4 for adults and 5.85 × 10−4 for children accounted for about 7.7% of total cancer risk, suggesting that low soil pH or soil acidiﬁcation could increase health risk for populations through rice consumption cultivated in ﬁelds contaminated by As, Cd and Cr. Health risk assessment performed through ADI was calculated
3.2.3. Soil to grain transfer The accumulation and transfer of heavy metals in rice grains poses potential risks to human health. In this study, Cd, Cu and Zn had high TFgrain/soil values (> 0.15), which shows that these three metals transferred from soil and accumulated easily in rice grain and thus, have high bioavailability (Table 1). The TFgrain/soil of Cd (P < 0.0001) and Zn (P = 0.007) increased when soil pH decreased signiﬁcantly (Table 3). Lower soil pH seems to increase the transfer of heavy metals from soil to rice, except for Hg. This may be due to characteristics of Hg in the rice grain (Meng et al., 2014). Fig. 2 shows that the spatial distribution of heavy metals in rice grain and soil is similar. The correlation between the levels of heavy metals in rice grain and soil could not be observed directly, however, but according to Fig. S5, a linear correlation between TFgrain/soil and grain metal levels was observed. This result could help in estimating heavy metal pollution in rice through soil pollution surveys. 3.3. Potential health risk assessment of heavy metals According to the method of health risk assessment suggested by the US EPA (US EPA, 1989, 2002, 2011), the non-carcinogenic and carcinogenic health risk assessment of heavy metals can be evaluated and calculated based on the average daily intake (ADI). ADI values of heavy metals through rice consumption are presented in Table 4. Comparing these data with previously reported studies, the ADI of rice in this study is similar to levels recorded in the industrial area in Huludao, China (Zheng et al., 2007), but lower than those in the mining area in Dabaoshan city (Zhuang et al., 2009). The population in the Yangtze River Delta had relatively higher ADI values of Cd and Pb, but lower Hg intake than Spain and Brazil (Llobet et al., 2003; Santos et al., 2004). 345
Fig. 5. Increasing change of soil to grain transfer factor (TFgrain/soil) with increasing non-carcinogenic hazard quotient (HQ) for heavy metals and cancer risk (Risk) for As, Cd, Cr and Pb, and decreasing of soil metals.
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metals were under the following values: As < 20 mg/kg, Pb < 100 mg/kg, Cd 0.07–0.68 mg/kg and Cu 7.56–30.87 mg/kg for non-carcinogenic health risk; As < 20 mg/kg, Cd < 4 mg/kg and Cr < 200 mg/kg for cancer risk.
directly using heavy metal concentrations in the rice grain. As discussed before, the transfer factor of soil to grain (TFgrain/soil) could be used to connect the observation of heavy metals in the rice grain to soil surveys. In addition to the linear correlation between TFgrain/soil and heavy metal levels in rice grain, an exponential relationship between TFgrain/soil and heavy metals in soil was found (Fig. 5). Bridged by TFgrain/soil, health hazard quotient (HQ) and cancer risk (Risk) could be estimated through the heavy metals in soil. And it was clear that TFgrain/soil has the same increased trend with HQ and Risk values, but decreased trend with increasing levels of soil metals (Fig. 5). It can be concluded that the rice product could have high health risk or adverse eﬀects for human when low metal levels were detected in surface soil, because of transfer of heavy metals from soil to rice grain. According to the ﬁtted regression curves between TFgrain/soil and HQ, the observation values of soil metals for rice could be calculated, based on the correlation shown in Figs. 5 and S3. In this study, because the HQ of As and Pb in most samples exceeded 1, there seems to be that the rice product has potential health risk if it was grown in the soil with As levels < 20 mg/kg, or Pb < 100 mg/kg after harvest (Fig. 5). In the case of Cd and Cu, the maximum and minimum observation values can be determined through upper and lower 95% conﬁdence levels for an exponential curve according to the HQ for adults and children (Fig. 5). When soil Cd and Cu levels are between 0.07–0.68 mg/kg and 7.56–30.87 mg/kg, respectively, the rice product could be considered to have a high risk for adverse eﬀects on human health caused by the high Cd and Cu in the study area. If the levels of Cd and Cu in the soil were below 0.07 and 7.56 mg/kg respectively, the transfer level of soil Cd and Cu to the rice grain would be insuﬃcient to give rise to the adverse eﬀect. The Risk values for As, Cd and Cr were above 10−4, which means cancer risk levels of these metals were unacceptable. As shown in Fig. 5, a high cancer risk would be expected with soil As < 20 mg/kg, Cd < 4 mg/ kg and Cr < 200 mg/kg after harvest in this study. For Pb, Risk values of all samples fell into the range of 10−6 to 10−4. Therefore, cancer risk of Pb was tolerable in study area for rice products with soil Pb < 100 mg/kg. Using the transfer factor from soil to rice grain, a rapid method can be built for assessment of rice safety through direct analysis of the soil. A trend was found that there is a potential/possible high health risk in rice products with correspondingly low concentrations of soil metals. More reliable and convenient methods to estimate human health risks through soil surveys must still be developed. Additionally, biomonitoring could be used to improve the assessment observation methods.
Acknowledgement This study was ﬁnancially supported by the the National Key R&D Program of China (grant number 2017YFD0800300), Program design for the Geological Origin Survey and Risk Assessment of soil heavy metals in typical area, Zhejiang Province by Chinese Academy of Geological Sciences (DD20160320-09), the Key Research and Development Project of Jiangsu Province, China (Grant No. BE2015708) and a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). The help of Wancang Zhao is gratefully acknowledged. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.catena.2018.12.029. References Adhikari, T., Rattan, R.K., 2000. Modelling zinc uptake by rice crop using a BarberCushman approach. Plant Soil 227, 235–242. Bandara, J., et al., 2008. Chronic renal failure among farm families in cascade irrigation systems in Sri Lanka associated with elevated dietary cadmium levels in rice and freshwater ﬁsh (tilapia). Environ. Geochem. Health 30, 465–478. Blake, L., Goulding, K.W.T., 2002. Eﬀects of atmospheric deposition, soil pH and acidiﬁcation on heavy metal contents in soils and vegetation of semi-natural ecosystems at Rothamsted Experimental Station, UK. Plant Soil 240, 235–251. Bravin, M.N., Tentscher, P., Rose, J., Hinsinger, P., 2009. Rhizosphere pH gradient controls copper availability in a strongly acidic soil. Environ. Sci. Technol. 43, 5686–5691. Cao, H., et al., 2010. Heavy metals in rice and garden vegetables and their potential health risks to inhabitants in the vicinity of an industrial zone in Jiangsu, China. J. Environ. Sci. 22, 1792–1799. Cheng, S.P., 2003. Heavy metal pollution in China: origin, pattern and control. Environ. Sci. Pollut. Res. 10, 192–198. Cheng, H.X., et al., 2005. A research framework for source tracking and quantitative assessment of the Cd anomalies along the Yangtze River Basin. Earth Sci. Front. 12, 261–272. Cheng, F.M., et al., 2006. Cadmium and lead contamination in japonica rice grains and its variation among the diﬀerent locations in southeast China. Sci. Total Environ. 359, 156–166. Efroymson, R.A., Sample, B.E., Suter, G.W., 2001. Uptake of inorganic chemicals from soil by plant leaves: regressions of ﬁeld data. Environ. Toxicol. Chem. 20, 2561–2571. FAOSTAT (Food and Agriculture Organization of the United Nations), 2007. Food and Agriculture Organization of the United Nations. http://faostat.fao.org/ (accessed Feb. 2016). Gardea-Torresdey, J.L., Peralta-Videa, J.R., Montes, M., De La Rosa, G., Corral-Diaz, B., 2004. Bioaccumulation of cadmium, chromium and copper by Convolvulus arvensis L.: Impact on plant growth and uptake of nutritional elements. Bioresour. Technol. 92, 229–235. General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China (AQSIQ), 2001. Hygienical Standard for Feeds, GB 13078-2001. Guo, J.H., et al., 2010. Signiﬁcant acidiﬁcation in major Chinese croplands. Science 327, 1008–1010. Hang, X.S., et al., 2009. Risk assessment of potentially toxic element pollution in soils and rice (Oryza sativa) in a typical area of the Yangtze River Delta. Environ. Pollut. 157, 2542–2549. IARC (International Agency for Research on Cancer), 1993. IARC Monographs on the Evaluations of Carcinogenic Risks to Humans; Beryllium, Cadmium, Mercury, and Exposures in the Glass Manufacturing Industry Lyon, France. IARC (International Agency for Research on Cancer), 2004. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans; Some Drinking-water Disinfectants and Contaminants, Including Arsenic, Lyon, France. IARC (International Agency for Research on Cancer), 2006. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans; Inorganic and Organic Lead Compounds. Lyon, France. Johnson, A., Singhal, N., Hashmatt, M., 2011. Metal–plant interactions: toxicity and tolerance. In: Khan, M.S., Zaidi, A., Goel, R., Musarrat, J. (Eds.), Biomanagement of Metal-Contaminated Soils. Springer Netherlands, Dordrecht, pp. 29–63. Kabata-Pendias, A., Pendias, H., 2001. Trace Elements in Soils and Plants, 3rd edition. CRC. Krauss, M., Wilcke, W., Kobza, J., Zech, W., 2002. Predicting heavy metal transfer from soil to plant: potential use of Freundlich-type functions. J. Plant Nutr. Soil Sci.
4. Conclusion From the results in this study, it was evident that > 50% of soil samples in the collection area were polluted by high levels of Cd and Zn. In contrast, the main contaminant in the rice shoots was As. The levels of heavy metals in the soil decreased with increasing soil pH, while rice shoots more easily accumulated heavy metals under low soil pH conditions. The spatial distribution of heavy metals in rice grains was the same as that of shoots. Transfer of heavy metals from shoots to rice grains seemed to be aﬀected by characteristics of the rice plant. TFgrain/shoot changed exponentially with the shoot metal levels and TFshoot/soil. According to the non-carcinogenic hazard quotients and cancer risk of heavy metals, people were exposed to health risks primarily due to high levels of Pb and As. Total hazard quotients showed high health risks in the Yangtze River Delta. Cancer risk results suggested that ~76% and ~15.7% of cancer risk was caused by Cd and As. Total noncarcinogenic hazard and cancer risk increased with decreasing soil pH because of enhanced mobility of heavy metals. Through correlation of TFgrain/soil and heavy metals in soil and rice grain, it is clear that the rice product could have high health risk or adverse eﬀects for humans when low metal levels were detected in the surface soil. In this study, the safety of the rice product should be screened and monitored when soil 347
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